SE541804C2 - Methods and control units for determining an extended state of health of a component and for control of a component - Google Patents

Methods and control units for determining an extended state of health of a component and for control of a component

Info

Publication number
SE541804C2
SE541804C2 SE1850392A SE1850392A SE541804C2 SE 541804 C2 SE541804 C2 SE 541804C2 SE 1850392 A SE1850392 A SE 1850392A SE 1850392 A SE1850392 A SE 1850392A SE 541804 C2 SE541804 C2 SE 541804C2
Authority
SE
Sweden
Prior art keywords
component
battery
health
determining
model
Prior art date
Application number
SE1850392A
Other versions
SE1850392A1 (en
Inventor
Klass Verena Löfqvist
Original Assignee
Scania Cv Ab
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Scania Cv Ab filed Critical Scania Cv Ab
Priority to SE1850392A priority Critical patent/SE541804C2/en
Priority to PCT/SE2019/050316 priority patent/WO2019199219A1/en
Publication of SE1850392A1 publication Critical patent/SE1850392A1/en
Publication of SE541804C2 publication Critical patent/SE541804C2/en

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H01M10/486—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte for measuring temperature
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B60L58/16—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/54—Drive Train control parameters related to batteries
    • B60L2240/545—Temperature
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/54—Drive Train control parameters related to batteries
    • B60L2240/547—Voltage
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/54—Drive Train control parameters related to batteries
    • B60L2240/549—Current
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/80—Time limits
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/44—Control modes by parameter estimation
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H01M2010/4271—Battery management systems including electronic circuits, e.g. control of current or voltage to keep battery in healthy state, cell balancing
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M2220/00—Batteries for particular applications
    • H01M2220/20—Batteries in motive systems, e.g. vehicle, ship, plane
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

Abstract

Methods and control units for determining an extended state of health (ESOH) and for controlling a component are presented. The method for determining ESOH includes:- measuring data related to the component during an operation time period tfor the component;- determining, a virtual component corresponding to the component;- predicting, a behavior of the component for at least one predetermined component operation;- determining, a state of health (SOH) for the component;- predicting, a behavior of the virtual component for at least one predetermined component operation, the physics-based component model Mincluding a component aging process;- determining, based on at least one of the predicted behavior of the virtual component and one or more model parameters of said physics-based component model M, an aging status for the component; and- determining the ESOH for the component based on the determined SOH and the determined aging status for thecomponent.

Description

METHODS AND CONTROL UNITS FOR DETERMINING AN EXTENDED STATE OF HEALTH OF A COMPONENT AND FOR CONTROL OF A COMPONENT Field of invention The present invention relates to a method for determining an extended state of health for a component, as defined in the preamble of claim 1, and to a method for control of a component, as defined in the preamble of claim 9. The present invention also relates to a control unit arranged for determining an extended state of health for a component, as defined in the preamble of claim 14, and to a control unit arranged for controlling a component, as defined in the preamble of claim 15. The present invention also relates to a computer program and a computer-readable medium comprising instructions for carrying out the method according to the invention.
Background of invention The following background information is a description of the background of the present invention, which thus not necessarily has to be a description of prior art.
In this document, the presented invention is described mainly for its use for batteries, and primarily in their application for vehicles. However, the present invention may of course also be used in other applications, e.g. for vessels and various other electronic equipment which comprises batteries. The herein presented invention is generally applicable on a large number of components including for example, in addition to batteries, also fuel cells, supercapacitors, combustion engines and/or electrical machines, as is described below.
Batteries are used today in a great number of devices, such as in vehicles, vessels, and in various electronic equipment, such as for example in computers, mobile telephones and toys.
Generally, there are batteries in most electrical devices, that at least partly may be designed so that they can be used without being connected to a power network. In for example vehicles and/or vessels, at least one start battery may be used for starting a combustion engine. Also, at least one traction battery may be used for providing energy to an electrical machine which drives/draws/pulls the vehicle and/or vessel. At least one service battery may further be used for providing electrical appliances with electrical energy in a vehicle and/or a vessel.
A battery comprises one or several battery cells, which may have a number of different designs and may comprise a number of different substances and/or chemical compounds. As a person skilled in the art knows, a battery/accumulator/secondary battery is drained and/or charged when it is used. A battery/accumulator/secondary battery may also loose charge over time when it is not used, due to so called selfdischarge. The battery/accumulator/secondary battery may be charged again by use of an external power source, for example a generator in a vehicle or a vessel, or by use of a battery charger of some type, connected to the battery's poles. Also, the battery/accumulator/secondary battery may be charged by use of inductive charging.
In many applications, such as e.g. in vehicle and/or vessel applications, batteries are exposed to tough operating conditions in terms of, amongst others, duty cycle, temperature, humidity and vibration. Many types of batteries, such as for example lithium-ion batteries, are sensitive systems that may be affected by such tough operating conditions.
In order to protect the batteries from operating conditions that may be potentially unsuitable/detrimental, a management system is often used to control the batteries. The main task of a battery management system (BMS) is to avoid detrimental operating conditions, such as e.g. overcharging and/or overheating. Such detrimental operating conditions may lead to problems related to safety, reliability, performance and/or life time for the batteries. In order to protect the batteries from such detrimental operation conditions, the battery management system may be arranged to ensure that the batteries are only used within certain limits related to voltage, current, temperature and/or state-of-charge/state of charge (SOC).
Correspondingly, other components, such as combustion engines and/or electrical machines, may also be exposed to potentially harmful/tough operating conditions. Such other components may therefore also be controlled by management systems in order to reduce the risk that the operation conditions have a negative effect on the other components.
SUMMARY OF INVENTION Some components, for example some batteries, such as lithiumion batteries, include complicated systems still not being fully understood. As a non-limiting example, it may be mentioned that a number of electrochemical, chemical, physical and/or mechanical processes occur within lithium-ion batteries. These processes may be affected by the operating conditions of the batteries, and they may also depend on each other. As a consequence, the processes are therefore not easy to predict.
For example, in order to be on the safe side, components, such as e.g. batteries, are therefore often oversized, i.e. are designed with more capacity than actually needed. Oversizing results in a poor utilization degree of the valuable component in terms of performance, and specifically in terms of allowed maximum and minimum state of charge (SOC) for a battery. The oversizing may result in unnecessary high costs, high weights and/or large volumes for the components.
Further, current component management systems, such as e.g. current battery management systems, struggle to estimate, among other parameters, state-of-health/state of health (SOH) accurately. Especially, a sufficiently accurate state of health estimation method which runs during normal vehicle operation, i.e. when e.g. the vehicle including the component is in use, e.g. travels on a road section, is still an unsolved research challenge.
Some of the known methods for estimating state of health are based on simplified battery models, e.g. equivalent circuit models, and the known component management systems are rulebased, i.e. they use static limits, which makes the estimations inaccurate and makes the component management suboptimal.
Some other known methods for estimating state of health are based on aging experiments, in which the usage of the component, e.g. a battery, is logged online, whereby the energy flowing through the battery is logged. The energy is then translated into a state of health for the battery based on aging observed over time at one specific energy throughput during the experiments. Such experiment-based methods may not be performed during normal operation of the component. They are also very time-consuming and expensive, as several years of lab testing is required in advance of the application/implementation of a component in a product. Due to the broad variety of possible different operating conditions and duty cycles, for example for vehicle applications, the performed experiments may not represent real-life situations/operations for the component. Therefore, the experiment-based methods may result in inaccurate values for real-life situations/operations for the component, which in turn makes the component management inflexible and suboptimal.
It is therefore an object to solve at least some of the abovementioned disadvantages.
The object is achieved by the above-mentioned method for determining an extended state of health (ESOH) for a component according to the characterizing portion of claim 1, the method including : - measuring data related to the component during at least one operation time period tmeasurefor the component; - determining, based on a data-based component model Mcomponent_datarelated to the measured data, a virtual component corresponding to the component; - predicting, based on the data-based component model Mcomponent_data, a behavior of the component for at least one predetermined component operation; - determining, based on the predicted behavior of the component, a state of health (SOH) for the component; - predicting, based on a physics-based component model Mcomponent_physics, a behavior of the virtual component for at least one predetermined component operation, the physics-based component model Mcomponent_physicsincluding at least one component aging process; - determining, based on at least one of the predicted behavior of the virtual component and one or more model parameters of said physics-based component model Mcomponent_physics, an aging status for the component; and - determining the extended state of health (ESOH) for the component based on the determined state of health (SOH) and the determined aging status for the component.
Hereby, an accurate resulting extended state of health for the component is estimated and is available for the component management system. An aging sensitive component management system, which takes aging of the component into consideration, is provided, whereby usage of the present invention enables rightsizing of the component, instead of the conventionally used oversizing of the component. The extended state of health for the component may thus be based also on the actual aging mechanisms that affect the component performance, e.g. by causing a decreased capacity and an increased resistance for a battery component.
The physics-based component model Mcomponent_physicsmay be used for deriving/determining/identifying the ongoing aging processes for the component, whereby extensive laboratory testing of the component may not be necessary. Also, the physics-based component model Mcomponent_physicsused according to the present invention facilitates access to very detailed component information, including aging information, which makes an optimized control of the component possible. For example, a reduced capacity or an increased resistance of a battery may be the result of various aging mechanisms. Based on the detailed aging information being provided by the embodiments of the present invention, the component control described herein may react differently depending of the nature of the determined present aging mechanism.
For example, knowledge of a battery's aging status, which is gained/determined according to the present invention, gives the component management system the possibility to safely minimize the so called "safety zones" of an oversized battery, since the battery becomes more predictable when this knowledge is available. Hereby, a higher utilization degree of the battery may be achieved.
A resulting benefit from the rightsized and well-utilized battery is a lower cost for the installed energy unit, as the usable energy, e.g. in terms of usable kWh, for the battery can be increased. A component management system having knowledge of the aging status of a component e.g. onboard a vehicle facilitates a customized battery control, which is advantageous in terms of improved component life time and performance.
Based on the determined extended state of health for the component, the component management system may dynamically adjust a number of parameters when the component is controlled, which is a great advantage compared to the conventional fixed parameters used in rule-based component management systems.
The dynamical adjustment of usage limits based on the determined extended state of health for the component results in an improved utilization level and a safer component operation when compared to the conventional rule-based component management systems, such as rule-based battery management systems. For the conventional rule-based battery management systems, the usage limits are traditionally static, which results in the low utilization degree of today's battery systems, as usage limits are set at the beginning of life (BOL) for the battery, whereby battery lifetime issues are taken into account already when the limits are set.
Also, the determination of the extended state of health and the component control according to the present invention may be used for scheduling predictive maintenance for example at service stations, e.g. for vehicles. Such scheduling may then be based on the aging status for the component, which makes it reliable and accurate, and also possible to be performed well in advance before the maintenance has to be made, which minimizes the disturbance for the user.
Thus, usage of the present invention has a number of advantages. During development of an entity including the component, e.g. of a vehicle including a battery, the increased knowledge of the component behaviour gained by the present invention makes the characteristics of the component more predictable, and therefore also enables rightsizing instead of oversizing. Rightsizing results in lower costs, volumes, and weights for the components, which is advantageous.
During use of an entity including the component, e.g. of a vehicle including a battery, the utilisation degree can be increased for the component, e.g. in terms of power and a usable state of charge window for a battery, thanks to the provided dynamic component control.
Further, the usage of the embodiments of the present invention also provides for an improved safety as a result of the gained knowledge related to which aging mechanisms are occurring for the component. Also, the extended state of health determined makes accurate predictive maintenance of the components possible.
According to an embodiment of the present invention, the measured data is time resolved.
According to an embodiment of the present invention, the databased component model Mcomponent_datais a machine learning model including at least one input and at least one output.
According to an embodiment of the present invention, the component is a battery or a battery cell, and one or more of the at least one input and the at least one output is related to at least one in the group of: - a measured current value i; - a moving average current value itdetermined based on at least two measured current values i and on a function of points in time t when the at least two current values i are measured; - a measured temperature value T; - a measured voltage value v; - a measured pressure value p; - a measured length value 1; and - a measured impedance value z.
According to an embodiment of the present invention, the physics-based component model Mcomponent_physicsis derived based on at least one in the group of: - the data-based component model Mcomponent_data; - a component specification; and - at least one laboratory test.
According to an embodiment of the present invention, the physics-based component model Mcomponent_physicsis determined based on: - a mathematical model describing at least one of an electrochemical, a physical, a chemical, and a thermal behavior of the component by usage of at least one equation; - a geometry of the component.
According to an embodiment of the present invention, the component is a battery or a battery cell, and the at least one predetermined component operation includes at least one in the group of: - a standard performance test; - a current pulse test; - a constant current discharge test; - a constant current charge test; - galvanostatic intermittent titration technique (GITT) test; and - a current profile test.
According to an embodiment of the present invention, the component includes at least one in the group of: - a battery; - a traction battery; - a start battery; - a service battery; - a battery cell; - an electrical machine; - a fuel cell; - a supercapacitor; and - a combustion engine.
The object is also achieved by the above-mentioned method for control of a component according to the characterizing portion of claim 9, the method including: - determining an extended state of health (ESOH) for the component according to any one of the herein mentioned embodiments; and - controlling the component based at least on the determined extended state of health (ESOH) for the component.
The component is hereby controlled e.g. by a component management system, based on the knowledge gained and included in the extended state of health for the component, such that the component control may be performed based also on the aging status/information related to the component. The component may, based on this information, be dynamically controlled by adjustments of one or more usage limits for the component, such that the component usage is optimized based on the current extended state of health information including also aging information.
An optimized usage of the component may hereby be provided, which is related to the current aging of the component. For example, a lifetime and/or a performance of a battery may hereby be optimized in accordance with the expectations of the customer/user .
According to an embodiment of the present invention, the controlling of the component is based also on at least one in the group of: - a requested component safety; - a requested component life time; - a requested component performance; - a requested balance between component life time and component performance; - a component purpose; - a present component state; - external component operating conditions; - a predicted future component usage; - a predicted remaining useful life (RUL) for said component; and - a predicted remaining battery charge and/or mileage for said component.
According to an embodiment of the present invention, the component is a battery or a battery cell, and the controlling includes at least one in the group of: - an adjustment of a maximum continuous battery charge current icharge_max_cont; - an adjustment of a maximum peak battery charge current icharge_max_peak; - an adjustment of a maximum continuous battery discharge Current idischarge_max_cont; - an adjustment of a maximum peak battery discharge current idischarge_max_peak; - an adjustment of a set temperature Tsetof a battery climate system; - an adjustment of a maximum temperature Tmaxof a battery climate system; - an adjustment of a minimum temperature Tminof a battery climate system; - an adjustment of a maximum battery cell voltage vmax; - an adjustment of a minimum battery cell voltage vmin; - an adjustment of an open circuit battery voltage curve used for state of charge (SOC) estimation; - an adjustment of an estimated battery capacity used for state of charge (SOC) estimation; - an adjustment of an estimated battery resistance; - an adjustment of a minimum battery state of charge (SOC); - an adjustment of a maximum battery state of charge (SOC); and an adjustment of a preferred battery state of charge (SOC).
The object is also achieved by the above-mentioned control unit arranged for determining an extended state of health (ESOH) for a component according to the characterizing portion of claim 14. The system includes: - first means arranged for measuring data related to at least one feature of the component, the measuring encompassing at least one operation of the component during a time period Tmeasure; - second means arranged for determining, based on a data-based component model Mcomponent_datarelated to the measured data, a virtual component corresponding to the component; - third means arranged for predicting, based on a data-based component model Mcomponent_data, a behavior of the component for at least one predetermined component operation; - fourth means arranged for determining, based on the predicted behavior of the component, a state of health (SOH) for the component; - fifth means arranged for predicting, based on a physicsbased component model Mcomponent_physics, a behavior of the virtual component for at least one predetermined component operation, the physics-based component model Mcomponent_physicsincluding at least one component aging process; - sixth means arranged for determining, based on at least one of the predicted behavior of the virtual component and one or more model parameters of said physics-based component model Mcomponent_physics, an aging status for the component; and - seventh means arranged for determining the extended state of health (ESOH) for the component based on the determined state of health (SOH) and the determined aging status for the component .
The object is also achieved by the above-mentioned control unit arranged for controlling a component according to the characterizing portion of claim 15. The system includes: - means arranged for determining an extended state of health (ESOH) for the component according to any one of the herein described embodiments; and - means arranged for controlling the component based at least on the determined extended state of health (ESOH) of the component.
The object is also achieved by the above-mentioned computer program and computer-readable medium.
The control units, the computer program and the computerreadable medium have advantages corresponding to the ones mentioned above for the corresponding methods.
Detailed exemplary embodiments and advantages of the method, control units, computer program and computer-readable medium according to the invention will below be described with reference to the appended drawings illustrating some preferred embodiments.
BRIEF DESCRIPTION OF THE DRAWINGS Embodiments of the invention are described in more detail with reference to attached drawings illustrating examples of embodiments of the invention in which: Figure 1 is a schematic illustration of a non-limiting example of a vehicle in which the present invention may be implemented, Figure 2 shows a flow chart diagram for some embodiments of the present invention, Figure 3 shows a flow chart diagram for some embodiments of the present invention, and Figure 4 is a schematic illustration of a control unit according to some embodiments of the present invention.
DETAILED DESCRIPTION OF INVENTION Figure 1 schematically shows an example vehicle 100, which may be used for explaining the present invention. As mentioned above, the present invention may be generally applicable on many sorts of components, not limited to vehicle components. The present invention is, thus, not limited to use in vehicles as the one shown in figure 1, and may also be used in many other applications. The vehicle shown in figure 1 is thus a non-limiting example.
The vehicle 100, which may be a passenger car, a truck, a bus or another vehicle, comprises a drive line, which conveys power to driving wheels 111, 112 in the vehicle 100. The drive line may comprise a propulsive component 110, which in a customary manner, via an output shaft of the propulsive component 110, is connected to a gearbox 103 via a clutch 106. The propulsive component 110 may for example include an electric machine 102, a combustion engine 101, and/or both an electrical machine and a combustion engine 101, 102. The drive line of the vehicle may be arranged in various ways, such as comprising a conventional manual gearbox or an automatic transmission and a coupling 106, and may also be a hybrid drive line, etc. An output shaft 107 from the gearbox 103 drives the wheels 111, 112 via a final drive 108, such as e.g. a customary differential, and drive shafts 104, 105 connected to the final drive 108. The driveline, and the vehicle as a whole, may be designed in a large number of ways, which is understood by a skilled person. For example, electrical machines 102 may be located differently than shown in figure 1, e.g. closer to the drive wheels. Also, some shown parts of the vehicle, such as the gearbox and/or the clutch, may be omitted in some designs. Thus, as mentioned above, the vehicle shown in figure 1 is a non-limiting example used for explaining the present invention. The invention may, however, be implemented in essentially any entity including a component for which the extended state of health is determined by use of the herein described invention.
The vehicle comprises at least one battery component 150. If the propulsive component 110 comprises an electric machine 102, the battery component 150 includes a traction battery 151 used to at least partly drive the electric machine 102. If the propulsive component 110 includes a combustion engine 101, which is driven by fuel, the battery component 150 includes a start battery 152 used, among others, to drive a start engine in the engine 101 and/or to provide power to the engine's ignition system. The battery component 150 may also include a service battery 153 providing power to operate electric equipment 130 in the vehicle. This electric equipment 130, which is illustrated schematically in figure 1, may comprise, among others, headlights and other lights, miscellaneous instruments, wipers, seat heaters, stereo equipment, video equipment, cigarette lighters and/or sockets for external equipment connected to the vehicle.
A control unit 140 arranged for determining an extended state of health (ESOH) and a control unit 170 arranged for controlling at least one component 150, 110 are in figure 1 schematically illustrated as receiving signals and/or providing control signals from and/or to the propulsive component 110 and/or the battery component 150. The control units 140, 170 may also receive and/or provide control signals to and/or from other devices/components in the vehicle 100.
The control units 140, 170 may be connected to an internal communication unit 180. The internal communication unit 180 may then be arranged for communication with at least one communication unit 185 external to the vehicle 100, e.g. via a wireless connection using a suitable communication protocol.
The external/offboard communication unit 185 may be connected to at least one external/offboard entity 186, such as e.g. a server, database, computer or any other data and/or information processing entity.
According to some embodiments of the present invention, as described in this document, the control unit 140 may comprise first means 141 arranged for measuring data, e.g. a first measuring unit 141, second means 142 arranged for determining a virtual component, e.g. a second virtual component determining unit 142, third means 143 arranged for predicting a behavior, e.g. a third behavior predicting unit 143, fourth means 144 arranged for determining a state of health, e.g. a fourth state of health determining unit 144, fifth means 145 arranged for predicting a behavior, e.g. a fifth behavior predicting unit 145, sixth means 146 arranged for determining an aging status, e.g. a sixth aging status determining unit 146, and seventh means 147 arranged for determining an extended state of health, e.g. a seventh extended state of health determining unit 147. According to some embodiments of the present invention, as described in this document, the control unit 170 may also include eighth means 148 arranged for controlling a component, e.g. an eighth component controlling unit 148. These control means/units/devices 141, 142, 143, 144, 145, 146, 147, 148, are described more in detail below, and may be divided physically into more than the herein described control means/systems/units 140, 170, or may be arranged in less control systems/units than herein described.
As mentioned above, the processes of some components, such as e.g. of lithium-ion batteries, are very complex and are not easily predicted, which may lead to design problems, such as oversizing, to poor utilization degrees and/or to difficulties in providing accurate state of charge (SOC) and/or state of health (SOH) estimations.
Figure 2 shows a flow chart diagram for a method 200 according to an embodiment of the present invention, i.e. a method for determining an extended state of health (ESOH) of a component, which aims at solving at least some of these problems. The method steps of figure 2 may for example be performed during normal operation of the component for which the extended state of health (ESOH) is to be determined, e.g. when the propulsion component 110 of a vehicle 100 is running and/or when the battery component 150 is utilized in some herein described way. The component 150, 110 may, according to various embodiments of the present invention, include a battery 150, a traction battery 151, a start battery 152, a service battery 153, a battery cell, an electrical machine 102, a fuel cell, a supercapacitor, and/or a combustion engine 101. Generally, the present invention may be applicable on essentially any component which has an aging mechanism being difficult, i.e. not easy, to predict and which may benefit from the herein presented embodiments. The present invention is for example advantageous for relatively expensive components, for which maintenance should be accurately and reliably predicted.
In a first step 210 of the method according to the present invention, data related to the component 150, 110 is measured during at least one operation time period tmeasurefor the component 150, 110, e.g. by use of a below described first measuring unit/means 141.
The data may, according to an embodiment of the present invention, be measured and/or sampled at a predetermined frequency, for example a 1 Hz sampling frequency, during normal operation of the component.
The measurements may for example be performed using one or more sensors measuring currents, voltages and/or temperatures related to the component, e.g. related to a battery and/or on a battery cell.
According to an embodiment of the present invention, the measured data is time resolved, i.e. includes time series data. Hereby, dynamical changes of the data may be detected and may be processed/analyzed, such that the dynamical properties of the component may be used as a base for the determination of the extended state of health for the component.
Generally, the processing/analysis/calculation/computation described in this document may be performed essentially at any location, for example onboard a vehicle 100 or a vessel, or in an offboard entity 186 being in communication with the vehicle 100 or vessel, e.g. via the above mentioned internal 180 and external 185 communication units. For example, the measured data may thus be processed onboard the vehicle 100 and/or may be at least partly transferred offboard and processed in an external offboard entity 186. The offboard entity 186 may e.g. be a server, database, computer or the like at a suitable location. Measurement/collection of data and/or transfer of the data offboard may be requested at predetermined points in time, may be triggered by predetermined operation conditions, and/or may be triggered by measurements/identification of a certain battery behavior. Measurements should, according to an embodiment, cover/encompass a predetermined time period, i.e. the above-mentioned operation time period tmeasurefor the component. As a non-limiting example, such a time period tmeasuremay be 30 minutes long.
In a second step 220 of the method according to the present invention, a virtual component 160 corresponding to the component 150, 110 is determined based on a data-based component model Mcomponent_datarelated to the component related data measured in the first step 210, e.g. by use of a below described second determining unit/means 142. The virtual component 160 is schematically illustrated in figure 1.
In a third step 230 of the method according to the present invention, a behavior of the component 150, 110 for at least one predetermined component operation is predicted based on the data-based component model Mcomponent_data, e.g. by use of a below described third predicting unit/means 143. This prediction of the behavior of the component 150, 110 may be seen as a virtual test for the component 150, 110.
Thus, the data-based component model Mcomponent_datamay, according to embodiments of the present invention, be used for capturing/determining a behavior of the component, e.g. of a battery, based on the measured/collected 210 data at a suitable point of time, such that a virtual component 160 may be determined 220. The virtual component 160, and thus also the data-based component model Mcomponent_data, may be used for predicting/determining 230 a behavior of the component 150, i.e. the real component 150, during at least one predetermined component operation, which may e.g. be a standardized performance test, as described more in detail below.
The measured/collected 210 data used for determining the databased component model Mcomponent_dataand/or the virtual component 160 may be seen as training data. The predetermined component operation may then be seen as providing essentially any other data than the training data, where the other data, i.e. the component operation data, should be suitable for performing the virtual test of the performance of the component model.
In a fourth step 240 of the method according to the present invention, a state of health (SOH) for the component 150, 110 is determined based on the behavior of the component 150, 110 predicted in the third step 230, e.g. by use of a below described fourth determining unit/means 144.
According to an embodiment of the present invention, the state of health is determined 240 in relation to an initial performance of the component 150, 110, i.e. is determined in relation to a so-called beginning of life (BOL) performance for the component. The beginning of life performance for the component 150, 110 may be determined in a corresponding way as the state of health for the component 150, 110 is determined and/or may be determined based on a component specification. For example, if the component is a battery component 150, a battery specification for that battery 150 may be used for indicating a beginning of life performance. Alternatively, a state of health determined in connection with the very first time the battery was brought into operation may be used for indicating a beginning of life performance. The state of health may for example be determined related to a ratio between the currently determined component performance and the beginning of life performance for that component, e.g. may be determined as a percentage of the beginning of life performance for the component. Thus, Image available on "Original document" where X is a performance measure of the component at the present/current moment and XBOLis the performance measure when the component was new, i.e. at its beginning of life (BOL). X could e.g. be capacity or resistance in case of the component being a battery.
Also, a combined state of health may be calculated: Image available on "Original document" where SOH is a combined SOH for different performance measures SOHx1to SOHxnfor the component, n is the number of considered performance measures and wi to wnis the weight that the performance measures are weighted with in order to determine the total SOH.
According to an embodiment of the present invention, the state of health determined in the fourth step 240 is stored in, i.e. is added to, a matrix including also various operating conditions. Thus, the matrix may then for each determined state of health value also include corresponding values related to operation conditions for that state of health. Such operation conditions may for example include component temperatures and/or state of charge values.
In a fifth step 250 of the method according to the present invention, a behavior of the virtual component 160 is predicted for at least one predetermined component operation based on a physics-based component model Mcomponent_physics, e.g. by use of a below described fifth predicting unit/means 145. The physics-based component model Mcomponent_physicshere includes at least one component aging process, which is utilized by the present invention in the following steps. The physics-based component model Mcomponent_physicsis updated/adjusted to the present component behavior when the fifth step 250 is performed. Thus, according to an embodiment of the present invention, the fifth step 250 of the model includes and/or corresponds to updating/adjusting/adapting one or more model parameters of the physics-based component model Mcomponent_physicsto the present/current component behavior.
The at least one predetermined component operation used in the fifth step 250 for predicting the behavior of the virtual component 160 may, according to an embodiment of the present invention, correspond to, e.g. be equal to, the at least one predetermined component operation used in the third step 230 for predicting the behavior of the component 150, 110.
According to another embodiment of the present invention, the at least one predetermined component operation used in the fifth step 250 may be different from the at least one predetermined component operation used in the third step 230. Generally, one or more virtual tests may be used for updating/determining/predicting the model parameters of the physics-based component model Mcomponent_modelbased on the databased component model Mcomponent_dataand/or the virtual component.
In a sixth step 260 of the method according to the present invention, an aging status for the component 150, 110 is determined based on at least one of the predicted behavior of the virtual component 160 and one or more model parameters of said physics-based component model Mcomponent_physics, e.g. by use of a below described determining unit/means 146. In this document aging status is defined as the type of aging mechanisms occurring in the component and/or to which extend the aging mechanisms occur in the component. The aging status is estimated based on the physics-based component model.
According to an embodiment of the present invention, information related to the aging mechanisms, and thus also the aging status, may be determined based on model parameters for the physics-based component model Mcomponent_physics, for example based on parameters related to a thickness of resistive surface films and/or a contact resistance. Thus, aging status related information may, according to an embodiment, be read from, and/or may be determined directly based on, the model parameters for the physics-based component model Mcomponent_physics.
In a seventh step 270 of the method according to the present invention, the extended state of health (ESOH) for the component 150, 110 is determined based on the determined state of health (SOH) and on the determined aging status for the component 150, 110, e.g. by use of a below described seventh determining unit/means 147.
According to an embodiment of the present invention, the extended state of health determined in the seventh step 270 is stored in, i.e. is added to, a matrix including also various operating conditions. Thus, the matrix may then for each determined extended state of health value also include corresponding values related to operation conditions for that extended state of health. Such operation conditions may for example include component temperatures and/or state of charge values.
The determination of the extended state of health for the component 150, 110, i.e. the method 200, may be performed during normal operation of the component 150, 110, for example during normal vehicle operation, i.e. when the vehicle including the component is in use. During normal operation, a start battery may e.g. be used for starting an engine and/or a traction battery may be used for driving an electrical machine and/or a propulsion component may be used for moving e.g. a vehicle.
Knowledge of an aging status for the component, such as an aging status for a battery, is provided when the present invention is used, which gives the component management system the possibility to increase the utilization degree of the component, e.g. of a battery. Thus, an aging sensitive component management system, which takes aging of the component into consideration, is provided by the present invention.
Based on the determined extended state of health for the component, a dynamical adjustment of a number of parameters may be performed by the component management system when the component is controlled, which also results in a safer and more reliable component operation when compared to the conventional rule-based component management systems.
Also, reliable and early scheduling of component maintenance based on the aging status for the component is made possible when the present invention is utilized.
According to an embodiment of the present invention, the databased component model Mcomponent_dataused for determining 220 the virtual component 160 is a machine learning model including at least one input and at least one output. A machine learning model may include one or more modelling methods that learn from, i.e. are adapted based on, data. The at least one input and the at least one output of a machine learning model may be included in, i.e. may be a part of, the component related data measured in the first step 210 of the method according to the present invention. The data-based component model may e.g. be created by using one or more modelling techniques, such as e.g. support vector machine modelling techniques, neural network modelling techniques, artificial intelligence modelling techniques, and/or system identification modelling techniques, based on varying model architectures, i.e. choices of input and output variables, and diverse operation conditions.
For an embodiment where the component is a battery 150 or a battery cell, one or more of the at least one input and the at least one output may be related to one or more of a number of measured values for the battery 150 or the battery cell, for example a measured current value i, a moving average current value itdetermined based on at least two measured current values i and a function of points in time t when the at least two current values i were measured, a measured temperature value T, a measured voltage value v, a measured pressure value p, a measured length value 1, and a measured impedance value z. The length 1 may be the length of a battery cell or a battery module. The cells and/or modules have a tendency to expand/swell when they age.
According to an embodiment of the present invention, a moving average current value itis determined based on input current values i measured over a period of time including a number of points in time t. A time function may be utilized when computing/determining the moving average current value it, which weighs more recent samples/measurements of the current such that they have more influence on the moving average current value itthan earlier samples/measurements have. Thus, the later/more recent samples/measurements are then more important for the moving average current value itthan the earlier/less recent samples/measurements have. Generally, for many components, such as e.g. batteries, the history of the component, e.g. the historic use of the component is an important parameter for determining a current state of health for the component. The component history is at least partly reflected in the moving average current value itaccording to an embodiment of the present invention.
As mentioned above, the data-based component model Mcomponent_data, may be used for predicting/determining 230 a behavior of the component 150, during at least one predetermined component operation. Such predetermined component operations may include a large number of operations, and may for example correspond to a simpler, i.e. lower complexity, operation than a normal, i.e. real life, operation of the component. Thus, the predetermined component operations may correspond to a suitable/appropriate test sequence.
The predetermined component operation may, according to an embodiment, include at least one standardized performance test. The standardized performance tests may be repeated at different occasions during a component life, such that the component behavior may be compared/analyzed in terms of state of health.
For embodiments for which the component is a battery 150 or a battery cell, the predetermined component operation may include a current pulse test, which makes it possible to perform a resistance estimation for the battery 150.
For embodiments for which the component is a battery 150 or a battery cell, the predetermined component operation may include a constant current discharge test, which makes it possible to perform a capacity estimation for the battery 150.
For embodiments for which the component is a battery 150 or a battery cell, the predetermined component operation may include a constant current charge test, which makes it possible to perform a capacity estimation for the battery 150.
For embodiments for which the component is a battery 150 or a battery cell, the predetermined component operation may include a galvanostatic intermittent titration technique (GITT) test and/or a similar simplified test, e.g. a zerocurrent and/or a close-to-zero current test at various state of charge levels and temperatures, which makes it possible to perform a state of charge (SOC) estimation for the battery 150 based on a measured open circuit voltage (OCV) in relation to an estimated state of charge curve derived from the virtual test 230. Thus, an OCV-SOC curve may here be estimated based on a virtual/simplified test, such as e.g. a GITT test. Then, a measured OCV-value may be used for determining a SOC value based on the estimated OCV-SOC curve.
For embodiments for which the component is a battery 150 or a battery cell, the predetermined component operation may include a current profile test, which may be recorded/measured during operation of the battery 150.
According to an embodiment of the present invention, the physics-based component model Mcomponent_physics, used for the prediction 250 of the virtual component behavior, is derived based on one or more of the data-based component model Mcomponent_data, a component specification, and at least one laboratory test. For example, the parametrization of the physics-based component model Mcomponent_physicsmay in some implementations be derived based on virtual tests of the databased component model Mcomponent_data, whereby laboratory tests may be avoided, i.e. may be unnecessary. The component specification may for example include a battery, engine or machine specification listing all essential data for the component, from which data may be extracted. The physics-based component model Mcomponent_physicsmay at least partly be based on such a component specification.
According to an embodiment of the present invention, the physics-based component model Mcomponent_physicsis determined based on a mathematical model and on a geometry of the component 150. The geometry may be determined based on component specification and/or on tests, such as laboratory tests, performed on the component. The mathematical model may describe an electrochemical, a physical, a chemical, a mechanical, an electrical, a thermodynamical, a kinetic and/or a thermal behavior of the component by usage of at least one mathematical equation. The parameters for the mathematical model may be derived based on the above-mentioned virtual test of the data-based component model Mcomponent_data.
The physics-based model for e.g. a battery or a battery cell is used to also predict the battery behavior during the selected virtual tests. Depending on if, which, and to which extent aging processes are necessary to be included in the model in order to properly describe the battery behavior during the virtual tests, the aging status is determined/estimated.
The history of the battery, e.g. how old the battery is, how much current has passed through the battery (i.e. so-called Ah counting), how much time the battery has spent in different state of charges, current magnitudes, temperature levels, and/or which depths of discharge (DOD) have occurred may also be useful for determining the aging mechanisms/processes for the battery.
When the physics-based component model Mcomponent_physicsis determined as described above, at least one component aging process is included in the physics-based component model Mcomponent_physics. Hereby, the predicted 250 behavior of the virtual component 160, which is based on the physics-based component model Mcomponent_physics, may be used for determining which aging processes are responsible for the behavior of the virtual component, and how these processes have influenced, are influencing, and/or in the future will influence the component behavior.
The aging processes included in the physics-based component model Mcomponent_physicsmay for a battery 150 or a battery cell be related to, e.g. may include, the increase of a thickness of resistive surface films and/or a modification of the composition of the surface films, e.g. the solid electrolyte interphase (SEI) which is a surface film on the electrode composed of electrolyte decomposition products, which increases in thickness. The aging processes may also be related to, e.g. may include, a number/an amount of cracked particles, since the active material particles may crack e.g. as a result from intercalation/de-intercalation of lithium and the related volume changes. A particle size distribution may then be adjusted in the physics-based component model Meomponent_physics· The aging processes may also be related to, e.g. may include, a quality of an electrical contact, which may include e.g. a loss of electronically conductive additive. A local contact resistance may then be adjusted in the physics-based component model Mcomponent _physics.
The aging processes may also be related to, e.g. may include, an amount of lithium plating, including e.g. plating of metallic lithium on the negative electrode and dendrite formation, which increases the risk for short circuit.
The aging processes may also be related to, e.g. may include, any other suitable parameter related to aging of the battery or battery cell.
One or more of the aging processes may have an impact on the behavior of the component 150, 110 and may also be matched with the predicted 230 behavior of the component 150, 110 being based on the predetermined component operation.
Based on the aging processes, it may also be possible to predict the remaining useful life (RUL) for the component, which may e.g. be used for scheduling of maintenance for the component and/or for the component control.
Figure 3 shows a flow chart diagram for a method 300 according to an aspect of the present invention, i.e. a method for control of a component, which aims at solving at least some of the above-mentioned problems. The method steps of figure 3 may for example be performed during normal operation of the component which is to be controlled, e.g. when the propulsion component 110 of a vehicle 100 is running and/or when the battery component 150 is used for starting an engine, for traction and/or for supplying electrical appliances with electrical energy.
In a first step 310 of the method according to the present aspect of the invention, an extended state of health (ESOH) for the component is determined as described above in connection with figure 2, e.g. by use of the above and below described first to seventh unit/means 141, 142, 143, 144, 145, 146, 147.
In a second step 320 of the method according to the aspect of the present invention, the component 150, 110 is controlled based at least on the determined extended state of health (ESOH) for the component 150, 110, e.g. by use of a below described controlling unit/means 148.
Thus, the real component 150, 110, for example the real battery 150, is hereby controlled e.g. by a component management system, based on the knowledge gained and included in the extended state of health for the component 150, 110. Especially, the component control may hereby be performed based also on the aging status/information related to the component 150, 110, which is included in the extended state of health.
Hereby, a component management system including the control unit 170, such as e.g. a battery management system, may be provided with information on the state of health for the component, including current, present and/or future aging mechanisms, which is based on physics-based electrochemical component models Mcomponent_physics. The component may, based on this information, be dynamically controlled by adjustments of one or more usage limits for the component, such that the component usage is optimized based on the current extended state of health information.
An optimized usage of the component may hereby be achieved, based on "soft", i.e. adaptable, usage limits being related to the actual aging of the component. For a battery component, the battery sizing, the safety, the utilization degree, the lifetime and/or the performance for the battery may hereby be optimized in accordance with the expectations of the customer/user .
According to various embodiments of the present invention, the extended state of health information, including the aging information, may be calculated/determined onboard an entity including the component, such as onboard a vehicle 100 including the battery component 150 and/or the propulsion component 110, or may be calculated/determined offboard an entity including the component, in an offboard entity 186. The extended state of health information may thus already be available onboard the entity, e.g. onboard the vehicle 100, or may need to be transferred to the entity, e.g. by usage of at least one external/offboard communication unit 185 and at least one internal/onboard communication unit 180. An offboard calculation/determination of the extended state of health may be advantageous since the external/offboard entity 186 may have powerful computing abilities. An onboard calculation/determination of the extended state of health may be advantageous since transfer of the information between onboard 180 and offboard 185 communication units may then be omitted.
According to various embodiments of the present invention, the control 320 of the component may be flexibly performed, and the limits/thresholds set for the control may be adjusted, e.g. may be continuously adjusted/adapted based on the determined extended state of health for the component 150, 110, and possibly also based on a duty cycle, a climate, a temperature, a state of charge, a current and/or a current history for the component 150, 110.
Also, the control 320 of the component may be based on a requested/necessary/expected component safety, such that a reliable and safe usage of the component is guaranteed.
The control 320 of the component may also be based on a requested/necessary/expected component life time, on a requested/necessary/expected requested component performance, and/or on a requested/necessary/expected balance between component life time and component performance. For example, if a customer/user is expecting to exchange a component, such as a battery, relatively often, the component may be more aggressively controlled, e.g. higher charge and/or discharge currents may be used for the battery, than if a longer component lifetime is expected.
The control 320 of the component may also be based on a requested/necessary/expected component purpose, e.g. may be optimized for best component life time, best component performance or the best balance of life time and performance, depending on customer/user preferences.
The control 320 of the component may also be based on a predicted future component usage, whereby it may be avoided that the component is drained of resources that may be needed for the predicted future usage.
The control 320 of the component may also be based on a present/current component state, e.g. a present/current battery state, such as for example a temperature, a state of charge, a current and/or a current history for the component/battery.
The control 320 of the component may also be based on external operating conditions, such as e.g. ambient temperature surrounding the component.
The control 320 of the component may also be based on a predicted remaining useful life (RUL) for the component.
The control 320 of the component may also be based on predicted remaining battery charge and/or mileage for the component, e.g. a battery.
Generally, since the aging status of the component 150, 110 is known and included in the extended state of health for the component 150, 110, component maintenance, e.g. service of the component or exchange of the component, may be scheduled well in advance such that the disturbance for the customer/user is minimized.
The control 320 of the component 150, 110, performed based on the determined extended state of health, may include a large number of operations, depending on the application and on the component being controlled. Below are a number of examples described for embodiments where the component is a battery 150 or a battery cell. Corresponding control operations may of course be made for other components than batteries or battery cells.
The control of a battery and/or a battery cell may include an adjustment of a maximum continuous battery charge current 1charge_max_contand/or an adjustment of a maximum peak battery charge current icharge_max_peak.
The control of a battery and/or a battery cell may also include an adjustment of a maximum continuous battery discharge current idischarge_max_contand/or an adjustment of a maximum peak battery discharge current idischarge_max-peak.
To adjust the charging and/or discharging currents for a battery or a battery cell may change their performance and/or lifetime. Hereby the performance and/or lifetime for the battery may be customized to the expectations of the customer/user . Also, so-called lithium plating for the battery may be mitigated/reduced or eliminated by reduction of the used charging current.
The control of a battery and/or a battery cell may also include an adjustment of a maximum battery cell voltage vmaxand/or an adjustment of a minimum battery cell voltage vmin.
The control of a battery and/or a battery cell may also include an adjustment of a minimum battery state of charge and/or an adjustment of a maximum battery state of charge. The control of a battery and/or a battery cell may, for hybrid vehicles that used charge sustaining control mechanisms, also include an adjustment of a preferred/requested battery state of charge (SOC).
By adaptively controlling the battery currents and/or voltages, and/or the state of charge limits, less attractive/advantageous state of charge areas, i.e. the used level of battery charge, may be avoided such that the condition of the battery is improved. According to an embodiment of the present invention, the state of charge limits defining the used state of charge area may be variably adapted, e.g. may be continuously adjusted.
The control of a battery and/or a battery cell may also include an adjustment of an open circuit voltage in relation to a state of charge curve used for state of charge estimation, whereby the state of charge estimation is improved.
The control of a battery and/or a battery cell may also include an adjustment of an estimated battery resistance, which may be related to a state of health for the battery and/or battery cell, and may be used for power and/or power loss prediction for the battery and/or battery cell.
The control of a battery and/or a battery cell may also include an adjustment of an estimated battery capacity, which may be related to a state of health for the battery and/or battery cell, and may be used for estimation of the state of charge for the battery and/or battery cell.
The control of a battery and/or a battery cell may also include an adjustment of a recommended set temperature Tsetof a battery climate system, an adjustment of a maximum temperature Tmaxof a battery climate system, and/or an adjustment of a minimum temperature Tminof a battery climate system. To control the battery climate, e.g. the battery temperature, may be of great help for improving the condition for the battery and/or the battery cells.
According to an embodiment of the present invention, one or more of the parameters mentioned above, such as e.g. the parameters related to charging and/or discharging currents, may be adjusted individually for single battery cells of a battery based on the extended state of health, i.e. based on their individually determined aging status, if the electrical configuration of the battery allows that.
The person skilled in the art will appreciate that a method for determining an extended state of health for a component and a method for control of a component according to the present invention may also be implemented in a computer program, which, when it is executed in a computer, instructs the computer to execute the method. The computer may be included in the herein described control units and/or may be coupled/connected to the herein described control unit. The computer program is usually constituted by a computer program product 403 stored on a non-transitory/non-volatile digital storage medium, in which the computer program is incorporated in the computer-readable medium of the computer program product. The computer-readable medium comprises a suitable memory, such as, for example: ROM (Read-Only Memory), PROM (Programmable Read-Only Memory), EPROM (Erasable PROM), Flash memory, EEPROM (Electrically Erasable PROM), a hard disk unit, etc.
Figure 4 shows in schematic representation a control unit/system/means 400/140/170. The control unit/system/means 400/140/170 comprises a computing unit 401, which may be constituted by essentially any suitable type of processor or microcomputer, for example a circuit for digital signal processing (Digital Signal Processor, DSP), or a circuit having a predetermined specific function (Application Specific Integrated Circuit, ASIC). The computing unit 401 is connected to a memory unit 402 arranged in the control unit/system/means 400/140/170, which memory unit provides the computing unit 401 with, for example, the stored program code and/or the stored data which the computing unit 401 requires to be able to perform computations. The computing unit 401 is also arranged to store partial or final results of computations in the memory unit 402.
In addition, the control unit/system/means 400/140/170 is provided with devices 411, 412, 413, 414 for receiving and transmitting input and output signals. These input and output signals may comprise waveforms, impulses, or other attributes which, by the devices 411, 413 for the reception of input signals, can be detected as information and can be converted into signals which can be processed by the computing unit 401. These signals are then made available to the computing unit 401. The devices 412, 414 for the transmission of output signals are arranged to convert signals received from the computing unit 401 in order to create output signals by, for example, modulating the signals, which can be transmitted to other parts of and/or systems within or outside the vehicle.
Each of the connections to the devices for receiving and transmitting input and output signals can be comprise one or more of a cable; a data bus, such as a CAN bus (Controller Area Network bus), a MOST bus (Media Orientated Systems Transport bus), or some other bus configuration; or by a wireless connection. A person skilled in the art will appreciate that the above-stated computer can be constituted by the computing unit 401 and that the above- stated memory may be constituted by the memory unit 402.
Control systems in modern vehicles commonly comprise communication bus systems including one or more communication buses for linking a number of electronic control units (ECU's), or controllers, and various components located on the vehicle. Such a control system may comprise a large number of control units/means and the responsibility for a specific function can be divided amongst more than one control unit/means. Vehicles of the shown type thus often comprise significantly more control units/means than are shown in figures 1 and 4, which is well known to the person skilled in the art within this technical field.
In the shown embodiment, the present invention is implemented in the control unit/system/means 400/140/170. The invention can also, however, be implemented wholly or partially in one or more other control units/systems/means already present in the vehicle, or in some control unit/system/means dedicated to the present invention.
According to an aspect of the invention, a control unit 140 arranged for determining an extended state of health (ESOH) for a component 150, 110 is presented.
The control unit 140 includes a first unit/means 141, arranged for measuring 210 data related to at least one feature of the component 150, 110, the measuring 210 encompassing at least one operation of the component 150, 110 during a time period Tmeasure.
The control unit 140 further includes a second unit/means 142, arranged for determining 220, based on a data-based component model Mcomponent_datarelated to the measured data, a virtual component 160 corresponding to the component 150, 110.
The control unit 140 also includes a third unit/means 143, arranged for predicting 230, based on a data-based component model Mcomponent_data, a behavior of the component 150, 110 for at least one predetermined component operation.
The control unit 140 also includes a fourth unit/means 144 arranged for determining 240, based on the predicted behavior of the component 150, 110, a state of health (SOH) for component 150, 110.
The control unit 140 also includes a fifth unit/means 145 arranged for predicting 250, based on a physics-based component model Mcomponent_physics, a behavior of the virtual component 160 for at least one predetermined component operation, the physics-based component model Mcomponent_physicsincluding at least one component aging process.
The control unit 140 also includes a sixth unit/means 146 arranged for determining 260, based on at least one of the predicted behavior of the virtual component 160 and one or more model parameters of said physics-based component model Mcomponent_physics, an aging status for the component 150, 110.
The control unit 140 also includes a seventh unit/means 147 arranged for determining 270 the extended state of health (ESOH) for the component 150, 110 based on the determined state of health (SOH) and the determined aging status for the component 150, 110.
As mentioned in this document, the method steps 220-270 and 310-320, and thus also the second to eight units/means 142-148, may be implemented to be executed at least partly outside/offboard the vehicle 100 in at least one external/offboard entity 186 located separately from the vehicle 100. This is schematically illustrated in figure 1, where the second to eight units/means 142-148 are schematically illustrated as being included in the offboard entity 186. The control units 140, 170 may therefore be connected to an internal communication unit 180 arranged for communication with at least one communication unit 185 external to the vehicle 100, e.g. via a wireless connection using a suitable communication protocol. The external/offboard communication unit 185 may be connected to the at least one external/offboard entity 186, such as e.g. a server, database, computer or any other data and/or information processing entity.
Of course, the control units 140, 170 and the second to eight units/means 141-148 may be implemented both onboard and offboard the vehicle, such that some units/means are arranged onboard and some are arranged offboard. For example, the second to sixth units/means 142-146 perform a relatively large number of computations, and may therefore according to an embodiment be advantageous to implement offboard 186 the vehicle.
If any of the second to eighth units/means 142-148 are arranged offboard 186, then the data/information needed for the offboard units/means to be able to perform their tasks and/or method steps should be transferred/transmitted offboard by the use of the internal 180 and external 185 communication means. Also, the results from the offboard arranged units/means are then transferred/transmitted via the use of the internal 180 and external 185 communication means to the onboard control units/systems 140, 170 such that the onboard component control may be performed.
The first measuring method step 210 is usually performed onboard the vehicle 101. Thus, the first units/means 141 is usually included in the vehicle 101.
By activation of the above described first to seventh 141-147 unit/means, the determination of the extended state of health for a component is executed, which has the above-mentioned advantages. This may also be described as the control unit 140 being configured/arranged to perform the in this document described first to seventh method steps 210-270 of the method 200 according to the present invention.
According to an aspect of the invention, a control unit 170 arranged for controlling a component 150, 110 is presented.
The control unit includes the first to seventh means 141-147 described above arranged for determination of the extended state of health for the component 150, 110.
The control unit further includes eight means 148 arranged for controlling 320 the component 150, 110 based on the determined extended state of health for the component 150, 110.
By activation of the above described first to eighth 141-148 unit/means, the control of the component based on the extended state of health is executed, which has the above-mentioned advantages. This may also be described as the control unit 170 being configured/arranged to perform the in this document described first 310 and second 320 steps of the controlling method 300 according to the present invention, including the first to seventh method steps 210-270 of the extended state of health determining method 200.
Here and in this document, units/means are often described as being arranged for performing steps of the method according to the invention. This also includes that the units/means are designed to and/or configured to perform these method steps.
The at least one control units 140, 170 are in figure 1 illustrated as including separately illustrated units/means/devices 141, 142, 143, 144, 145, 146, 147, 148. Also, the control units 140, 170 may include or be coupled to e.g. a battery component 150 and/or a propulsion component 110. These means/units/devices 141, 142, 143, 144, 145, 146, 147, 148, 140, 170 may, however, be at least to some extent logically separated but implemented in the same physical unit/device. These means/units/devices 141, 142, 143, 144, 145, 146, 147, 148, 140, 170 may also be part of a single logic unit which is implemented in at least two different physical units/devices. These means/units/devices 141, 142, 143, 144, 145, 146, 147, 148, 140, 170 may also be at least to some extent logically separated and implemented in at least two different physical means/units/devices. Further, these means/units/devices 141, 142, 143, 144, 145, 146, 147, 148, 140, 170 may be both logically and physically arranged together, i.e. be part of a single logic unit which is implemented in a single physical means/unit/device. These means/units/devices 141, 142, 143, 144, 145, 146, 147, 148, 140, 170 may for example correspond to groups of instructions, which can be in the form of programming code, that are input into, and are utilized by at least one processor when the units/means are active and/or are utilized for performing its method step, respectively. It should be noted that the control units 140, 170 may be implemented at least partly within the vehicle 100 and/or at least partly outside of the vehicle 100, e.g. in a server, computer, processor or the like located separately from the vehicle 100.
As mentioned above, the units 141, 142, 143, 144, 145, 146, 147, 148 described above correspond to the claimed means 141, 142, 143, 144, 145, 146, 147, 148 arranged for performing the embodiments of the present invention, and the present invention as such.
The control units 140, 170 according to the present invention can be arranged for performing all of the above, in the claims, and in the herein described embodiments method steps. The control units 140, 170 are hereby provided with the above described advantages for each respective embodiment.
A skilled person also realizes that the above described control units 140, 170 may be modified according to the different embodiments of the method of the present invention. The present invention is also related to a vehicle 100, such as a truck, a bus or a car, including the herein described control units 140, 170 for estimating an extended state of health of a component and for controlling the component, respectively.
The inventive method, and embodiments thereof, as described above, may at least in part be performed with/using/by at least one device. The inventive method, and embodiments thereof, as described above, may be performed at least in part with/using/by at least one device that is suitable and/or adapted for performing at least parts of the inventive method and/or embodiments thereof. A device that is suitable and/or adapted for performing at least parts of the inventive method and/or embodiments thereof may be one, or several, of a control unit, an electronic control unit (ECU), an electronic circuit, a computer, a computing unit and/or a processing unit.
With reference to the above, the inventive method, and embodiments thereof, as described above, may be referred to as an, at least in part, computerized method. The method being, at least in part, computerized meaning that it is performed at least in part with/using/by the at least one device that is suitable and/or adapted for performing at least parts of the inventive method and/or embodiments thereof.
With reference to the above, the inventive method, and embodiments thereof, as described above, may be referred to as an, at least in part, automated method. The method being, at least in part, automated meaning that it is performed with/using/by the at least one device that is suitable and/or adapted for performing at least parts of the inventive method and/or embodiments thereof.
The present invention is not limited to the above described embodiments. Instead, the present invention relates to, and encompasses all different embodiments being included within the scope of the independent claims.

Claims (15)

Claims
1. A method (200) for determining an extended state of health (ESOH) for a component (150, 110) ; characterized by: - measuring (210) data related to said component (150, 110) during at least one operation time period tmeasurefor said component (150, 110); - determining (220), based on a data-based component model Mcomponent_datarelated to said measured data, a virtual component (160) corresponding to said component (150, 110); - predicting (230), based on said data-based component model Mcomponent_data, a behavior of said component (150, 110) for at least one predetermined component operation; - determining (240), based on said predicted behavior of said component (150, 110), a state of health (SOH) for said component (150, 110); - predicting (250), based on a physics-based component model Mcomponent_physics, a behavior of said virtual component (160) for at least one predetermined component operation, said physicsbased component model Mcomponent_physicsincluding at least one component aging process; - determining (260), based on at least one of said predicted behavior of said virtual component (160) and one or more model parameters of said physics-based component model Mcomponent_physics, an aging status for said component (150, 110); and - determining (270) said extended state of health (ESOH) for said component (150, 110) based on said determined state of health (SOH) and said determined aging status for said component (150, 110).
2. The method (200) as claimed in claim 1, wherein said measured data is time resolved.
3. The method (200) as claimed in any one of claims 1-2, wherein said data-based component model Mcomponent_datais a machine learning model including at least one input and at least one output.
4. The method (200) as claimed in claim 3, wherein said component is a battery (150) or a battery cell, and one or more of said at least one input and said at least one output is related to at least one in the group of: - a measured current value i; - a moving average current value itdetermined based on at least two measured current values i and on a function of points in time t when said at least two current values i are measured; - a measured temperature value T; - a measured voltage value v; - a measured pressure value p; - a measured length value 1; and - a measured impedance value z.
5. The method as claimed in any one of claims 1-4, wherein said physics-based component model Mcomponent_physicsis derived based on at least one in the group of: - said data-based component model Mcomponent_data; - a component specification; and - at least one laboratory test.
6. The method as claimed in any one of claims 1-5, wherein said physics-based component model Mcomponent_physicsis determined based on: - a mathematical model describing at least one of an electrochemical, a physical, a chemical, a mechanical, an electrical, a thermodynamical, a kinetic and a thermal behavior of said component by usage of at least one equation; and - a geometry of said component 150.
7. The method as claimed in any one of claims 1-6, wherein said component is a battery (150) or a battery cell, and said at least one predetermined component operation includes at least one in the group of: - a standard performance test; - a current pulse test; - a constant current discharge test; - a constant current charge test; - galvanostatic intermittent titration technique (GITT) test; and - a current profile test.
8. The method (200) as claimed in any one of claims 1-7, wherein said component (150, 110) includes at least one in the group of: - a battery (150); - a traction battery (151); - a start battery (152); - a service battery (153); - a battery cell; - an electrical machine (102); - a fuel cell; - a supercapacitor; and - a combustion engine (101).
9. A method (300) for control of a component (150, 110); characterized by: - determining (310) an extended state of health (ESOH) for said component (150, 110) according to any one of claims 1-8; and - controlling (320) said component (150, 110) based at least on said determined extended state of health (ESOH) for said component (150, 110).
10. The method (300) as claimed in claim 9, wherein said controlling (320) of said component (150, 110) is based also on at least one in the group of: - a requested component safety; - a requested component life time; - a requested component performance; - a requested balance between component life time and component performance; - a component purpose; - a present component state; - external component operating conditions; - a predicted future component usage; - a predicted remaining useful life (RUL) for said component (150, 110); and - a predicted remaining battery charge and/or mileage for said component (150, 110).
11. The method (300) as claimed in any one of claims 9-10, wherein said component is a battery (150) or a battery cell, and said controlling (320) includes at least one in the group of: - an adjustment of a maximum continuous battery charge current icharge_max_cont; - an adjustment of a maximum peak battery charge current icharge_max_peak; - an adjustment of a maximum continuous battery discharge current idischarge_max_cont; - an adjustment of a maximum peak battery discharge current idischarge_max_peak; - an adjustment of a set temperature Tsetof a battery climate system; an adjustment of a maximum temperature Tmaxof a battery climate system; - an adjustment of a minimum temperature Tminof a battery climate system; - an adjustment of a maximum battery cell voltage vmax; - an adjustment of a minimum battery cell voltage vmin; - an adjustment of an open circuit battery voltage curve used for state of charge (SOC) estimation; - an adjustment of an estimated battery capacity used for state of charge (SOC) estimation; - an adjustment of an estimated battery resistance; - an adjustment of a minimum battery state of charge (SOC); - an adjustment of a maximum battery state of charge (SOC); and - an adjustment of a preferred battery state of charge (SOC).
12. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method according to any one of claims 1-11.
13. A computer-readable medium comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method according to any one of claims 1-11.
14. A control unit (140) arranged for determining an extended state of health (ESOH) for a component (150, 110); characterized by: - first means (141) arranged for measuring (210) data related to at least one feature of said component (150, 110), said measuring (210) encompassing at least one operation of said component (150, 110) during a time period Tmeasure; - second means (142) arranged for determining (220), based on a data-based component model Mcomponent_datarelated to said measured data, a virtual component (160) corresponding to said component (150, 110); - third means (143) arranged for predicting (230), based on a data-based component model Mcomponent_data, a behavior of said component (150, 110) for at least one predetermined component operation; - fourth means (144) arranged for determining (240), based on said predicted behavior of said component (150, 110), a state of health (SOH) for said component (150, 110); - fifth means (145) arranged for predicting (250), based on a physics-based component model Mcomponent_physics, a behavior of said virtual component (160) for at least one predetermined component operation, said physics-based component model Mcomponent_physicsincluding at least one component aging process; - sixth means (146) arranged for determining (260), based on at least one of said predicted behavior of said virtual component (160) and one or more model parameters of said physics-based component model Mcomponent_physics, an aging status for said component (150, 110); and - seventh means (147) arranged for determining (270) said extended state of health (ESOH) for said component (150, 110) based on said determined state of health (SOH) and said determined aging status for said component (150, 110).
15. A control unit (170) arranged for controlling a component (150, 110); characterized by: - means (141, 142, 143, 144, 145, 146, 147) arranged for determining (310) an extended state of health (ESOH) for said component (150, 110) according to any one of claims 1-8; and - means (148) arranged for controlling (320) said component (150, 110) based on said determined extended state of health (ESOH) of said component (150, 110).
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