CN109977468B - Verification system, method, equipment and control system of energy management strategy - Google Patents
Verification system, method, equipment and control system of energy management strategy Download PDFInfo
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Abstract
The invention is applicable to the technical field of energy management, and provides a verification system, a method, equipment and a control system of an energy management strategy, wherein load simulation equipment is mainly used for simulating load operation conditions, and can directly exchange energy according to working condition data by means of an energy exchange system constructed by power electronic components, so that the energy system is directly charged and discharged to simulate energy consumption and energy recovery during load operation, the working condition simulation effect is good, the energy conversion loss is reduced, and the verification accuracy can be well ensured; the deployment is relatively simplified, the efficiency is higher, and the cost is reduced; no mechanical parts are operated in the working condition simulation process, so that the safety is high, and mechanical vibration and noise are eliminated.
Description
Technical Field
The invention belongs to the technical field of energy management, and particularly relates to a verification system, method, equipment and control system of an energy management strategy.
Background
Along with the increasing severity of energy and environmental problems, the traditional automobile industry is undergoing an energy transformation, and various new energy automobiles, particularly hybrid electric automobiles and pure electric automobiles, gradually enter the field of vision of people. The energy storage system is an important component in the power system of the new energy automobile, and is used for providing energy for an electric drive system and other vehicle-mounted units (such as an electric air conditioner compressor and the like) and recovering braking energy when the automobile brakes. The performance of the energy storage system influences the dynamic performance and the endurance mileage of the whole vehicle to a great extent. The energy storage units forming the energy storage system are various, mainly comprise lithium batteries, nickel-hydrogen batteries, lead-acid batteries, super capacitors, flywheel energy storages and the like, and have different physicochemical properties, so that the respective energy storage characteristics are greatly different, and the energy storage units have advantages and disadvantages. In order to solve the contradiction between the power characteristics and the energy characteristics of the lithium battery, people try to organically combine two or more energy storage units in different forms, for example, combine an energy storage unit (such as an energy type lithium battery) with a power storage unit (such as a super capacitor), and match reasonable software and hardware architecture and energy management strategies, so that each energy storage unit can have advantages complementary in characteristics, and the energy storage system is called a composite energy storage system, and has high energy utilization efficiency.
In the composite energy storage system, the function of the energy management strategy is to reasonably distribute power among the energy storage units according to the working state of the automobile. The excellent energy management strategy can exert the advantages of different energy storages to the greatest extent, and the energy is efficiently utilized. Energy management strategies can be largely divided into two broad categories: rule-based energy management policies and optimization method-based energy management policies. In order to quantify the effectiveness of energy management strategies, or to compare between various energy management strategies, verification of the energy management strategy is required.
Currently, there are three main methods for verifying energy management strategies: computer software simulation, real vehicle-based testing and motor test bench-based testing. All three methods have certain limitations. For the first method for simulating computer software, the software simulation is often a software model environment obtained based on the physical environment simplification, has limitation, and the simulation result is very dependent on the modeling accuracy, because the simulation result obtained by a simple model lacks persuasion, and the more accurate and more comprehensive model is often more complex, the more difficult to solve, and the requirement on the computer performance is met. For the second real vehicle testing method, different automobile control unit (Vehicle Control Unit, VCU)/micro control unit (Micro Control Unit, MCU) control codes are required to be written for realizing different energy management strategies, the corresponding codes are required to be modified for modifying the strategies, time and labor are wasted, meanwhile, the real vehicle testing is complex, the workload is large, requirements are met for time, personnel, places and even weather, the cost is high, and certain potential safety hazards exist. For the third method based on the motor-dynamometer experiment table, a high-power motor and a dynamometer are often required to simulate the running working condition of an automobile, and sometimes a transmission device such as a reduction gearbox is also required to be matched, so that the hardware cost is high; the motor test bed needs a matched control system (such as an industrial personal computer/PLC and the like) to respectively control parameters such as the rotating speed, the torque and the like of the motor and the dynamometer according to working condition data to be simulated so as to simulate specific automobile energy consumption and braking energy recovery, and the running working condition of the automobile is complex and changeable, and has high requirements on the control system, so that the set of control system is complex; the selection of the motor and the dynamometer on the rack limits the range of the capability of simulating the running working condition of the automobile, the combination of the motor and the dynamometer with low power can not simulate the working condition with high power, the motor with high power has high cost, and the simulation effect on the working condition with low speed and low power is poor (related to factors such as the speed regulation range of the motor); the simulation process mainly involves the interconversion between electric energy and mechanical energy and electric energy, and a large energy conversion loss exists (related to factors such as efficiency of the motor); meanwhile, rotating parts such as a motor rotating shaft, a coupler and the like rotating at high speed have certain potential safety hazards and are accompanied with vibration and noise pollution; the motor test bed needs to be arranged on a stable and reliable base, and has requirements on a test field and space.
Therefore, the verification technology of the existing energy management strategy has poor working condition simulation effect and cannot obtain higher verification accuracy; the operation is complex, the energy management strategy can not be deployed flexibly and efficiently, the efficiency is low, the cost is high, and potential safety hazards can exist.
Disclosure of Invention
The invention aims to provide a verification system, a method, equipment and a control system of an energy management strategy, and aims to solve the problems of low verification precision, complex operation, low efficiency and higher cost in the prior art.
In one aspect, the present invention provides a verification system for an energy management strategy, the system comprising:
an energy system;
the load simulation equipment is configured with an energy exchange system, and the energy exchange system is used for exchanging energy with the energy system based on a configured first working condition, and the first working condition indicates: the energy exchange condition of the load simulated by the load simulation equipment when the load runs under a second working condition corresponding to the first working condition; the method comprises the steps of,
and the control system is used for managing the energy exchange according to the energy management strategy to be verified, and monitoring the energy exchange to obtain a corresponding energy management strategy verification result.
Further, the control system includes:
the upper computer is used for building the energy management strategy to be verified and configuring related interfaces; the method comprises the steps of,
and the control equipment is used for completing the deployment of the energy management strategy to be verified as a rapid control prototype RCP, and executing the management and monitoring work based on the defined interface.
Further, the energy system includes:
an energy-type energy storage system and a power-type energy storage system.
Further, the load is an electric vehicle; the energy type energy storage system is a lithium battery pack, the lithium battery pack comprises a lithium battery unit and a battery management system, the power type energy storage system is a super capacitor pack, and the super capacitor pack comprises a super capacitor unit and a capacitor management system; the lithium battery pack and the super capacitor pack are connected with the load simulation equipment through a direct current-direct current bidirectional conversion circuit and a direct current bus; the energy exchange system is composed of power electronic components; the upper computer software of the upper computer is MATLAB/Simulink, dSPACE RCP and HIL, control desk and HelpDesk; the control equipment is dsace equipment; the interface comprises one or more of the following: analog-to-digital conversion interface, pulse width modulation PWM interface, encoder interface, controller area network CAN interface and serial communication interface.
In another aspect, the present invention further provides a method for verifying an energy management policy, where the method is based on a verification system as described above, and the method includes:
the energy exchange system in the load simulation equipment exchanges energy with the energy system based on the first working condition;
and the control system manages the energy exchange according to the energy management strategy to be verified, monitors the energy exchange and obtains the verification result of the energy management strategy.
Further, when the control system includes: when the upper computer and the control equipment are used, the method further comprises the following steps:
the upper computer builds the energy management strategy to be verified and configures the interface;
a compiler in the upper computer software of the upper computer compiles the energy management strategy to be verified and the interface configuration information into a database file which can be imported by the control equipment,
the control device imports the database file.
Further, the energy management strategy to be verified is based on a fuzzy logic rule, and the upper computer builds the energy management strategy to be verified, specifically comprising:
establishing a membership function between a variable and a semantic state, wherein the variable comprises: input variables corresponding to monitoring information obtained by monitoring the energy exchange and output variables corresponding to energy distribution control information, wherein a plurality of semantic states corresponding to each variable form a fuzzy set;
based on the membership function, a fuzzy logic rule base for fuzzy reasoning is established,
the energy exchange management specifically includes:
based on real-time monitoring information and the fuzzy logic rule base, carrying out fuzzy reasoning to obtain a fuzzy reasoning result;
and obtaining real-time energy distribution control information according to the fuzzy reasoning result.
Further, the method further comprises:
converting the second working condition into the first working condition, wherein the second working condition is represented by the load operation speed-time relationship, and the first working condition is represented by the charge-discharge power-time relationship of the load simulation equipment operation;
and leading the first working condition into the load simulation equipment.
In another aspect, the present invention further provides a load simulator for energy management policy verification, configured with an energy exchange system, where the energy exchange system is configured to exchange energy with the energy system based on a configured first working condition, and the first working condition indicates: and the energy exchange condition of the load simulated by the load simulation equipment when the load runs under a second working condition corresponding to the first working condition.
In another aspect, the present invention also provides a control system for energy management policy validation, the control system comprising:
the upper computer is used for building an energy management strategy to be verified and configuring related interfaces; the method comprises the steps of,
and the control equipment is used for completing the deployment of the energy management strategy to be verified as a rapid control prototype RCP, and executing the management and monitoring work of energy exchange between the load simulation equipment and the energy system based on the defined interface.
According to the invention, the load simulation equipment is used for simulating the load operation working condition, and can directly exchange energy according to the working condition data by means of the energy exchange system constructed by the power electronic components, so that the energy system is directly charged and discharged to simulate the energy consumption and energy recovery during load operation, the working condition simulation effect is good, the energy conversion loss is reduced, and the verification accuracy can be well ensured; the deployment is relatively simplified, the efficiency is higher, and the cost is reduced; no mechanical parts are operated in the working condition simulation process, so that the safety is high, and mechanical vibration and noise are eliminated.
Drawings
FIG. 1 is a schematic diagram of a verification system of an energy management strategy according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a verification system of an energy management strategy according to a second embodiment of the present invention;
FIG. 3 is a schematic diagram of a verification system of an energy management strategy according to a third embodiment of the present invention;
FIG. 4 is a schematic view of the experimental apparatus provided by a specific application example of the present invention;
fig. 5 is a schematic diagram of a fuzzy rule table in a specific application example of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The following describes in detail the implementation of the present invention in connection with specific embodiments:
embodiment one:
fig. 1 shows the structure of a verification system of an energy management policy according to a first embodiment of the present invention, and for convenience of explanation, only the portions related to the embodiments of the present invention are shown in detail as follows:
an energy system 101;
the load simulation device 102 is configured with an energy exchange system, and the energy exchange system is configured to exchange energy with the energy system 101 based on a configured first working condition, where the first working condition indicates: the energy exchange condition of the load simulated by the load simulation device 102 when the load runs under the second working condition corresponding to the first working condition; the method comprises the steps of,
the control system 103 is configured to manage energy exchange according to an energy management policy to be verified, and monitor the energy exchange to obtain a corresponding energy management policy verification result.
In this embodiment, the energy system 101 may include an energy storage system and/or an external power grid. An energy storage system comprised in the energy system 101, an external power grid, etc., wherein the energy storage system should be controllable by the control system 103, for example: when the energy system 101 includes an energy storage system, the energy storage system may include a corresponding management system and an energy storage unit, where the management system may be controlled by the control system 103, so that the energy storage unit can perform charge and discharge operations in a controlled manner; when the energy system 101 includes an energy storage system and an external power grid, the energy storage system may be controlled by the control system 103, and the external power grid may not be controlled by the control system 103.
The energy storage system may be of a single type or may be formed by combining multiple types. For example: the energy storage system may be an energy-only energy storage system, or a power-only energy storage system, or the energy storage system may include not only an energy-type energy storage system but also a power-type energy storage system. The energy type energy storage system can be a lithium battery pack, a nickel-hydrogen battery pack, a lead-acid battery pack and the like, and the power type energy storage system can be a super capacitor pack, a flywheel energy storage device and the like.
The load simulation device 102 is mainly used for simulating loads such as electric vehicles, and the like, so as to directly exchange energy with the energy system 101 through an energy exchange system configured by the load simulation device. The energy exchange system is made up of power electronics components, such as: thyristors, power transistors (GTR), insulated gate bipolar transistors (Insulated Gate Bipolar Transistor, IGBTs), and the like. The load simulation device 102 is different from the existing computer software simulation technology, relies on an established pure software model to simulate, is also different from the existing real vehicle-based test technology, adopts a real load to test, is also different from the existing motor test bench-based test technology, and adopts an industrial personal computer/programmable logic controller (Programmable Logic Controller, PLC) and the like to control a motor and a dynamometer to simulate the real power condition of the load. The load simulation device 102 simulates the energy exchange with the energy system when the load is operating under the second operating condition through the energy exchange system. The second condition may be a specified standard test condition in which the load is operable, or a custom condition. The specified standard test conditions can beU.S. ENVIRONMENTAL PROTECTION AGENCYThe formulated urban road circulation working condition (Urban Dynamometer Driving Schedule, UDDS), european endurance test standard working condition (New European Driving Cycle, NEDC) and the like, and each working condition can be correspondingly expressed as the running speed-time relation of the load. The first working condition corresponds to the second working condition but is not the same, the second working condition can reflect the actions of the load motor and other power systems, and the first working condition only reflects: the energy exchange with the energy system when the load is operating in the second condition, the first condition may be reflected to the direct energy exchange action with the energy system 101 on the energy exchange system constructed from the power electronics. The first operating condition may be correspondingly expressed as a charge-discharge power-time relationship for operation of the load simulator. The first operating mode corresponds to the second operating mode and can be understood as: the load operation speed-time relationship described above is related to the operation of the load simulation device 102The charge-discharge power-time relationship may be mutually inverted, for example: and obtaining a corresponding charge and discharge power-time relationship from the operation speed-time relationship according to the longitudinal dynamics theory of the electric vehicle.
In the verification system, the energy management strategy to be verified is mainly to reasonably distribute power on the energy system 101 according to the working states of the energy system 101 and the load simulation equipment 102. The energy management strategy to be verified can be a rule-based energy management strategy, an energy management strategy based on an optimization method and the like, and can also be a combination of a plurality of energy management strategies.
The control system 103 may be a conventional industrial computer or PLC, or a micro control unit (Micro Controller Unit, MCU), or a computer, or a control network composed of multiple computers. On the one hand, the control system 103 may build or import the energy management policy to be verified from outside, and on the other hand, may manage the energy exchange between the load simulation device 102 and the energy system 101 according to the built or imported energy management policy to be verified, for example: the control system 103 controls the load simulation device 102 and the energy system 101 to start or stop running, and controls power distribution on each energy storage system in the energy system 101 according to the operation state monitoring information of the energy system 101 and the load simulation device 102, and on the other hand, monitors energy exchange executed by adopting the energy management policy to be verified, so as to obtain energy exchange monitoring information indicating the verification result of the energy management policy, for example: the charging and discharging current peak value of the lithium battery pack, the State of Charge (SOC) value of the super capacitor pack, the braking energy recovery efficiency, the maximum fluctuation range of the DC bus voltage and the like. The energy exchange monitoring information may directly reflect the energy management policy verification result, or may reflect the energy management policy verification result by using a comparison result of the energy exchange monitoring information and the reference information, for example: the method comprises the steps of setting ase:Sub>A charge-discharge current peak value reference value A of ase:Sub>A lithium battery pack, and reflecting an energy management strategy verification result by comparing energy exchange monitoring information B with ase:Sub>A set charge-discharge current peak value reference value (B-A)/A multiplied by 100.
According to the embodiment, the load simulation equipment provided with the energy exchange system is mainly utilized, the energy exchange system is composed of power electronic components, and when the simulation load runs under the second working condition, the energy exchange system is used for simulating direct energy exchange with the energy system, so that the working condition simulation effect is good, the energy conversion loss is reduced, and the verification accuracy can be well ensured; the deployment is relatively simplified, the efficiency is higher, and the cost is reduced; no mechanical parts are operated in the working condition simulation process, so that the safety is high, and mechanical vibration and noise are eliminated.
Embodiment two:
the present embodiment further provides, based on the first embodiment, the following:
as shown in fig. 2, in this embodiment, the control system 103 specifically includes:
the upper computer 201 is used for building an energy management strategy to be verified and configuring related interfaces; the method comprises the steps of,
the control device 202 is used as a rapid control prototype (Rapid Control Prototype, RCP) to complete the deployment of the energy management strategy to be verified and to perform management and monitoring of the energy exchange between the energy system 101 and the load simulation device 102 based on the defined interface.
In this embodiment, the host software used in the host computer 201 may be MATLAB/Simulink, dSPACE RCP and HIL, control desk, helpDesk, etc. The upper computer 201 may utilize the upper computer software to build an energy management policy to be verified, and define relevant interfaces in the control device 202, so that the control device 202 can implement interaction with the energy system 101 and the load simulation device 102 through the defined interfaces, and perform management and monitoring work of energy exchange between the energy system 101 and the load simulation device 102. The relevant interfaces may be various input-output and communication interfaces, such as: analog-to-digital (a/D, D/a) interfaces, pulse width modulation (Pulse Width Modulation, PWM) interfaces, encoder interfaces, controller area network (Controller Area Network, CAN) interfaces, serial communication interfaces (e.g., RS485 interfaces), and the like.
The energy management strategy to be verified can be built based on fuzzy logic rules, and specifically can be related to: first, a membership function between a variable and a semantic state is established, wherein the variable comprises: input variables corresponding to monitoring information obtained by monitoring energy exchange between the energy system 101 and the load simulation device 102, such as: SOC, power demand (Preq), etc., and output variables corresponding to energy allocation control information, such as: the power allocation value, and a plurality of semantic states corresponding to each variable form a fuzzy set, for example: SOC corresponds to a first semantic state L with lower charge quantity, a second semantic state M with medium charge quantity, a third semantic state H with higher charge quantity, a fuzzy set is { L, M, H }, and a membership function can be similarly established for the power requirement Preq; and secondly, based on the membership function, establishing a fuzzy logic rule base for fuzzy reasoning, wherein the fuzzy logic rule can be an if-then rule, obtaining the semantic state of a corresponding output variable according to the semantic state corresponding to the real-time monitoring information serving as the input variable, and finally obtaining real-time energy distribution control information for power distribution.
The control device 202 may be a dsace device, csace device, rapidECU device, or PROTronic device, etc. The control device 202, as an RCP, may import (or download) the built energy management policy to be verified from the host computer 201, and complete the deployment of the local energy management policy to be verified. The interface configuration information obtained by the energy management policy and the interface definition to be verified can be compiled by a compiler in the upper computer software to obtain a corresponding database file, and the database file can be understood and executed by the control device 202. The database file may be imported from the host computer 201 into the control device 202. The control device 202 may also perform management and monitoring of energy exchanges between the energy system 101 and the load simulation device 102 according to the deployed energy management policies to be verified based on the defined interfaces. The management of the energy exchange between the energy system 101 and the load simulation device 102 by the control device 202 may specifically be: based on the real-time monitoring information and the fuzzy logic rule base, fuzzy reasoning is carried out to obtain a fuzzy reasoning result; and then, according to the fuzzy reasoning result, obtaining real-time energy distribution control information and carrying out power distribution.
By implementing the embodiment, the RCP function can be used, the energy management strategy to be verified can be conveniently and flexibly deployed on the physical platform rapidly, complicated code writing, modifying and debugging work is avoided, the operation is simplified, the verification efficiency is further improved, and the cost is reduced.
Embodiment III:
the present embodiment further provides the following on the basis of the first or second embodiment:
as shown in fig. 3, in the present embodiment, the energy system 101 includes: the energy type energy storage system and the power type energy storage system, the energy type energy storage system is a lithium battery pack 301, the lithium battery pack 301 comprises a lithium battery unit and a battery management system (Battery Management System, BMS), the power type energy storage system is a super capacitor pack 302, the super capacitor pack 302 comprises a super capacitor unit and a capacitor management system (Capacitor Management System, CMS), and the lithium battery pack 301 and the super capacitor pack 302 are connected with the load simulation equipment 102 through a direct current-direct current (DC-DC) bidirectional conversion circuit 303 and a direct current bus 304. The DC-DC bi-directional conversion circuit 303 is simultaneously controlled by the control device 202.
Accordingly, in the membership function, the input variables may be the first SOC of the lithium battery pack 301, the second SOC of the supercapacitor pack 302, and the power requirement Preq of the dc bus 304. The input variables may reflect the operating states of the energy system 101 and the load simulation device 102.
In the verification system of each embodiment, each component may be implemented by a corresponding hardware or software unit, and each unit may be an independent software or hardware unit, or may be integrated into one software or hardware unit, which is not used to limit the present invention.
Embodiment four:
the implementation flow of the verification method of the energy management policy provided by the embodiment is based on the verification system of the embodiment. For convenience of explanation, only the portions related to the embodiments of the present invention are shown, and the following details are described in the verification method:
the energy exchange system in the load simulation device 102 exchanges energy with the energy system 101 based on the first operating condition.
The control system 103 manages the energy exchange according to the energy management policy to be verified, and monitors the energy exchange to obtain the verification result of the energy management policy.
In the verification method of the present embodiment, the energy system 101, the load simulation device 102, and the control system 103 have the corresponding functions in the verification system embodiment, and may execute the corresponding processing flows, which are not described herein again.
The steps of the energy system 101, the load simulation device 102, and the control system 103 are not in obvious sequence when the verification method of the present embodiment is executed.
In other embodiments implementing the verification method, the following may also be involved:
in an embodiment, when the control system 103 includes the above-mentioned host computer 201 and the control device 202, the verification method further includes: the upper computer 201 builds an energy management strategy to be verified and configures related interfaces; a compiler in the upper computer software of the upper computer 201 compiles the energy management policy to be verified and the interface configuration information into a database file which can be imported by the control device 202, and the control device 202 imports the database file.
In another embodiment, the to-be-verified energy management policy is based on fuzzy logic rules, and the process of building the to-be-verified energy management policy by the upper computer 201 may specifically include: establishing a membership function between a variable and a semantic state, wherein the variable comprises: input variables corresponding to monitoring information obtained by monitoring energy exchange and output variables corresponding to energy distribution control information, wherein a plurality of semantic states corresponding to each variable form a fuzzy set; and establishing a fuzzy logic rule base for fuzzy reasoning based on the membership function. The process of managing energy exchange may specifically include: based on the real-time monitoring information and the fuzzy logic rule base, fuzzy reasoning is carried out to obtain a fuzzy reasoning result; and obtaining real-time energy distribution control information according to the fuzzy reasoning result.
In another embodiment, the verification method may further include: converting the second working condition into a first working condition, wherein the second working condition is represented by a load operation speed-time relationship, and the first working condition is represented by a charge-discharge power-time relationship of load simulation equipment operation; and leading the first working condition into load simulation equipment.
The above description is given of the relevant parts in the above embodiment of the verification system, and these descriptions may be equally applicable to the verification method and are not repeated.
Fifth embodiment:
in an embodiment of the present invention, a computer readable storage medium is provided, where a computer program is stored, where the computer program, when executed by a processor, implements the flow in the embodiment of the verification method, for example, the flow of energy exchange, management and monitoring of energy exchange, and the like.
The computer readable storage medium of embodiments of the present invention may include any entity or device capable of carrying computer program code, recording medium, such as ROM/RAM, magnetic disk, optical disk, flash memory, and so on.
One specific application example:
the following describes the present application by way of a specific application example:
the experimental device in this application example is equivalent to the verification system, and is implemented in the verification system, the method or the apparatus, and this section focuses on the specific description of the experimental device and the experimental process equivalent to the verification method. The schematic of the experimental setup can be seen in fig. 4.
The experimental device proposed by the application example is an entity implementation of the verification method for the energy management strategy, and mainly comprises an electric load simulation device, an upper computer, dsace hardware, a No. 1 bidirectional DC/DC, a No. 2 bidirectional DC/DC, an energy type lithium battery pack (hereinafter referred to as a lithium battery pack) with a Battery Management System (BMS), and a power type super capacitor pack (hereinafter referred to as a super capacitor pack) with a Capacitance Management System (CMS). The lithium battery pack is electrically connected with a first bidirectional DC/DC low-voltage side (namely an energy storage side), the super capacitor pack is electrically connected with a second bidirectional DC/DC low-voltage side (namely an energy storage side), a first bidirectional DC/DC high-voltage side (namely a direct current bus side) is electrically connected with a direct current side of the electric load simulation system, and an alternating current side of the electric load simulation system is electrically connected with a power grid. The dsace hardware is in signal connection with the first bidirectional DC/DC, the second bidirectional DC/DC, the lithium battery pack BMS, the super capacitor pack CMS and the electric load simulation equipment. The experimental device can verify the energy distribution and energy utilization effects of various energy management strategies of the composite energy storage system (namely, the energy-covered lithium battery pack and the power super capacitor pack) under different working conditions.
The specific model of dSPACE hardware in the experimental device is Microlabbox 1302F; the two DC/DC models are bidirectional DC/DC based on a half-bridge topological structure; the lithium battery pack model is 120V60AH ternary lithium battery pack with a passive BMS; the super capacitor group is formed by connecting two Maxwell BMOD0165P048B01 modules in series, the working voltage is controlled to be 48V-90V, the total capacity is 82.5F, and the super capacitor group is provided with a CMS; the upper computer of the electric load simulation system is an X64 computer running with a Microsoft Windows operating system, and software used in experiments is filled in the upper computer, and comprises Matlab/Simulink, dSPACE ControlDesk, dSPACE RCP and HIL, dSPACE HelpDesk and electric load simulation equipment control software BTS.
According to the verification method, the experimental device is adopted to verify the energy management strategy of the composite energy storage system based on the fuzzy logic rule under the standard US06 working condition.
The first step is to establish an energy management strategy based on fuzzy logic rules in an upper computer Matlab/Simulink, and configure corresponding dSPACE real-time hardware interfaces in software according to requirements. Establishing an energy management strategy based on fuzzy logic rules comprises three steps:
1. blurring: and establishing membership functions of all the input/output variables to obtain fuzzy sets. The input quantity of the energy management strategy refers to the state of charge (BSOC) of the lithium battery pack, the state of charge (CSOC) of the super capacitor pack and the power demand (Preq) of the direct current bus, and the output quantity refers to the ratio Kbat of the output power of the lithium battery pack to the power demand of the bus. Membership functions refer to the mapping between variables within a descriptive domain and a particular semantic. For example, the input quantity-battery state of charge BSOC-with a discourse of [ BSOCmin, BSOCmax ] is divided into five semantic states: EL (extremely low charge), L (low charge), M (medium charge), H (high charge), and EH (extremely high charge), and the membership degree between BSOC and five semantic states are described by five membership functions, respectively, so as to obtain a fuzzy set { EL, L, M, H, EH } of the input quantity, wherein BSOCmin is a lower limit value of the charge of the lithium battery, and BSOCmax is an upper limit value of the charge of the lithium battery. The same procedure is used for other input/output quantities, except that the semantic state of a particular partition is distinguished from a defined membership function. The state of charge CSOC of the input-supercapacitor group with a universe of [ COSCmin, CSOCmax ] is divided into three semantic states: l (lower charge), M (medium charge), H (higher charge), the fuzzy set { L, M, H }, BSOCmin being the lower limit value of the charge of the lithium battery, and BSOCmax being the upper limit value of the charge of the lithium battery; preq with the argument [ PreqN, preqP ] is divided into seven semantic states: NH (high brake energy recovery power), NM (medium brake energy recovery power), NL (low brake energy recovery power), ZO (zero power demand), PL (low power consumption), PM (medium demand consumption), PH (high power consumption), the fuzzy set is { NH, NM, NL, ZO, PL, PM, PH }, preqN is the maximum power value at the time of brake energy recovery, the sign is negative, preqP is the maximum power demand value under the driving condition, the sign is positive; dividing the output quantity of the lithium battery pack with the argument of 0-1, which is the output power of the lithium battery pack and occupies the bus required power KBat into six semantic states: EL (small), L (small), M (medium), H (large), EH (large), the ambiguity set is { EL, L, M, H, EH }.
2. Fuzzy reasoning: and establishing a fuzzy rule base, and performing fuzzy reasoning according to the fuzzy logic rule when the control system makes a decision. The fuzzy rule is an if-then rule, and a fuzzy rule table shown in fig. 5 is established according to the working characteristics of the composite energy storage system.
3. Deblurring: and converting the result obtained by the fuzzy reasoning in the last step into control output. Here, a weighted average method is used to deblur, resulting in a specific Kbat value.
In the MATLAB/Simulink of the upper computer, fuzzy logic controller can be adopted for rapid and convenient configuration. At the same time, the input/output real-time hardware interface needs to be configured, and the interface is integrated in the ds1103 interface library. Configuring a CAN communication interface to collect BSOC, CSOC, preq three input quantities; and an RS485 serial port communication interface is configured to control the behavior state of the bidirectional DC/DC, so as to control the output power of the lithium battery pack and the super capacitor pack. The direct current bus demand power Preq, the lithium battery pack output power Pbat and the super capacitor pack output power Psup meet the following formulas:
P req ＝P bat +P sup
wherein, preq >0 indicates that the bus demand power is positive and the energy of the energy storage system is being consumed; preq <0 indicates that the bus demand power is negative and energy is being recovered by regenerative braking to the energy storage system; pbat >0 indicates that the lithium battery pack is discharging, pbat <0 indicates that the lithium battery pack is charging; psup >0 indicates that the supercapacitor bank is discharging and Psup <0 indicates that the supercapacitor bank is charging.
Compiling and downloading the energy management strategy based on the fuzzy logic rule built in the upper computer into dSPACE hardware, and connecting the configured dSPACE real-time hardware interface with a controlled object to complete the deployment of a rapid control prototype of the energy management strategy. And writing the contents of energy management strategies, interface configuration information and the like into database files (sdf) which can be understood and executed by the dSPACE hardware through a built-in compiler in the upper computer software, and then importing the database files into the dSPACE hardware. And connecting a CAN communication interface of the lithium battery pack BMS, the super capacitor pack CMS and the electric load simulation system with dSPACE to form a CAN communication network, and connecting a bidirectional DC/DC serial communication interface with dSPACE. On one hand, dsace hardware is used as an entity controller to control a controlled object, and on the other hand, the dsace hardware is used as data acquisition and recording equipment to record experimental data.
And thirdly, importing a standard test working condition file or a user-defined working condition file into the electric load simulation equipment. The test of the composite energy storage system is carried out by adopting the US06 working condition, and when the composite energy storage system is imported, one-step calculation is needed, namely, the vehicle speed-time curve is calculated according to the longitudinal dynamics related theoretical formula of the vehicle to obtain the charge-discharge power-time curve. The US06 working condition is converted, and the obtained charge-discharge power-time working condition curve is led into the electric load simulation equipment. When the electric load simulation system charges the composite energy storage system, the simulation is that the electric drive system charges the energy storage system when braking energy is recovered in a real vehicle test working condition, and the energy flow direction is a power grid-electric load simulation system-composite energy storage system; when the electric load simulation system discharges the composite energy storage system, the electric driving system simulates the discharging process performed in the energy storage system when the electric driving system drives the vehicle to run in the real vehicle test working condition, and the energy flow direction is the composite energy storage system, the electric load simulation system and the power grid.
And the fourth step is to send an operation starting instruction to each device through dSPACE in the upper computer software and record experimental data. And the electric load simulation equipment simulates the running working condition of the automobile according to the set working condition file after receiving the starting instruction. The dSPACE hardware is communicated with a lithium battery pack BMS to obtain current state of charge (BSOC) and temperature information of the battery; the dSPACE hardware is communicated with a super capacitor bank CMS to obtain the current state of charge (CSOC) of the capacitor; the dSPACE hardware is communicated with the electric load simulation equipment to obtain the current direct current bus power demand Preq, the dSPACE hardware distributes the power demand on the direct current bus according to the BSOC, the CSOC and the bus power demand Preq and the energy management strategy, the specific distribution method is that the dSPACE is communicated with the bidirectional DC/DC, and the input and output power of the lithium battery pack and the super capacitor pack is controlled by controlling the working mode of the bidirectional DC/DC. The lithium battery pack is used as an energy accumulator, and the first bidirectional DC/DC is operated in a high-voltage side constant-voltage stabilizing mode so as to stabilize the voltage of a direct-current bus; the super capacitor group is used as a power type energy accumulator, the second bidirectional DC/DC works in a high-voltage side constant-current mode, and the power requirement on the direct-current bus is extracted or supplemented. The control method can avoid control conflict when two bidirectional DC/DC works simultaneously.
The fifth step is to analyze the experimental data to verify the energy management strategy. The experimental data to be analyzed refer to the experimental data recorded in the fourth step, and mainly include: a lithium battery pack discharge current-time curve, a super capacitor pack discharge current-time curve, a battery state of charge (BSOC-time curve, a super capacitor state of charge (CSOC-time curve), a direct current bus voltage-time curve and the like. The method is mainly used for verifying the peak discharge current of the lithium battery pack, the maximum variation range of the SOC of the lithium battery pack, the maximum fluctuation range of the DC bus voltage and the like. Experimental results show that the peak charge and discharge currents of the lithium battery pack are reduced by about 70% and 50%, respectively, and the service life of the lithium battery is prolonged; meanwhile, the SOC fluctuation range of the super capacitor bank is larger, which indicates that the characteristics of the super capacitor bank are effectively played; the efficiency of braking energy recovery is improved by 10%, and the endurance mileage of the whole vehicle is improved.
And the verification of the energy management strategy of the composite energy storage system is completed by analyzing the experimental result. The experimental efficiency is improved, and the verification period is shortened.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (10)
1. A verification system for an energy management strategy, the system comprising:
an energy system;
the load simulation equipment is configured with an energy exchange system, and the energy exchange system is used for exchanging energy with the energy system based on a configured first working condition, and the first working condition indicates: the energy exchange condition of the load simulated by the load simulation equipment when the load runs under a second working condition corresponding to the first working condition; the method comprises the steps of,
the control system is used for managing the energy exchange according to the energy management strategy to be verified, and monitoring the energy exchange to obtain a corresponding energy management strategy verification result;
the first working condition is correspondingly expressed as a charge-discharge power-time relation of the operation of the load simulation equipment, wherein the first working condition corresponds to the second working condition, and the first working condition refers to: the simulated load operation speed-time relationship and the charge-discharge power-time relationship of the load simulation equipment operation can be mutually converted.
2. The authentication system of claim 1, wherein the control system comprises:
the upper computer is used for building the energy management strategy to be verified and configuring related interfaces; the method comprises the steps of,
and the control equipment is used for completing the deployment of the energy management strategy to be verified as a rapid control prototype RCP, and executing the management and monitoring work based on the defined interface.
3. The authentication system of claim 2, wherein the energy system comprises:
an energy-type energy storage system and a power-type energy storage system.
4. A validation system according to claim 3, wherein the load is an electric vehicle; the energy type energy storage system is a lithium battery pack, the lithium battery pack comprises a lithium battery unit and a battery management system, the power type energy storage system is a super capacitor pack, and the super capacitor pack comprises a super capacitor unit and a capacitor management system; the lithium battery pack and the super capacitor pack are connected with the load simulation equipment through a direct current-direct current bidirectional conversion circuit and a direct current bus; the energy exchange system is composed of power electronic components; the upper computer software of the upper computer is MATLAB/Simulink, dSPACE RCP and HIL, control desk and HelpDesk; the control equipment is dsace equipment; the interface comprises one or more of the following: analog-to-digital conversion interface, pulse width modulation PWM interface, encoder interface, controller area network CAN interface and serial communication interface.
5. A method of verification of an energy policy, characterized in that the method is based on a verification system according to any one of claims 1 to 4, the method comprising:
the energy exchange system in the load simulation equipment exchanges energy with the energy system based on the first working condition;
and the control system manages the energy exchange according to the energy management strategy to be verified, monitors the energy exchange and obtains the verification result of the energy management strategy.
6. The authentication method of claim 5, wherein when the control system comprises: when the upper computer and the control equipment are used, the method further comprises the following steps:
the upper computer builds the energy management strategy to be verified and configures the interface;
a compiler in the upper computer software of the upper computer compiles the energy management strategy to be verified and the interface configuration information into a database file which can be imported by the control equipment,
the control device imports the database file.
7. The verification method of claim 6, wherein the energy management policy to be verified is based on fuzzy logic rules, and the upper computer builds the energy management policy to be verified, specifically comprising:
establishing a membership function between a variable and a semantic state, wherein the variable comprises: input variables corresponding to monitoring information obtained by monitoring the energy exchange and output variables corresponding to energy distribution control information, wherein a plurality of semantic states corresponding to each variable form a fuzzy set;
based on the membership function, a fuzzy logic rule base for fuzzy reasoning is established,
the energy exchange management specifically includes:
based on real-time monitoring information and the fuzzy logic rule base, carrying out fuzzy reasoning to obtain a fuzzy reasoning result;
and obtaining real-time energy distribution control information according to the fuzzy reasoning result.
8. The authentication method of claim 5, wherein the method further comprises:
converting the second working condition into the first working condition, wherein the second working condition is represented by the load operation speed-time relationship, and the first working condition is represented by the charge-discharge power-time relationship of the load simulation equipment operation;
and leading the first working condition into the load simulation equipment.
9. A load simulation device for energy management policy validation, characterized by an energy exchange system configured to exchange energy with the energy system based on a configured first operating condition, the first operating condition being indicative of: the energy exchange condition of the load simulated by the load simulation equipment when the load runs under a second working condition corresponding to the first working condition;
the first working condition is correspondingly expressed as a charge-discharge power-time relation of the operation of the load simulation equipment, wherein the first working condition corresponds to the second working condition, and the first working condition refers to: the simulated load operation speed-time relationship and the charge-discharge power-time relationship of the load simulation equipment operation can be mutually converted.
10. A control system for energy management strategy verification, the control system comprising: the upper computer is used for building an energy management strategy to be verified and configuring related interfaces; the method comprises the steps of,
control device for completing the deployment of the energy management strategy to be validated as a fast control prototype RCP and for performing the management and monitoring of the energy exchange between the load simulation device and the energy system according to claim 9, based on the defined interface.
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