GB2557073A - Monitoring the health of a vehicle battery - Google Patents
Monitoring the health of a vehicle battery Download PDFInfo
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- GB2557073A GB2557073A GB1801427.4A GB201801427A GB2557073A GB 2557073 A GB2557073 A GB 2557073A GB 201801427 A GB201801427 A GB 201801427A GB 2557073 A GB2557073 A GB 2557073A
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- 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
- G01R31/005—Testing of electric installations on transport means
- G01R31/006—Testing of electric installations on transport means on road vehicles, e.g. automobiles or trucks
- G01R31/007—Testing of electric installations on transport means on road vehicles, e.g. automobiles or trucks using microprocessors or computers
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- 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
- G01R31/005—Testing of electric installations on transport means
-
- 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]
- G01R31/3644—Constructional arrangements
- G01R31/3647—Constructional arrangements for determining the ability of a battery to perform a critical function, e.g. cranking
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- 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]
- G01R31/371—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] with remote indication, e.g. on external chargers
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- Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
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- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Secondary Cells (AREA)
- Tests Of Electric Status Of Batteries (AREA)
Abstract
A method of monitoring the health of vehicle batteries comprises receiving data from monitoring circuitry mounted on a plurality of vehicles. The data is collected during at least a portion of a cranking cycle triggered by an ignition event, and is transmitted with a vehicle identifier indicating the vehicle type. The data is analysed to determine a current state of the vehicle battery. The analysis involves comparing, using pattern matching techniques, a waveform (e.g. a voltage waveform), formed from the data, with stored waveforms formed from data collected from other vehicles. The analysis may use weather or temperature forecasts in predicting battery failure, and may also involve the use of an artificial neural network.
Description
(56) Documents Cited:
US 20050182536 A1 (62) Divided from Application No
1506643.4 under section 15(9) of the Patents Act 1977 (58) Field of Search:
INT CL G01R, H01M Other: EPODOC, WPI (71) Applicant(s):
Trakm8 Limited (Incorporated in the United Kingdom)
Lydden House, Wincombe Business Park, SHAFTESBURY, Dorset, SP7 9QJ, United Kingdom (72) Inventor(s):
Matthew William Cowley Timothy Adam Cowley (74) Agent and/or Address for Service:
Script IP Limited
Turnpike House, 18 Bridge Street, FROME, Somerset, BA11 1BB, United Kingdom (54) Title of the Invention: Monitoring the health of a vehicle battery Abstract Title: Monitoring the health of vehicle batteries (57) A method of monitoring the health of vehicle batteries comprises receiving data from monitoring circuitry mounted on a plurality of vehicles. The data is collected during at least a portion of a cranking cycle triggered by an ignition event, and is transmitted with a vehicle identifier indicating the vehicle type. The data is analysed to determine a current state of the vehicle battery. The analysis involves comparing, using pattern matching techniques, a waveform (e.g. a voltage waveform), formed from the data, with stored waveforms formed from data collected from other vehicles. The analysis may use weather or temperature forecasts in predicting battery failure, and may also involve the use of an artificial neural network.
FIG. 2 second of engine crank
FIG. 1
No
MONITORING THE HEALTH OF A VEHICLE BATTERY
FIELD OF THE INVENTION
The field of the invention relates to monitoring the health of automotive batteries used for the cranking of combustion engines.
BACKGROUND
Battery faults are a common cause of motor vehicle breakdown. Automotive batteries are typically sealed lead-acid rechargebable batteries made from galvanic cells arranged in series to provide 12 Volts for cars and light commercial vehicles and up to 24 Volts for HGVs. The lead acid batteries are made from plates of lead and lead dioxide which is submerged into an electrolyte solution of sulphuric acid and water. Electricity is produced via chemical reaction.
There are several construction methods for lead-acid batteries such as valve regulated lead-acid, absorbed glass mat (AGM) or (gel cell) which are both “maintenance free” sealed batteries. A cheaper alternative (flooded cell) batteries are available which require more maintenance such as topping up and are suitable for use with simpler charging circuits found in older vehicles.
Newer battery technologies such as lithium-iron and nickel-metal-hydride are entering the automotive market with the introduction of hybrid cars, stop-start technology and electric cars. Lithium-ion batteries have a very high energy density and are very light, but they are expensive, they degrade quickly and may only last two or three years whether you use them or not and they are particularly sensitive to high temperature.
There are two main purposes for automotive batteries. Starting (cranking or shallow cycle) batteries are designed to provide a short but large burst of energy in order to start an engine. Recreational (deep cycle) style batteries are designed to provide continuous powers for long periods of time and are designed to have a greater depth of discharge. Irrespective of the type of battery (lead-acid or lithium-ion etc.) used by the vehicle manufacturer, the requirements for cranking a combustion engine of a short but large burst of energy means that these batteries will fail periodically and often without warning.
It is therefore desirable to be aware of a battery’s state of health in order to be able to predict such failures. One approach to measuring a battery’s state of health is to connect a known load across the battery terminals and measure the voltage drop. A disadvantage of this approach is that it typically requires direct access to the battery terminals and as such is only performed intermittently such that in many cases an imminent battery failure may not be detected.
An alternative approach suggested in US 2009/032230 is to provide an on-board battery state monitoring system that detects changes in the voltage output by a battery during the engine cranking phase and determines a low battery state of health where particular detected voltages are outside of threshold values. A problem with this is that the voltage output by a battery during an engine cranking phase varies in a complex manner and depends on many factors, such that determining the health of the battery by simply comparing voltages at certain points with threshold values may not provide an accurate result.
It would be desirable to be able to accurately and regularly monitor the state of health of a battery such that imminent failure may be detected.
SUMMARY
A first aspect of the present invention provides, a battery monitoring device for monitoring a health of a battery in a vehicle comprising: monitoring circuitry for monitoring signals indicative of a current output of said battery, said monitoring circuitry being operable to monitor and capture said signals during at least a portion of a cranking cycle triggered by an ignition event; transmitting circuitry operable to transmit data indicative of said monitored signals towards an analysing device that is remote from said vehicle.
The inventors of the present invention recognised not only that a good indicator of battery health is the change in battery output during a cranking cycle where the load on the battery is high and very variable, but also that were the data to be transmitted to be analysed remotely then more processing power might be available than would be the case for an on-board analyser. Furthermore, a remote analyser could collect data from many different vehicles allowing the different characteristic waveforms to be compared and analysed along with their failure rate allowing the algorithms used to be updated and an increasingly accurate prediction of potential future battery failures to be made.
Thus, a way of monitoring the health of a battery is provided that uses a device that is mounted on the vehicle allowing it to monitor and capture variations in a battery output during the cranking cycle. This data is then transmitted to a remote analyser for analysis. In this regard a remote analyser is one that is not mounted on the vehicle but is in a location away from the vehicle such that it may receive data from many different vehicles.
In some embodiments, said battery monitoring device further comprises: an interface configured to connect to a diagnostic interface on said vehicle and to receive said signals indicative of said current output of said battery from said interface.
The monitoring device may be configured to connect with an on-board diagnostic interface that is available on modern vehicles and provides access to various signals regarding the status of a vehicle’s systems, including signals indicative of the current battery output. In this way a monitoring device can receive and analyse signals from any vehicle having such an interface without the need to adapt the vehicle or provide professional fitting of the monitoring device. Relevant information can be captured simply by mounting a monitoring device on this socket.
In some embodiments, the interface comprises an on-board diagnostic socket.
Many modern vehicles comprise an on-board diagnostic or OBD socket, such as an OBD-II diagnostic connector of a J1962 OBD connector, which may be used when servicing the vehicle to determine information regarding the vehicle’s current status but can also be used when the vehicle is in use to monitor signals from the engine including signals indicative of the output of the battery. If this information is collected during the cranking cycle, then this is a good indication of the state of health of the battery.
In some embodiments, said transmitting circuitry is operable to transmit data via a wireless communication network to said remote analysing device.
Wireless communication networks cover large areas of the country and transmitting circuitry operable to transmit data via these wireless communication networks are inexpensive and reliable. Thus, the use of such a wireless communication network along with suitable transmitting circuitry is an inexpensive and efficient way of transmitting the collected data to a remote analysing device, where it may be analysed.
In this regard, the wireless transmitter may comprise a SIM-card, a GSM modem, a WiFi® modem or a Bluetooth® communication device. It may transmit the data directly via the wireless communication network to the remote analyser or it may transmit it to an intermediate wireless transmitting device which may transmit it further to the analyser. In any case, the remote analysing device is remote from the vehicle in that it is not mounted on or in the vehicle.
In some embodiments, the battery monitoring device further comprises a receiver operable to receive data regarding the health of said battery from said remote analysing device.
Although the remote analysing device may simply analyse the data remotely and transmit the results to the user via some communication means not mounted on the vehicle such as a web portal or to his smart phone, in some embodiments information is transmitted back to the vehicle itself such that warning circuitry associated with the vehicle can alert the user to potential problems with the battery.
In some embodiments, said monitoring circuitry is operable to monitor changes in a voltage level output by said battery with time prior to and during said at least a portion of said cranking cycle.
As noted previously, the load on the battery during the cranking cycle is a heavy one and thus, variations in the output of the battery during loading are an indication of its state of health. Information such as the voltage level output by the battery prior to the cranking cycle and during at least a quarter of the cranking cycle is particularly helpful when diagnosing the health of a battery.
In some embodiments, the monitoring circuitry is further operable to determine at least one of an air intake temperature at a time of said cranking cycle and a vehicle identifier, said transmitter being operable to output said at least one of said air intake temperature and said vehicle identifier.
The output of a battery will vary with temperature, batteries functioning better where the temperature is not too cold. Thus, an indication of the temperature at the air intake of the vehicle which may be available from an on-board diagnostic socket for example, provides ambient temperature data and can be used in the interpretation of the results such that variations in the output of the battery that are temperature dependent can be compensated for in the results analysis. Furthermore, a vehicle identifier identifying the type of vehicle may be useful as different vehicles will have different loads on the battery during their cranking cycles and thus, it may be useful to compare data from similar vehicles. Furthermore, if the identifier identifies a particular vehicle, then an age of the battery may also be available along with data for its previous cranking cycles such that deteriorations can be detected.
In some embodiments, said battery monitoring device further comprises an accelerometer operable to detect movement of a vehicle due to a person entering a vehicle; a portion of said monitoring circuitry monitoring said battery being operable to switch on in response to said detection of said person, and in response to detecting a fall in an average output signal of said battery of more than a predetermined amount to commence monitoring and capturing said signals for a predetermined time such that an output of said battery is monitored during said at least a portion of said cranking cycle.
In order to avoid the monitoring circuitry consuming too much power and monitoring for signals from the batteries when the vehicle is not in use, it maybe convenient to have some means of switching the monitoring device on when the car is about to be used. In this regard, as it is the cranking cycle at the ignition of the engine that is to be monitored, then detection of a person entering the vehicle is a good indicator that this may be about to happen and thus, in some cases, something that detects this is useful to automatically turn the monitoring circuitry on. The collection of the data may be made from the moment that the output of the battery level falls indicating that a load is being taken from it and continued for a predetermined time period.
In some embodiments, said monitoring circuitry is configured to monitor a plurality of cranking cycles of said vehicle.
In order to monitor the health of the battery, the monitoring cycle needs to be carried out a number of times. It could be carried out every cranking cycle or it could be that the battery is monitored periodically. In some cases, it may be convenient to monitor the first cranking cycle of every day as at this point the vehicle will not have been used for a while and there will be no surface charge and as such, this is the cranking cycle that generally puts the most load on the vehicle and also the one that is consistent such that it can be compared with other cycles taken from the same time of day. In this regard, where there is some surface charge left and this varies, then this will affect the load on the battery.
In some embodiments, said device is configured to determine when an engine of said vehicle is running and when it is off, and to monitor cranking cycles that occur where said engine has been off for more than a predetermined time prior to said cranking cycle and not to monitor cranking cycles where said engine has been on during said predetermined time.
As noted above, where the monitoring device monitors the battery periodically, then if it is desirable to monitor a cranking cycle where there is no charge on the alternator, then in some cases, rather than doing it based on time of day it may do it based on detection that the engine has not been used for a predetermined time.
A second aspect of the present invention provides a method of monitoring a health of a battery in a vehicle comprising: monitoring signals indicative of a current output of said battery during at least a portion of a cranking cycle triggered by an ignition event; transmitting data indicative of said monitored signals towards an analysing device that is remote from said vehicle.
A third aspect of the present invention provides a method of determining a current battery state of batteries mounted on a plurality of vehicles, said method comprising: receiving data from monitoring circuitry mounted on said plurality of vehicles, said data being indicative of an output of said battery on said vehicle during at least a portion of a cranking cycle triggered by an ignition event on said vehicle; for data received from each of said vehicles, analysing said data to determine a current state of said battery on said vehicle; and outputting a result of said analysing step.
The invention also provides a remote analysing device which receives and analyses data from many vehicles. The use of a remote analysing device to analyse data from a number of vehicles allows accurate analysis of complex waveforms to be performed using high performance processing circuitry that would be difficult to provide on a vehicle. Furthermore, as data from a number of vehicles is collected the analysis and prediction algorithms used can be continually updated and improved as more data from different vehicles is received.
In some embodiments, the method further comprises periodically receiving further data from said monitoring circuity mounted on said vehicle indicative of said output of said battery during a further cranking cycle and determining changes in said state of said battery from said further data.
The remote analysing device may periodically receive data from the monitoring circuitry and it can compare changes in the state of the battery from this data and this will allow it to recognise deteriorations in the health of the battery.
In some embodiments, said method comprises storing at least some of said received data and said analysing step comprises a learning algorithm which analyses said received data and performs a statistical assessment of a battery’s health in dependence upon said received data and previously received data from at least a subset of said plurality of vehicles.
One advantage of using a remote analyser is that data from a number of vehicles can be collected and also the processing power of this remote analyser may be high. Thus, it can compare the data from a number of vehicles and use learning algorithms to update its analysing algorithms and thus better predict any future failure of batteries.
In some embodiments, said received data comprises a waveform indicative of changes in an output of said battery during said at least a portion of said cranking cycle and said analysing step comprises performing pattern matching of said waveform with stored waveforms to determine said current state of said battery.
Although a variety of different analysing methods may be performed, one accurate way of analysing the waveform indicative of the output of the battery during a portion of the cranking cycle is to compare it, perhaps using pattern matching techniques, with stored waveforms collected from other vehicles where the health of the battery is now known. This enables the current health of the battery to be accurately determined.
In some embodiments, the method further comprises updating said stored waveforms in dependence upon at least some of said received waveforms.
In addition to analysing the data, the data may also be used to update the stored data and to improve the models. For example, as batteries fail the waveforms captured prior to the failure may be stored as indicative of an imminent failure.
In some embodiments, the method further comprises receiving data indicative of at least one of a type and age of said vehicle, said comparing step comparing waveforms from vehicles of at least one of a similar age and type.
As data can be collected from many vehicles, then if the type and age of the vehicle is collected this information can be used when comparing waveforms, such that waveforms from some similar vehicles can be compared with each other increasing the accuracy of the results.
In some embodiments, said indicative data comprises a vehicle identifier, said method comprising a further step of accessing a database of vehicles and vehicle identifiers and determining said at least one of a type and age of said vehicle from said database.
The age and make of the vehicle may be determined from a vehicle identifier by accessing a database of vehicles and vehicle identifiers. A vehicle identifier may be an efficient way of communicating to the load analysing device sufficient information for it to identify the type and age of the vehicle.
In some embodiments, said waveform data is classified depending on a time of year and said step of comparing is performed for waveforms from a same time of year.
As noted previously, the ambient temperature affects the load on the battery. Thus, it maybe advantageous if the waveform data is classified depending on a time of year as a certain waveform may not indicate imminent failure of a battery in the summer, but may do so for a battery in the winter where the load is higher and the ability of the battery to deliver power is reduced. Thus, classifying the waveform data according to the time of year can increase the accuracy of the predictions.
In some embodiments, said current state of said battery comprises a prediction of future battery failure.
As noted previously, the method is a method of determining a current state of the battery. This in itself may be a prediction of future battery failure and although it is the current state of the battery that is derived from the information, this may be used simply as a prediction of future battery failure.
In some embodiments, the method comprises accessing a weather forecast database and determining at least one of a temperature at a time of monitoring of said received data and a predicted temperature for an upcoming period and using said at least one temperature in said prediction of future battery failure.
As noted previously, the temperature that a cranking cycle’s data is collected at affects the results and thus, knowledge of that temperature can be useful to determine the actual load on the battery. In this regard, it may be useful if the analysing method accesses a weather forecast database and determines the temperature at the time of monitoring of the received data and also a predicted temperature for an upcoming period, as if there is to be a cold spell, then the battery will need to be in better health than if this were not the case and thus, this could be helpful when predicting battery failure.
In some embodiments, said analysing step further comprises determining a state of further components of said vehicle in dependence upon said received data.
In addition to determining the state of the battery, the data received may also be indicative of the state of health of other components used in the cranking cycle such as the starter motor, the lubricants or the alternator. Thus, the data may be used to determine the health of these components. In this regard, as the analysing device may have high processing power and may analyse complex waveforms, certain variations in the waveform may be characteristic of a starter motor or characteristic of lubricants or alternators and thus, these portions of the cranking cycle can be used to identify potential problems with these components.
In some embodiments, said received data further comprises at least one of an output of said battery at rest prior to said ignition cycle, and a temperature of air intake of said vehicle at or close to a time of said cranking cycle.
In some embodiments, said outputting step comprises transmitting via a wireless communication network to a destination.
Having analysed the data then the results of this analysis maybe output via a wireless communication network. This could be to the user of the vehicle either to a device on the vehicle itself such as a warning indicator or perhaps to a web portal or to the mobile phone of the user. Alternatively or additionally it may be output to an organisation such as a breakdown organisation, such that this organisation is aware of where there maybe problems in vehicles under its care.
In some embodiments, said destination is dependent upon said vehicle said data was received from.
The destination of the data output may be dependent upon the vehicle that the data was received from, in that some vehicles may have warning indicators within them and in this case the data is sent back to the vehicle and the user is warned. Alternatively, the user may subscribe to some web portal service in which case the data from their vehicle will be transmitted to that web portal, or the vehicle may be under the care of a breakdown service and the breakdown people may be collecting the data.
A fourth aspect of the present invention provides a computer program which when executed by a computer is operable to control the computer to perform the method according to a first or second aspect of the present invention.
A fifth aspect of the present invention provides an analysing device for determining a current battery state of batteries mounted on a plurality of vehicles, said analysing device comprising: an input operable to receive data from monitoring circuitry mounted on said plurality of vehicles, said data being indicative of an output of said battery on said vehicle during at least a portion of a cranking cycle triggered by an ignition event on said vehicle; an analyser operable to analyse data received from each of said vehicles to determine a current state of said battery on said vehicle; and an output operable to output a result of said analysing step.
Further particular and preferred aspects are set out in the accompanying independent and dependent claims. Features of the dependent claims may be combined with features of the independent claims as appropriate, and in combinations other than those explicitly set out in the claims.
Where an apparatus feature is described as being operable to provide a function, it will be appreciated that this includes an apparatus feature which provides that function or which is adapted or configured to provide that function.
BRIEF DESCRIPTION OF THE DRAWINGS
Embodiments of the present invention will now be described further, with reference to the accompanying drawings, in which:
Figure l shows an example of the voltage output from a battery during a cranking cycle; Figure 2 shows a block diagram indicating schematically the monitoring device and the analysing device according to an embodiment;
Figure 3 shows an example of the device as an OBD connecting device;
Figure 4 shows a flow diagram illustrating steps performed at a monitoring device according to an embodiment; and
Figure 5 shows a flow diagram illustrating steps performed at a remote analyser according to an embodiment.
Embodiments of the present invention make use of the fact that the electrical signature of the output of the battery during a cranking cycle of a combustion engine is indicative of the health of the battery irrespective of the type of battery used within the vehicle. Thus, this data may be used to accurately determine the state of health of a battery.
In this regard, the cranking signature will vary between vehicle makes, models, age of vehicle as well as temperature and how well maintained the vehicle is. Therefore, a “big data” approach may be used to accommodate a large number of vehicle types and environmental conditions and allow the data to be analysed in a complex manner and to provide a good predictor of the battery’s health. Other factors such as non battery related faults will affect the cranking signature and may be detected by analysing this electrical signature as well.
Thus, a system is provided that can measure the output of the battery during a cranking cycle and can transmit it, perhaps using wireless communication technology, to a remote analyser which can collect data from a number of vehicles and from other databases and analyse the waveforms and use learning algorithms to update them and provide predictions of battery failure.
Figure 1 shows an example of a battery output during a cranking cycle. The graph shows a measured voltage waveform from a 12 Volt lead acid battery under load during the cranking of the vehicle. The vehicle engine strokes can be observed as a voltage oscillation of the load on the vehicle during cranking which is sinusoidal. As the frequency of this oscillation increases the battery voltage recovers as the load on the battery decreases and the engine starts eventually, leading to the vehicle alternator providing a charge on the battery shown when the voltage jumps above 12 Volts. This waveform is known as a cranking signature and in this particular example it is taken from a Kia Picante 2004 which is a small hatchback with a one litre engine.
The raw sampled voltage could be processed on-board using a microprocessor; however for better analysis, embodiments use big data calculations off-board at a remote server host and use these to measure the battery health and predict battery failure. This allows not only an increase in processing power but also it allows the collection of data from many vehicles which can be used to update and improve predictions.
Figure 2 shows a block diagram schematically showing the monitoring device and remote analysing system. A car battery that is fitted in a vehicle has its output measured by a monitoring device 10. The monitoring device 10 comprises an analogue voltage scaling circuit and an analogue to digital converting circuit which converts the output to a digital signal that is then input to a microprocessor and a network interface device such as a modem or other wireless communication transport device for sending the raw captured data from the vehicle to a host analysing server 20.
When the microprocessor detects an ignition crank which may be done by detecting the initial fall in voltage shown in Figure 1, it samples the voltage at a high frequency for a short period of time for example, at 300Hz for 30 seconds, while the engine is being cranked. In alternative embodiments it may sample at other perhaps high frequencies of up to 1 KHz. The raw sample voltage data is transmitted to the server where battery health is measured.
The health of a battery under load during cranking is not a simple calculation; different vehicle models have different cranking signatures and cranking signatures vary between vehicles and change depending on the temperature and to a lesser extent the age of the vehicle.
Thus, the server host uses mathematical algorithms for analysing the cranking signature, such as learning algorithm which extracts a wide range of features which are interpreted by a trained artificial neural network (ANN), in some cases a cascade clarifier is used with a Kolmogorov-Smirnov test to discriminate between outcomes. Other mathematical algorithms can be used within the classification to create a state of health battery forecast; the outcome of this is measured over time to create a statistical assessment of the battery’s health.
The vehicle’s make/model and therefore the engine power train is an important factor in understanding the cranking signature. The algorithm learns through guided learning against known outcome data or uses self training. The algorithm is time adaptive and elastic to cater for new vehicle models. There are several possible algorithm approaches within the ANN field which may be employed.
The algorithm provides a statistical probability (prognosis) of the state of health of the battery over time to predict the likelihood of when the battery may fail in the future.
For example, a message such as your battery has a 30% probability of failing within the next three months may be the outcome of the analysis. The forecast may use weather forecast data such as current ambient temperature observations taken either from a vehicle sensor or from the CAN bus or from third party providers such as the UK meteorological office. Meteorological forecast data can be used by the algorithm to adjust the short time predicted battery prognosis.
In some embodiments, the device can be plugged directly into the J1962 (OBD) vehicle diagnostic connector as shown in Figure 3. This has the advantage of allowing post manufacture fitting of such devices, a simple and inexpensive process. In other embodiments, it maybe installed into the vehicle connected into the vehicle’s electrics.
Figure 4 shows a flow diagram schematically illustrating steps of a method performed at a vehicle for monitoring a battery state of health. In this embodiment, the monitoring circuitry is activated by determining that a person enters the vehicle perhaps from an accelerometer detector mounted on the vehicle which detects movement of the vehicle caused by the person entering. When this is detected, the battery monitoring circuitry is automatically switched on. In this embodiment the battery is only monitored when the vehicle has not been used for a while, thus prior to monitoring the battery it is determined whether or not the vehicle has been used recently. This maybe detected from an engine temperature compared to an air intake temperature or it may be detected from other data available to the monitoring circuitry. If it is detected that the vehicle has been used recently then the monitoring circuitry is switched off. If it has not been used for a predetermined time, then there will be no surface charge on the alternator and the cranking load on the battery which will be at its highest and thus, monitoring of the battery during the cranking cycle is performed.
If it is determined that monitoring should occur, then on detection of a fall in the battery output voltage indicating the cranking cycle has started, the monitoring circuitry starts collecting the output voltage data and continues to collect it during a predetermined time. In this embodiment it samples the data at a frequency of several hundred Hertz. The collected data will then be output wirelessly to a remote analyser.
It should be noted that although in this embodiment the data is output wirelessly, in some embodiments it might be output in a different manner such as by using a memory stick or by downloading it via a wire to a computer. However, the wireless output of the data allows the data to be continually transmitted to the remote analyser and avoids or at least reduces periods during which the battery is not monitored.
Once the predetermined time period has passed and the collected data has been output, then the monitoring circuitry is switched off until a person is detected entering the car again.
Figure 5 shows steps performed at the analysing device according to an embodiment. The analysing device receives data from a vehicle and in this embodiment, data regarding current and future weather conditions. This allows it to determine the ambient temperature experienced by the vehicle at the time the data was collected. In other embodiments rather than receiving this information from a database it may receive the information with the data received from the vehicle.
The next step performed will be to compare the received data with data that is collected and stored from similar vehicles at similar temperatures. In this regard, the analyser has a large database of data collected from different vehicles at different temperatures and it stores the data along with this information such that relevant data may be compared. The comparison of the data may be by some pattern matching technique that looks at the waveform received and compares it with stored waveforms in some cases including those received from this vehicle such that deteriorations can be detected. At some point the received data may also be stored adding to or perhaps replacing some of the previously stored data such that the database is continually improved. It should be understood that the step of updating the stored data maybe performed at any point during the analysis or indeed in some cases the data may be discarded rather than stored.
The state of health of the battery is determined by using the compared waveforms and data associated with them that may indicate when a battery with that waveform later failed. Predicted future weather conditions may also be used in the analysis as this will affect when a battery fails. If, for example, a cold spell is forecast, then a battery is more likely to fail than if it is to be warm and thus, a battery with a relatively poor state of health may not have a predicted failure where the weather conditions are good, while it may do if weather conditions are predicted to become cold. If a battery failure is predicted, then a battery fault prediction is output. This may be output to a web portal which the user can access or it may be output back to the vehicle where it may trigger a warning within the vehicle, or it may be output to some database that a user or breakdown organisation can access.
Although illustrative embodiments of the invention have been disclosed in detail herein, with reference to the accompanying drawings, it is understood that the invention is not limited to the precise embodiment and that various changes and modifications can be effected therein by one skilled in the art without departing from the scope of the invention as defined by the appended claims and their equivalents.
Various aspects are set out in the following numbered paragraphs:
1. A battery monitoring device for monitoring a health of a battery in a vehicle comprising:
monitoring circuitry for monitoring signals indicative of a current output of said battery, said monitoring circuitry being operable to monitor and capture said signals during at least a portion of a cranking cycle triggered by an ignition event;
transmitting circuitry operable to transmit data indicative of said monitored signals towards an analysing device that is remote from said vehicle.
2. A battery monitoring device according to paragraph l, said battery monitoring device further comprising:
an interface configured to connect to a diagnostic interface on said vehicle and to receive said signals indicative of said current output of said battery from said interface.
3. A battery monitoring device according to paragraph 2, wherein said diagnostic interface comprises an on-board diagnostic socket.
4. A battery monitoring device according to any preceding numbered paragraph, wherein said transmitting circuitry is operable to transmit data via a wireless communication network to said remote analysing device.
5. A battery monitoring device according to any preceding numbered paragraph, further comprising a receiver operable to receive data regarding health of said battery from said remote analysing device.
6. A battery monitoring device according to any preceding numbered paragraph, wherein said monitoring circuitry is operable to monitor changes in a voltage level output by said battery with time prior to and during said at least a portion of said cranking cycle.
7. A battery monitoring device according to any preceding numbered paragraph, said monitoring circuitry being further operable to determine at least one of an air intake temperature at a time of said cranking cycle and a vehicle identifier, said transmitter being operable to output said at least one of said air intake temperature and said vehicle identifier.
8. A battery monitoring device according to any preceding numbered paragraph, said battery monitoring device further comprising an accelerometer operable to detect movement of a vehicle due to a person entering a vehicle;
said monitoring circuitry being operable to switch on in response to said detection of said person, and in response to detecting a fall in an average output signal of said battery of more than a predetermined amount to commence monitoring and capturing said signals for a predetermined time such that an output of said battery is monitored during said at least a portion of said cranking cycle.
9. A battery monitoring device according to any preceding numbered paragraph, said monitoring circuitry being configured to monitor a plurality of cranking cycles of said vehicle.
10. A battery monitoring device according to paragraph 9, said device being configured to determine when an engine of said vehicle is running and when it is off, and to monitor cranking cycles that occur where said engine has been off for more than a predetermined time prior to said cranking cycle and not to monitor cranking cycles where said engine has been on during said predetermined time.
11. A method of monitoring a health of a battery in a vehicle comprising: monitoring signals indicative of a current output of said battery during at least a portion of a cranking cycle triggered by an ignition event;
transmitting data indicative of said monitored signals towards an analysing device that is remote from said vehicle.
12. A method of determining a current battery state of batteries mounted on a plurality of vehicles, said method comprising:
receiving data from monitoring circuitry mounted on said plurality of vehicles, said data being indicative of an output of said battery on said vehicle during at least a portion of a cranking cycle triggered by an ignition event on said vehicle;
for data received from each of said vehicles, analysing said data to determine a current state of said battery on said vehicle; and outputting a result of said analysing step.
13. A method according to paragraph 12, further comprising periodically receiving further data from said monitoring circuity mounted on said vehicle indicative of said output of said battery during a further cranking cycle and determining changes in said state of said battery from said further data.
14. A method according to paragraph 13, wherein said method comprises storing at least some of said received data and said analysing step comprises a learning algorithm which analyses said received data and performs a statistical assessment of a battery’s health in dependence upon said received data and previously received data from at least a subset of said plurality of vehicles.
15. A method according to any one of paragraphs 12 to 14, wherein said received data comprises a waveform indicative of changes in an output of said battery during said at least a portion of said cranking cycle and said analysing step comprises performing pattern matching of said waveform with stored waveforms to determine said current state of said battery.
16. A method according to paragraph 15, further comprising updating said stored waveforms in dependence upon at least some of said received waveforms.
17. A method according to paragraph 15 or 16, further comprising receiving data indicative of at least one of a type and age of said vehicle, said comparing step comparing waveforms from vehicles of at least one of a similar age and type.
18. A method according to paragraph 17, wherein said indicative data comprises a vehicle identifier, said method comprising a further step of accessing a database of vehicles and vehicle identifiers and determining said at least one of a type and age of said vehicle from said database.
19. A method according to any one of paragraphs 15 to 18, wherein said waveform data is classified depending on a time of year and said step of comparing is performed for waveforms from a same time of year.
20. A method according to any one of paragraphs 12 to 19, wherein said current state of said battery comprises a prediction of future battery failure.
21. A method according to paragraph 20, comprising accessing a weather forecast database and determining at least one of a temperature at a time of monitoring of said received data and a predicted temperature for an upcoming period and using said at least one temperature in said prediction of future battery failure.
22. A method according to any one of paragraphs 12 to 21, wherein said analysing step further comprises determining a state of further components of said vehicle in dependence upon said received data.
The further components may be the starter motor, lubricants or alternator.
23. A method according to any one of paragraphs 12 to 22, wherein said received data further comprises at least one of an output of said battery at rest prior to said ignition cycle, and a temperature of air intake of said vehicle at or close to a time of said cranking cycle.
24. A method according to any one of paragraphs 12 to 23, wherein said outputting step comprises transmitting via a wireless communication network to a destination, (could be breakdown people, webportal, vehicle received from or to user of vehicle).
25. A method according to paragraph 24, wherein said destination is dependent upon said vehicle said data was received from.
26. A computer program operable when executed by a computer to control said computer to perform steps in a method according to any one of paragraphs 11 to 25.
27. An analysing device for determining a current battery state of batteries mounted on a plurality of vehicles, said analysing device comprising:
an input operable to receive data from monitoring circuitry mounted on said plurality of vehicles, said data being indicative of an output of said battery on said vehicle during at least a portion of a cranking cycle triggered by an ignition event on said vehicle;
an analyser operable to analyse data received from each of said vehicles to determine a current state of said battery on said vehicle; and an output operable to output a result of said analysing step.
Claims (14)
1. A method of determining a current battery state of batteries mounted on a plurality of vehicles, said method comprising:
receiving data from monitoring circuitry mounted on said plurality of vehicles, said data being indicative of an output of said battery during at least a portion of a cranking cycle triggered by an ignition event on said vehicle and including a vehicle identifier indicating a type of said vehicle;
for data received from each of said vehicles, analysing said data to determine a current state of said battery on said vehicle;
wherein said received data comprises data indicative of changes in an output of said battery during said at least a portion of said cranking cycle and said analysing step comprises comparing using pattern matching techniques a waveform formed from said data with stored waveforms formed from data collected from other vehicles to determine said state of said battery; and outputting a result of said analysing step.
2. A method according to claim l, further comprising periodically receiving further data from said monitoring circuity mounted on said vehicle indicative of said output of said battery during a further cranking cycle and determining changes in said state of said battery from said further data.
3. A method according to claim 2, wherein said method comprises storing at least some of said received data and said analysing step comprises a learning algorithm which analyses said received data and performs a statistical assessment of a battery’s health in dependence upon said received data and previously received data from at least a subset of said plurality of vehicles.
4. A method according to any preceding claim, further comprising updating said stored waveforms in dependence upon at least some of said received waveforms.
5. A method according to any preceding claim,, said method comprising a further step of accessing a database of vehicles and vehicle identifiers and determining said type of said vehicle from said database.
6. A method according to any preceding claim, wherein said waveform data is classified depending on a time of year and said step of comparing is performed for waveforms classified together for a same time of year.
7. A method according to any preceding claim, wherein said current state of said battery comprises a prediction of future battery failure.
8. A method according to claim 7, comprising accessing a weather forecast database and determining at least one of a temperature at a time of monitoring of said received data and a predicted temperature for an upcoming period and using said at least one temperature in said prediction of future battery failure.
9. A method according to any preceding claim, wherein said analysing step further comprises determining a state of further components of said vehicle in dependence upon said received data.
10. A method according to any preceding claim, wherein said received data further comprises at least one of an output of said battery at rest prior to said ignition cycle, and a temperature of air intake of said vehicle at or close to a time of said cranking cycle.
11. A method according to any one preceding claim, wherein said outputting step comprises transmitting via a wireless communication network to a destination.
12. A method according to claim 11, wherein said destination is dependent upon said vehicle said data was received from.
13. A computer program operable when executed by a computer to control said computer to perform steps in a method according to any preceding claim.
14. An analysing device for determining a current battery state of batteries mounted on a plurality of vehicles, said analysing device comprising:
an input operable to receive data from monitoring circuitry mounted on said plurality of vehicles, said data being indicative of an output of said battery during at least a portion of a cranking cycle triggered by an ignition event on a vehicle and including a vehicle identifier indicating a type of said vehicle;
an analyser operable to analyse data received from each of said vehicles to determine a current state of said battery on said vehicle wherein said analyser is operable to compare waveforms formed from said data using pattern matching techniques with stored waveforms formed from data collected from other vehicles to
5 determine said state of said battery; and an output operable to output a result of said analysing step.
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US11653127B2 (en) | 2020-06-10 | 2023-05-16 | Bridgestone Mobility Solutions B.V. | Monitoring voltage measurements for a vehicle battery |
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CN107122594B (en) * | 2017-04-10 | 2020-06-26 | 湖南中车时代电动汽车股份有限公司 | New energy vehicle battery health prediction method and system |
EP4216050A1 (en) | 2017-10-03 | 2023-07-26 | Google LLC | Actionable event determination based on vehicle diagnostic data |
NL2019831B1 (en) * | 2017-10-30 | 2019-05-08 | Anwb B V | Method and apparatus for indicating a state of health of a battery |
FR3118188B1 (en) * | 2020-12-18 | 2023-01-20 | Electricite De France | Plug-in device for determining the state of health of an electric vehicle battery. |
WO2022129794A1 (en) * | 2020-12-18 | 2022-06-23 | Electricite De France | Method and device for determining the state of health of a battery of an electric vehicle |
CN113219358A (en) * | 2021-04-29 | 2021-08-06 | 东软睿驰汽车技术(沈阳)有限公司 | Battery pack health state calculation method and system and electronic equipment |
US20240169767A1 (en) * | 2022-11-22 | 2024-05-23 | Robert Bosch Gmbh | Vehicle component health detection |
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US20050182536A1 (en) * | 2004-02-18 | 2005-08-18 | Doyle Marquis D. | Methods and apparatus for determining battery characteristics in a vehicle |
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US7705602B2 (en) * | 1997-11-03 | 2010-04-27 | Midtronics, Inc. | Automotive vehicle electrical system diagnostic device |
US8212527B2 (en) * | 2008-07-29 | 2012-07-03 | GM Global Technology Operations LLC | Method and apparatus for telematics-based vehicle no-start prognosis |
US8560165B2 (en) * | 2012-01-17 | 2013-10-15 | GM Global Technology Operations LLC | Co-operative on-board and off-board component and system diagnosis and prognosis |
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US20050182536A1 (en) * | 2004-02-18 | 2005-08-18 | Doyle Marquis D. | Methods and apparatus for determining battery characteristics in a vehicle |
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US11653127B2 (en) | 2020-06-10 | 2023-05-16 | Bridgestone Mobility Solutions B.V. | Monitoring voltage measurements for a vehicle battery |
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GB201801427D0 (en) | 2018-03-14 |
GB2557073B (en) | 2020-02-19 |
GB2537612A (en) | 2016-10-26 |
GB201506643D0 (en) | 2015-06-03 |
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