CN115320385B - Thermal runaway early warning method, device, equipment and storage medium for vehicle battery - Google Patents
Thermal runaway early warning method, device, equipment and storage medium for vehicle battery Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
- B60L3/0023—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train
- B60L3/0046—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train relating to electric energy storage systems, e.g. batteries or capacitors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
- B60L58/24—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries for controlling the temperature of batteries
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Abstract
The application relates to a thermal runaway early warning method, a device, equipment and a storage medium of a vehicle battery, wherein the early warning method comprises the following steps: acquiring the temperature of a vehicle battery in a sampling time period; acquiring the weight of the temperature according to the temperature, and acquiring an entropy value according to the weight; acquiring an entropy weight according to the entropy value; acquiring a first evaluation parameter according to the weight and the entropy weight; judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, and if so, judging that the vehicle battery has thermal runaway risk. According to the application, the first evaluation parameter is set through the single parameter of the obtained temperature data, so that the change trend of the temperature is obtained, and further, whether the thermal runaway risk exists in the vehicle battery is accurately evaluated, and the accuracy and the sensitivity of the thermal runaway early warning on the vehicle battery can be ensured while the energy consumption is reduced.
Description
Technical Field
The application relates to the technical field of thermal runaway early warning, in particular to a thermal runaway early warning method, device, equipment and storage medium of a vehicle battery.
Background
New energy electric vehicles are commonly used to power vehicle batteries for powering power devices of the new energy electric vehicles. In the use process of the vehicle battery, the vehicle battery has the risk of thermal runaway, and the thermal runaway of the vehicle battery has the characteristics of rapidness, intensity and difficult control, so the early warning of the thermal runaway of the battery is particularly important.
The existing runaway early warning scheme of the vehicle battery usually obtains a plurality of data such as voltage, current and temperature of the battery, processes and presets an early warning model according to the obtained data, and analyzes according to the early warning model, so that the aim of carrying out thermal runaway early warning on the vehicle battery is fulfilled.
However, when the vehicle battery actually generates thermal runaway, the voltage, current or temperature change is difficult to accurately acquire, and the sensitivity of the thermal runaway early warning is not high; and the data of voltage, current and temperature are monitored for a long time, which also causes an increase in energy consumption.
Disclosure of Invention
Based on the above, the application provides a thermal runaway early warning method, device, equipment and storage medium for a vehicle battery, so as to solve the problems of low sensitivity and high energy consumption in the prior art of carrying out thermal runaway early warning on the vehicle battery.
In a first aspect, the present application provides a thermal runaway warning method of a vehicle battery, the thermal runaway warning method including:
Acquiring the temperature of a vehicle battery in a sampling time period, wherein the temperature is acquired at m temperature acquisition points on the vehicle battery, and each temperature acquisition point respectively acquires the temperature at n sampling moments in the sampling time period;
Obtaining weights of m x n temperatures according to the m x n temperatures, and obtaining n entropy values according to the m x n weights, wherein the m x n weights are weights occupied by the temperatures of the temperature acquisition points in the temperatures of the m temperature acquisition points at each sampling moment, and the n entropy values are entropy values of the m temperature acquisition points at each sampling moment;
Acquiring n entropy weights according to n entropy values, wherein the n entropy weights are entropy weights occupied by each entropy value in the n entropy values;
obtaining m first evaluation parameters according to m x n weights and n entropy weights, wherein the m first evaluation parameters are first evaluation parameters of each temperature acquisition point in the sampling time period;
Judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, and if so, judging that the vehicle battery has thermal runaway risk.
In one embodiment, when the temperature of the vehicle battery in the sampling period is obtained, m is an even number, and every two temperature acquisition points are correspondingly arranged on one battery module of the vehicle battery;
When m first evaluation parameters are obtained according to m x n weights and n entropy weights, m/2 second evaluation parameters are obtained according to m first evaluation parameters, and m/2 second evaluation parameters are second evaluation parameters of each battery module in the sampling duration;
Judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, if so, judging that the vehicle battery has thermal runaway risk, and replacing the thermal runaway risk with:
And judging whether each battery module has abnormal temperature according to the variation trend of the second evaluation parameter of each battery module, and if so, judging that the vehicle battery has thermal runaway risk.
In one embodiment, obtaining weights of the m×n temperatures according to the m×n temperatures, and obtaining n entropy values according to the m×n weights includes:
Establishing a temperature matrix according to the temperature:
Wherein t ij represents the temperature of the ith temperature probe at the sampling time represented by the j moment;
converting the temperature matrix into a weight matrix of the temperature by adopting a data normalization method:
wherein p ij represents the weight of the temperature of the ith temperature probe in the temperatures of m temperature probes at the sampling time represented by the moment j;
obtaining n entropy values according to m x n weight matrixes, wherein the mathematical expression is as follows:
Wherein e j represents entropy values at the sampling time represented by m temperature probes j, 0≤ej≤1。
In one embodiment, the mathematical expression for obtaining n entropy weights from n of the entropy values is:
Wherein W j represents entropy weights of entropy values of m temperature acquisition points at the sampling time points represented by the j time points in entropy values of n sampling time points.
In one embodiment, the mathematical expression for obtaining m first evaluation parameters according to the weights of m×n temperatures and n entropy weights is as follows:
Wherein S i represents a first evaluation parameter of the ith temperature probe within the sampling period.
In one embodiment, the mathematical expression of obtaining the second evaluation parameters of the m/2 battery modules according to the m first evaluation parameters is as follows:
Mi/2＝|Si-Si-1|
Wherein i=2, 4,6,8 …, M i/2 represents the second evaluation parameter of the i/2 th battery module within the sampling period.
In one embodiment, acquiring a temperature of a vehicle battery over a sampling period includes:
Acquiring a state of charge signal, wherein the state of charge signal comprises one of: the vehicle battery is not charged completely, and the vehicle battery is charged completely;
And when the vehicle battery is in the state of completing charging, acquiring the temperature of the vehicle battery in the sampling time period.
In a second aspect, the present application provides a thermal runaway warning device of a vehicle battery, the thermal runaway warning device including:
an acquisition module configured to:
Acquiring the temperature of a vehicle battery in a sampling time period, wherein the temperature is acquired at m temperature acquisition points on the vehicle battery, and each temperature acquisition point respectively acquires the temperature at n sampling moments in the sampling time period;
a processing module configured to:
Obtaining weights of m x n temperatures according to the m x n temperatures, and obtaining n entropy values according to the m x n weights, wherein the m x n weights are weights occupied by the temperatures of the temperature acquisition points in the temperatures of the m temperature acquisition points at each sampling moment, and the n entropy values are entropy values of the m temperature acquisition points at each sampling moment;
Acquiring n entropy weights according to n entropy values, wherein the n entropy weights are entropy weights occupied by each entropy value in the n entropy values;
Obtaining m first evaluation parameters according to m x n weights and n entropy weights, wherein the m first evaluation parameters are first evaluation parameters of each temperature acquisition point in the sampling time period;
Judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, and if so, judging that the vehicle battery has thermal runaway risk.
In a third aspect, the present application provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any one of the thermal runaway warning methods of a vehicle battery provided by the present application when executing the computer program.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of any one of the thermal runaway warning methods of a vehicle battery provided by the present application.
According to the application, the first evaluation parameter is set through the single parameter of the obtained temperature data, so that the change trend of the temperature is obtained, and further, whether the thermal runaway risk exists in the vehicle battery is accurately evaluated, and the accuracy and the sensitivity of the thermal runaway early warning on the vehicle battery can be ensured while the energy consumption is reduced.
Drawings
FIG. 1 is a flowchart of a thermal runaway warning method for a vehicle battery according to an embodiment of the application;
fig. 2 is a flowchart of step S200 in a thermal runaway warning method for a vehicle battery according to an embodiment of the application;
fig. 3 is a flowchart of step S500 in a thermal runaway warning method for a vehicle battery according to an embodiment of the application;
fig. 4 is a flowchart of step S100 in a thermal runaway warning method for a vehicle battery according to an embodiment of the application
Fig. 5 is a flowchart of a thermal runaway warning method for a vehicle battery according to a second embodiment of the present application;
Fig. 6 is a flowchart of step S500 in a thermal runaway warning method for a vehicle battery according to a second embodiment of the application.
Detailed Description
The present application 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 application 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 application.
It should be noted that the illustrations provided in the present embodiment are merely schematic illustrations of the basic idea of the present invention.
The structures, proportions, sizes, etc. shown in the drawings attached hereto are for illustration purposes only and should not be construed as limiting the invention to the extent that it can be practiced, since modifications, changes in the proportions, or otherwise, used in the practice of the invention, are particularly adapted to the specific details of construction and the use of the invention, without departing from the spirit or essential characteristics thereof, which fall within the scope of the invention as defined by the appended claims.
References in this specification to orientations or positional relationships as "upper", "lower", "left", "right", "intermediate", "longitudinal", "transverse", "horizontal", "inner", "outer", "radial", "circumferential", etc., are based on the orientation or positional relationships shown in the drawings, are also for convenience of description only, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore are not to be construed as limiting the invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Example 1
As shown in fig. 1, a first embodiment of the present application provides a thermal runaway warning method for a vehicle battery, the thermal runaway warning method including the following steps:
s100, acquiring the temperature of a vehicle battery in a sampling time period, wherein the temperature is acquired at m temperature acquisition points on the vehicle battery, and each temperature acquisition point acquires the temperature at n sampling moments in the sampling time period;
s200, obtaining weights of m x n temperatures according to the m x n temperatures, and obtaining n entropy values according to the m x n weights, wherein the m x n weights are weights occupied by the temperatures of the temperature acquisition points in the temperatures of the m temperature acquisition points at each sampling moment, and the n entropy values are entropy values of the m temperature acquisition points at each sampling moment;
S300, acquiring n entropy weights according to n entropy values, wherein the n entropy weights are entropy weights occupied by each entropy value in the n entropy values;
s400, obtaining m first evaluation parameters according to m x n weights and n entropy weights, wherein the m first evaluation parameters are first evaluation parameters of each temperature acquisition point in the sampling duration;
S500, judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, and if so, judging that the vehicle battery has thermal runaway risk.
In step S100, it is exemplarily illustrated that m temperature acquisition points are preset on the vehicle battery to acquire the temperature of the vehicle battery at the temperature acquisition points. The sampling duration may be preset to a fixed value, or may be set according to a user instruction, and the former is described as an example in this embodiment; in the present embodiment, the sampling period is set to 1h. The sampling instants are time nodes within a sampling duration, and the n sampling instants may be evenly distributed within the sampling duration.
As shown in fig. 2, in step S200, it is exemplarily illustrated that weights of m×n temperatures are obtained according to m×n temperatures, and n entropy values are obtained according to m×n weights, that is, step S200 specifically includes the following steps:
s201, establishing a temperature matrix according to m x n temperatures:
Wherein t ij represents the temperature of the ith temperature probe at the sampling time represented by the j moment;
s202, converting the temperature matrix into a weight matrix of the temperature by adopting a data normalization method:
wherein p ij represents the weight of the temperature of the ith temperature probe in the temperatures of m temperature probes at the sampling time represented by the moment j;
s203, acquiring n entropy values according to the weight matrix, wherein the mathematical expression is as follows:
Wherein e j represents entropy values at the sampling time represented by m temperature probes j, 0≤ej≤1。
In more detail, in step S202, it is exemplarily illustrated that the mathematical expression for obtaining weights of m×n temperatures from m×n temperatures is:
According to the mathematical expression, when obtaining m×n temperatures, weights of the m×n temperatures can be obtained correspondingly.
As shown in fig. 1, in step S300, it is exemplarily illustrated that the mathematical expression for obtaining n entropy weights from n entropy values is:
Wherein W j represents entropy weights of entropy values of m temperature acquisition points at the sampling time points represented by the j time points in entropy values of n sampling time points.
In step S400, it is exemplarily illustrated that the mathematical expression for obtaining m first evaluation parameters from the weights of m×n temperatures and n entropy weights is:
Wherein S i represents a first evaluation parameter of the ith temperature probe within the sampling period.
As shown in fig. 3, in step S500, it is exemplarily illustrated that, according to the trend of the variation of the first evaluation parameter of each of the temperature acquisition points, it is determined whether there is a temperature abnormality at each of the temperature acquisition points, that is, step S500 specifically includes the following steps:
S501, obtaining m first change curves, wherein the m first change curves are change curves of first evaluation parameters of each temperature acquisition point;
S502, acquiring whether the slopes of the line segments where the two adjacent points are located on the m first change curves exceed a first slope threshold value, if so, judging that the temperature acquisition points corresponding to the first change curves are abnormal, and the vehicle battery is at risk of thermal runaway.
It can be appreciated that compared with the current first thermal runaway warning method: the method comprises the steps of obtaining various parameters such as voltage, current and temperature, and observing the variation trend of the various parameters such as voltage, current and temperature to perform thermal runaway early warning; the application only obtains the single parameter of temperature, thus achieving the purpose of more energy saving.
Compared with the current second thermal runaway early warning method: the method comprises the steps of obtaining single parameters such as voltage, current or temperature and observing the variation trend of the single parameters to perform thermal runaway early warning; according to the application, the first evaluation parameter is set by the obtained temperature data so as to obtain the change trend of the temperature, so that whether the thermal runaway risk exists in the vehicle battery can be accurately evaluated, and the accuracy and the sensitivity of the thermal runaway early warning on the vehicle battery can be ensured.
In conclusion, the application can ensure the low accuracy and sensitivity of the thermal runaway early warning of the vehicle-mounted battery and reduce the energy consumption required by the thermal runaway early warning.
As shown in fig. 4, more specifically, the temperature of the vehicle battery is acquired for the sampling period, that is, step S100 specifically includes the steps of:
S101, acquiring a charge state signal, wherein the charge state signal comprises one of the following components: the vehicle battery is not charged completely, and the vehicle battery is charged completely;
s102, when the vehicle battery is in the state of being charged, acquiring the temperature of the vehicle battery in the sampling time period.
In step S101, it is exemplarily illustrated that, when the battery is charged to a preset target state of charge or to a full state of charge, a signal that the vehicle battery is charged is obtained; and when the current state of charge of the vehicle battery does not reach the target state of charge or reaches the full charge state, obtaining a signal that the vehicle battery is not charged completely. The target state of charge may be set according to actual needs of a user of the vehicle, for example, the target state of charge is set to 99%, 95%, or 90% of the full charge state.
In step S102, it is exemplarily illustrated that temperatures of m temperature acquisition points on the vehicle battery are acquired during a sampling period (1 h in this embodiment) after the vehicle battery is charged, and the acquired temperatures are analyzed to determine whether there is a risk of thermal runaway of the vehicle battery.
It can be understood that if there is a potential risk of thermal runaway in the vehicle battery, the vehicle battery is prone to be abnormal in temperature after the charging is completed, so that the thermal runaway early warning is performed after the charging of the vehicle battery is completed, and the accuracy and the sensitivity of the early warning can be further improved.
More specifically, the energy of the thermal runaway warning of the vehicle battery can come from a power supply unit, such as a charging pile electrically connected with the vehicle battery when the vehicle battery is charged, or a household power grid electrically connected with the vehicle battery, so that the situation that the state of charge of the vehicle battery is reduced when the thermal runaway warning is performed on the vehicle battery can be avoided, and the dynamic property of the vehicle battery can be ensured.
Example two
As shown in fig. 5, a second embodiment of the present application provides a thermal runaway warning method for a vehicle battery, where the difference between the second embodiment and the first embodiment is at least that:
When the temperature of the vehicle battery in the sampling time period is obtained, m is an even number, and every two temperature acquisition points are correspondingly arranged on one battery module of the vehicle battery;
When m first evaluation parameters are obtained according to m x n weights and n entropy weights, m/2 second evaluation parameters are obtained according to m first evaluation parameters, and m/2 second evaluation parameters are second evaluation parameters of each battery module in the sampling duration;
Judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, if so, judging that the vehicle battery has thermal runaway risk, and replacing the thermal runaway risk with:
And judging whether each battery module has abnormal temperature according to the variation trend of the second evaluation parameter of each battery module, and if so, judging that the vehicle battery has thermal runaway risk.
In step S100, it is exemplarily illustrated that when the temperature acquisition points are set on the vehicle battery, two temperature acquisition points are correspondingly set on each battery module of the vehicle battery, and since the present embodiment is provided with m temperature acquisition points, the vehicle battery includes m/2 battery modules when m is a positive even number.
In step S400, it is exemplarily illustrated that the second evaluation parameter of each battery module is obtained according to the first evaluation parameters of the 2 temperature acquisition points corresponding to each battery module, and since there are m/2 battery modules in this embodiment, there are m/2 second evaluation parameters corresponding to this embodiment.
More specifically, the mathematical expression of obtaining the second evaluation parameters of m/2 of the battery modules according to the m first evaluation parameters is as follows:
Mi/2＝|Si-Si-1|
Wherein i=2, 4,6,8 …, M i/2 represents the second evaluation parameter of the i/2 th battery module within the sampling period.
I represents an i-th temperature acquisition point, and it is understood that the i-th and i-1-th temperature acquisition points are both disposed on the i/2 th battery module.
As shown in fig. 6, in step S500, it is exemplarily illustrated that the replaced step S500 specifically includes the following steps:
S503, obtaining m/2 second change curves, wherein the m/2 first change curves are change curves of second evaluation parameters of each battery module;
S504, acquiring whether the slope of a line segment where two adjacent points are located on m/2 second change curves exceeds a second slope threshold, if so, judging that the battery module corresponding to the second change curves has abnormal temperature, and the vehicle battery has thermal runaway risk.
It can be understood that by setting the second evaluation parameter of each battery module of the vehicle battery, when it is determined that the vehicle battery has a thermal runaway risk, it can be specifically determined which battery module of the vehicle battery has a thermal runaway risk, so as to take countermeasures for the vehicle battery in a targeted manner, for example, cool down the battery module having a thermal runaway risk, and so on, so as to further improve the function of performing thermal runaway early warning on the vehicle battery.
It is also understood that, since the second evaluation parameter is obtained based on the absolute value of the difference between the two first evaluation parameters, the determination of whether the battery module is at risk of thermal runaway by the second evaluation parameter has higher accuracy and sensitivity.
Example III
The third embodiment of the application provides a thermal runaway early-warning device of a vehicle battery, which is characterized by comprising;
an acquisition module configured to:
Acquiring the temperature of a vehicle battery in a sampling time period, wherein the temperature is acquired at m temperature acquisition points on the vehicle battery, and each temperature acquisition point respectively acquires the temperature at n sampling moments in the sampling time period;
a processing module configured to:
Obtaining weights of m x n temperatures according to the m x n temperatures, and obtaining n entropy values according to the m x n weights, wherein the m x n weights are weights occupied by the temperatures of the temperature acquisition points in the temperatures of the m temperature acquisition points at each sampling moment, and the n entropy values are entropy values of the m temperature acquisition points at each sampling moment;
Acquiring n entropy weights according to n entropy values, wherein the n entropy weights are entropy weights occupied by each entropy value in the n entropy values;
obtaining m first evaluation parameters according to m x n weights and n entropy weights, wherein the m first evaluation parameters are first evaluation parameters of each temperature acquisition point in the sampling time period;
Judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, and if so, judging that the vehicle battery has thermal runaway risk.
Example IV
The fourth embodiment of the application provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of any one of the thermal runaway early warning methods of the vehicle battery.
Example five
A fifth embodiment of the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of any one of the thermal runaway warning methods of a vehicle battery provided by the present application.
The above embodiments may be arbitrarily combined, and all possible combinations of the features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. A thermal runaway warning method of a vehicle battery, characterized by comprising:
Acquiring the temperature of a vehicle battery in a sampling time period, wherein the temperature is acquired at m temperature acquisition points on the vehicle battery, and each temperature acquisition point respectively acquires the temperature at n sampling moments in the sampling time period;
Obtaining weights of m x n temperatures according to the m x n temperatures, and obtaining n entropy values according to the m x n weights, wherein the m x n weights are weights occupied by the temperatures of the temperature acquisition points in the temperatures of the m temperature acquisition points at each sampling moment, and the n entropy values are entropy values of the m temperature acquisition points at each sampling moment;
Acquiring n entropy weights according to n entropy values, wherein the n entropy weights are entropy weights occupied by each entropy value in the n entropy values;
Obtaining m first evaluation parameters according to m x n weights and n entropy weights, wherein the m first evaluation parameters are first evaluation parameters of each temperature acquisition point in the sampling time period;
Judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, and if so, judging that the vehicle battery has thermal runaway risk.
2. The thermal runaway warning method of a vehicle battery according to claim 1, wherein when the temperature of the vehicle battery in a sampling period is acquired, m is an even number, and every two temperature acquisition points are correspondingly arranged on one battery module of the vehicle battery;
When m first evaluation parameters are obtained according to m x n weights and n entropy weights, m/2 second evaluation parameters are obtained according to m first evaluation parameters, and m/2 second evaluation parameters are second evaluation parameters of each battery module in the sampling duration;
Judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, if so, judging that the vehicle battery has thermal runaway risk, and replacing the thermal runaway risk with:
And judging whether each battery module has abnormal temperature according to the variation trend of the second evaluation parameter of each battery module, and if so, judging that the vehicle battery has thermal runaway risk.
3. The thermal runaway warning method of a vehicle battery according to claim 2, wherein obtaining weights of m x n of the temperatures from m x n of the temperatures, and obtaining n entropy values from m x n of the weights, comprises:
Establishing a temperature matrix according to m x n temperatures:
Wherein t ij represents the temperature of the ith temperature probe at the sampling time represented by the j moment;
converting the temperature matrix into a weight matrix of the temperature by adopting a data normalization method:
wherein p ij represents the weight of the temperature of the ith temperature probe in the temperatures of m temperature probes at the sampling time represented by the moment j;
obtaining n entropy values according to the weight matrix, wherein the mathematical expression is as follows:
Wherein e j represents entropy values at the sampling time represented by m temperature probes j,
4. The thermal runaway warning method of a vehicle battery according to claim 3, wherein the mathematical expression of obtaining n entropy weights from n entropy values is:
Wherein W j represents entropy weights of entropy values of m temperature acquisition points at the sampling time points represented by the j time points in entropy values of n sampling time points.
5. The method for thermal runaway warning of a vehicle battery according to claim 4, wherein the mathematical expression for obtaining m first evaluation parameters from the weights of m×n temperatures and n entropy weights is:
Wherein S i represents a first evaluation parameter of the ith temperature probe within the sampling period.
6. The thermal runaway warning method of a vehicle battery according to claim 5, wherein obtaining a mathematical expression of second evaluation parameters of m/2 of the battery modules from m of the first evaluation parameters is:
Mi/2＝|Si-Si-1|
Wherein i=2, 4,6, 8..m i/2 represents the second evaluation parameter of the i/2 th battery module in the sampling period.
7. The thermal runaway warning method of a vehicle battery according to claim 1, wherein acquiring the temperature of the vehicle battery for a sampling period of time includes:
Acquiring a state of charge signal, wherein the state of charge signal comprises one of: the vehicle battery is not charged completely, and the vehicle battery is charged completely;
And when the vehicle battery is in the state of completing charging, acquiring the temperature of the vehicle battery in the sampling time period.
8. A thermal runaway warning device of a vehicle battery, characterized by comprising:
an acquisition module configured to:
Acquiring the temperature of a vehicle battery in a sampling time period, wherein the temperature is acquired at m temperature acquisition points on the vehicle battery, and each temperature acquisition point respectively acquires the temperature at n sampling moments in the sampling time period;
a processing module configured to:
Obtaining weights of m x n temperatures according to the m x n temperatures, and obtaining n entropy values according to the m x n weights, wherein the m x n weights are weights occupied by the temperatures of the temperature acquisition points in the temperatures of the m temperature acquisition points at each sampling moment, and the n entropy values are entropy values of the m temperature acquisition points at each sampling moment;
Acquiring n entropy weights according to n entropy values, wherein the n entropy weights are entropy weights occupied by each entropy value in the n entropy values;
Obtaining m first evaluation parameters according to m x n weights and n entropy weights, wherein the m first evaluation parameters are first evaluation parameters of each temperature acquisition point in the sampling time period;
Judging whether each temperature acquisition point has abnormal temperature according to the change trend of the first evaluation parameter of each temperature acquisition point, and if so, judging that the vehicle battery has thermal runaway risk.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the thermal runaway warning method of a vehicle battery according to any one of claims 1 to 7 when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the thermal runaway warning method of a vehicle battery according to any one of claims 1 to 7.
Priority Applications (1)
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