CN117420464A - Electric automobile battery pack evaluation method and system - Google Patents
Electric automobile battery pack evaluation method and system Download PDFInfo
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- CN117420464A CN117420464A CN202311582759.0A CN202311582759A CN117420464A CN 117420464 A CN117420464 A CN 117420464A CN 202311582759 A CN202311582759 A CN 202311582759A CN 117420464 A CN117420464 A CN 117420464A
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- 238000011156 evaluation Methods 0.000 title claims abstract description 25
- 238000000034 method Methods 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000010276 construction Methods 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
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Classifications
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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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
- G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
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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]
- G01R31/3644—Constructional arrangements
- G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/389—Measuring internal impedance, internal conductance or related variables
-
- 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]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
Abstract
The invention discloses an evaluation method and system for a battery pack of an electric automobile, wherein the battery capacity, the battery self-discharge rate, the battery voltage consistency, the battery temperature consistency and the battery internal resistance consistency are scored according to the basic information of the battery pack of the electric automobile, so that the battery pack of the electric automobile can be accurately and effectively evaluated, and meanwhile, the evaluation accuracy of the battery pack of the electric automobile can be further improved by inputting a scoring result into a preset prediction model to predict the service life of the battery.
Description
Technical Field
The invention relates to the technical field of battery pack evaluation, in particular to an electric automobile battery pack evaluation method and system.
Background
The electric automobile is a vehicle which uses a vehicle-mounted power supply as power and uses a motor to drive wheels to run, meets various requirements of road traffic and safety regulations, and has the characteristics of energy conservation, environmental protection, simple structure, convenient maintenance and the like compared with the traditional automobile, so that the electric automobile is more and more favored by people. The power battery is used as one of important parts in the electric automobile, and the accurate determination of the performance of the power battery has important significance on the overall performance of the whole electric automobile.
Disclosure of Invention
In view of the above, the present invention provides a method and a system for evaluating a battery pack of an electric vehicle, which can evaluate the battery pack of the electric vehicle.
The technical scheme of the invention is realized as follows:
the method for evaluating the battery pack of the electric automobile specifically comprises the following steps:
acquiring basic information of a battery pack of the electric automobile;
grading battery parameters according to basic information of the battery pack of the electric automobile to obtain battery parameter grading results, wherein the battery parameter grading results comprise a battery capacity grading result, a battery self-discharge rate grading result, a battery voltage consistency grading result, a battery temperature consistency grading result and a battery internal resistance consistency grading result;
and inputting the grading result of the battery parameters into a preset prediction model to predict the service life of the battery, thereby realizing the evaluation of the battery pack of the electric automobile.
As a further alternative of the method for evaluating a battery pack of an electric vehicle, the obtaining of the battery capacity scoring result specifically includes:
acquiring capacity historical data and charging frequency historical data of the electric automobile battery pack;
establishing a capacity prediction model of the electric vehicle battery pack based on capacity historical data and charging frequency historical data by using a gray prediction algorithm;
inputting historical data of the current charging times of the electric automobile battery pack into a capacity prediction model to obtain the current capacity of the electric automobile battery pack;
and scoring according to the current capacity and the original capacity to obtain a battery capacity scoring result.
As a further alternative of the method for evaluating a battery pack of an electric vehicle, the obtaining of the battery self-discharge rate scoring result specifically includes:
acquiring self-discharge rate historical data of the electric automobile battery pack;
fitting the self-discharge rate historical data to obtain a self-discharge rate fitting coefficient of the electric vehicle battery pack;
predicting according to the fitting coefficient and the discharge times of the electric automobile battery pack to obtain the current self-discharge rate of the electric automobile battery pack;
and scoring according to the current self-discharge rate of the battery and the self-discharge rate of the original battery to obtain a scoring result of the self-discharge rate of the battery.
As a further alternative of the electric vehicle battery pack evaluation method, the obtaining of the battery voltage consistency scoring result specifically includes:
acquiring voltage history data of each battery in the electric automobile battery pack;
generating a voltage state sequence of each battery according to the voltage history data of each battery;
and scoring the battery voltage consistency according to the voltage state sequence of each battery to obtain a battery voltage consistency scoring result.
As a further alternative of the method for evaluating a battery pack of an electric vehicle, the obtaining of the battery temperature consistency scoring result specifically includes:
acquiring temperature data of each battery in the battery pack of the electric automobile;
calculating the temperature difference between the batteries according to the temperature data of each battery;
and scoring according to the temperature difference between the batteries to obtain a battery temperature consistency scoring result.
As a further alternative of the method for evaluating a battery pack of an electric vehicle, the obtaining of the battery internal resistance consistency scoring result specifically includes:
acquiring voltage data and current data of each battery in the battery pack of the electric automobile;
calculating the internal resistance of each battery according to the voltage data and the current data of each battery;
obtaining the internal resistance difference between the batteries according to the internal resistance of each battery;
and scoring according to the internal resistance difference between the batteries to obtain a battery internal resistance consistency scoring result.
An electric vehicle battery pack evaluation system, comprising:
the first acquisition module is used for acquiring basic information of the battery pack of the electric automobile;
the first scoring module is used for scoring battery parameters according to basic information of the battery pack of the electric automobile to obtain battery parameter scoring results, wherein the battery parameter scoring results comprise battery capacity scoring results, battery self-discharge rate scoring results, battery voltage consistency scoring results, battery temperature consistency scoring results and battery internal resistance consistency scoring results;
and the prediction module is used for inputting the battery parameter scoring result into a preset prediction model to predict the service life of the battery, so that the evaluation of the battery pack of the electric automobile is realized.
As a further alternative of the electric vehicle battery pack evaluation system, the first scoring module includes a battery capacity scoring module, a battery self-discharge rate scoring module, a battery voltage consistency scoring module, a battery temperature consistency scoring module, and a battery internal resistance consistency scoring module, the battery capacity scoring module includes:
the second acquisition module is used for acquiring capacity historical data and charging frequency historical data of the electric automobile battery pack;
the construction module is used for establishing a capacity prediction model of the electric vehicle battery pack based on capacity historical data and charging frequency historical data by using a gray prediction algorithm;
the input module is used for inputting the current charging frequency historical data of the electric automobile battery pack into the capacity prediction model to obtain the current capacity of the electric automobile battery pack;
and the second scoring module is used for scoring according to the current capacity and the original capacity to obtain a battery capacity scoring result.
As a further alternative of the electric vehicle battery pack evaluation system, the battery self-discharge rate scoring module includes:
the third acquisition module is used for acquiring the self-discharge rate historical data of the electric automobile battery pack;
the fitting module is used for fitting the self-discharge rate historical data to obtain a self-discharge rate fitting coefficient of the electric vehicle battery pack;
the execution module is used for predicting according to the fitting coefficient and the discharge times of the electric automobile battery pack to obtain the current battery self-discharge rate of the electric automobile battery pack;
and the third scoring module is used for scoring according to the current self-discharge rate of the battery and the self-discharge rate of the original battery to obtain a scoring result of the self-discharge rate of the battery.
As a further alternative of the electric vehicle battery pack evaluation system, the battery voltage consistency scoring module includes:
a fourth obtaining module, configured to obtain voltage history data of each battery in the electric vehicle battery pack;
the generating module is used for generating a voltage state sequence of each battery according to the voltage history data of each battery;
the fourth scoring module is used for scoring the battery voltage consistency according to the voltage state sequence of each battery to obtain a battery voltage consistency scoring result;
the battery temperature consistency scoring module includes:
a fifth acquisition module, configured to acquire temperature data of each battery in the electric vehicle battery pack;
the first calculation module is used for calculating the temperature difference between the batteries according to the temperature data of each battery;
the fifth scoring module is used for scoring according to the temperature difference between the batteries to obtain a battery temperature consistency scoring result;
the battery internal resistance consistency scoring module comprises:
the sixth acquisition module is used for acquiring voltage data and current data of each battery in the electric automobile battery pack;
the second calculation module is used for calculating the internal resistance of each battery according to the voltage data and the current data of each battery;
the third calculation module is used for obtaining the internal resistance difference between the batteries according to the internal resistance of each battery;
and the sixth scoring module is used for scoring according to the internal resistance difference between the batteries to obtain a battery internal resistance consistency scoring result.
The beneficial effects of the invention are as follows: the battery pack basic information of the electric automobile is obtained, the battery capacity, the battery self-discharge rate, the battery voltage consistency, the battery temperature consistency and the battery internal resistance consistency are scored according to the battery pack basic information of the electric automobile, the battery pack of the electric automobile can be accurately and effectively evaluated, and meanwhile, the evaluation accuracy of the battery pack of the electric automobile can be further improved by inputting the scoring result into a preset prediction model to predict the service life of the battery.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an evaluation method of a battery pack of an electric vehicle according to the present invention;
fig. 2 is a schematic diagram of the battery pack evaluation system for an electric vehicle according to the present invention.
Detailed Description
The following description of the technical solutions in the embodiments of the present invention will be clear and complete, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, an electric vehicle battery pack evaluation method specifically includes:
acquiring basic information of a battery pack of the electric automobile;
grading battery parameters according to basic information of the battery pack of the electric automobile to obtain battery parameter grading results, wherein the battery parameter grading results comprise a battery capacity grading result, a battery self-discharge rate grading result, a battery voltage consistency grading result, a battery temperature consistency grading result and a battery internal resistance consistency grading result;
and inputting the grading result of the battery parameters into a preset prediction model to predict the service life of the battery, thereby realizing the evaluation of the battery pack of the electric automobile.
In this embodiment, by acquiring the basic information of the battery pack of the electric automobile and scoring the battery capacity, the battery self-discharge rate, the battery voltage consistency, the battery temperature consistency and the battery internal resistance consistency according to the basic information of the battery pack of the electric automobile, the battery pack of the electric automobile can be accurately and effectively evaluated, and meanwhile, the accuracy of evaluating the battery pack of the electric automobile can be further improved by inputting the scoring result into a preset prediction model to predict the service life of the battery.
Preferably, the obtaining of the battery capacity scoring result specifically includes:
acquiring capacity historical data and charging frequency historical data of the electric automobile battery pack;
establishing a capacity prediction model of the electric vehicle battery pack based on capacity historical data and charging frequency historical data by using a gray prediction algorithm;
inputting historical data of the current charging times of the electric automobile battery pack into a capacity prediction model to obtain the current capacity of the electric automobile battery pack;
and scoring according to the current capacity and the original capacity to obtain a battery capacity scoring result.
In this embodiment, a capacity prediction model of the electric vehicle battery pack is established by using a gray prediction algorithm based on capacity historical data and charging frequency historical data, and the current capacity of the electric vehicle battery pack is estimated based on the capacity prediction model, so that the estimated accuracy and efficiency can be improved, and the accuracy and efficiency for obtaining the battery capacity scoring result are improved.
Preferably, the obtaining of the battery self-discharge rate scoring result specifically includes:
acquiring self-discharge rate historical data of the electric automobile battery pack;
fitting the self-discharge rate historical data to obtain a self-discharge rate fitting coefficient of the electric vehicle battery pack;
predicting according to the fitting coefficient and the discharge times of the electric automobile battery pack to obtain the current self-discharge rate of the electric automobile battery pack;
and scoring according to the current self-discharge rate of the battery and the self-discharge rate of the original battery to obtain a scoring result of the self-discharge rate of the battery.
In this embodiment, the self-discharge rate fitting coefficient is obtained, and prediction is performed according to the self-discharge rate fitting coefficient and the number of times of discharge of the electric vehicle battery pack, so that the current battery self-discharge rate of the electric vehicle battery pack can be accurately obtained, and the accuracy of obtaining the battery self-discharge rate scoring result can be improved.
It should be noted that, the formula of the current battery self-discharge rate specifically includes:
wherein, C is the current self-discharge rate of the battery, A is the fitting coefficient, B is the self-discharge rate of the original battery, and D is the discharge times of the battery pack of the electric automobile.
Preferably, the obtaining of the battery voltage consistency scoring result specifically includes:
acquiring voltage history data of each battery in the electric automobile battery pack;
generating a voltage state sequence of each battery according to the voltage history data of each battery;
and scoring the battery voltage consistency according to the voltage state sequence of each battery to obtain a battery voltage consistency scoring result.
Preferably, the obtaining of the battery temperature consistency scoring result specifically includes:
acquiring temperature data of each battery in the battery pack of the electric automobile;
calculating the temperature difference between the batteries according to the temperature data of each battery;
and scoring according to the temperature difference between the batteries to obtain a battery temperature consistency scoring result.
Preferably, the obtaining of the battery internal resistance consistency scoring result specifically includes:
acquiring voltage data and current data of each battery in the battery pack of the electric automobile;
calculating the internal resistance of each battery according to the voltage data and the current data of each battery;
obtaining the internal resistance difference between the batteries according to the internal resistance of each battery;
and scoring according to the internal resistance difference between the batteries to obtain a battery internal resistance consistency scoring result.
An electric vehicle battery pack evaluation system, comprising:
the first acquisition module is used for acquiring basic information of the battery pack of the electric automobile;
the first scoring module is used for scoring battery parameters according to basic information of the battery pack of the electric automobile to obtain battery parameter scoring results, wherein the battery parameter scoring results comprise battery capacity scoring results, battery self-discharge rate scoring results, battery voltage consistency scoring results, battery temperature consistency scoring results and battery internal resistance consistency scoring results;
and the prediction module is used for inputting the battery parameter scoring result into a preset prediction model to predict the service life of the battery, so that the evaluation of the battery pack of the electric automobile is realized.
Preferably, the first scoring module includes a battery capacity scoring module, a battery self-discharge rate scoring module, a battery voltage consistency scoring module, a battery temperature consistency scoring module, and a battery internal resistance consistency scoring module, and the battery capacity scoring module includes:
the second acquisition module is used for acquiring capacity historical data and charging frequency historical data of the electric automobile battery pack;
the construction module is used for establishing a capacity prediction model of the electric vehicle battery pack based on capacity historical data and charging frequency historical data by using a gray prediction algorithm;
the input module is used for inputting the current charging frequency historical data of the electric automobile battery pack into the capacity prediction model to obtain the current capacity of the electric automobile battery pack;
and the second scoring module is used for scoring according to the current capacity and the original capacity to obtain a battery capacity scoring result.
Preferably, the battery self-discharge rate scoring module includes:
the third acquisition module is used for acquiring the self-discharge rate historical data of the electric automobile battery pack;
the fitting module is used for fitting the self-discharge rate historical data to obtain a self-discharge rate fitting coefficient of the electric vehicle battery pack;
the execution module is used for predicting according to the fitting coefficient and the discharge times of the electric automobile battery pack to obtain the current battery self-discharge rate of the electric automobile battery pack;
and the third scoring module is used for scoring according to the current self-discharge rate of the battery and the self-discharge rate of the original battery to obtain a scoring result of the self-discharge rate of the battery.
Preferably, the battery voltage consistency scoring module includes:
a fourth obtaining module, configured to obtain voltage history data of each battery in the electric vehicle battery pack;
the generating module is used for generating a voltage state sequence of each battery according to the voltage history data of each battery;
the fourth scoring module is used for scoring the battery voltage consistency according to the voltage state sequence of each battery to obtain a battery voltage consistency scoring result;
the battery temperature consistency scoring module includes:
a fifth acquisition module, configured to acquire temperature data of each battery in the electric vehicle battery pack;
the first calculation module is used for calculating the temperature difference between the batteries according to the temperature data of each battery;
the fifth scoring module is used for scoring according to the temperature difference between the batteries to obtain a battery temperature consistency scoring result;
the battery internal resistance consistency scoring module comprises:
the sixth acquisition module is used for acquiring voltage data and current data of each battery in the electric automobile battery pack;
the second calculation module is used for calculating the internal resistance of each battery according to the voltage data and the current data of each battery;
the third calculation module is used for obtaining the internal resistance difference between the batteries according to the internal resistance of each battery;
and the sixth scoring module is used for scoring according to the internal resistance difference between the batteries to obtain a battery internal resistance consistency scoring result.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. The method for evaluating the battery pack of the electric automobile is characterized by comprising the following steps of:
acquiring basic information of a battery pack of the electric automobile;
grading battery parameters according to basic information of the battery pack of the electric automobile to obtain battery parameter grading results, wherein the battery parameter grading results comprise a battery capacity grading result, a battery self-discharge rate grading result, a battery voltage consistency grading result, a battery temperature consistency grading result and a battery internal resistance consistency grading result;
and inputting the grading result of the battery parameters into a preset prediction model to predict the service life of the battery, thereby realizing the evaluation of the battery pack of the electric automobile.
2. The method for evaluating a battery pack of an electric vehicle according to claim 1, wherein the obtaining of the battery capacity scoring result specifically comprises:
acquiring capacity historical data and charging frequency historical data of the electric automobile battery pack;
establishing a capacity prediction model of the electric vehicle battery pack based on capacity historical data and charging frequency historical data by using a gray prediction algorithm;
inputting historical data of the current charging times of the electric automobile battery pack into a capacity prediction model to obtain the current capacity of the electric automobile battery pack;
and scoring according to the current capacity and the original capacity to obtain a battery capacity scoring result.
3. The method for evaluating the battery pack of the electric vehicle according to claim 2, wherein the obtaining of the battery self-discharge rate scoring result specifically comprises:
acquiring self-discharge rate historical data of the electric automobile battery pack;
fitting the self-discharge rate historical data to obtain a self-discharge rate fitting coefficient of the electric vehicle battery pack;
predicting according to the fitting coefficient and the discharge times of the electric automobile battery pack to obtain the current self-discharge rate of the electric automobile battery pack;
and scoring according to the current self-discharge rate of the battery and the self-discharge rate of the original battery to obtain a scoring result of the self-discharge rate of the battery.
4. The method for evaluating a battery pack of an electric vehicle according to claim 3, wherein the obtaining of the battery voltage consistency scoring result specifically comprises:
acquiring voltage history data of each battery in the electric automobile battery pack;
generating a voltage state sequence of each battery according to the voltage history data of each battery;
and scoring the battery voltage consistency according to the voltage state sequence of each battery to obtain a battery voltage consistency scoring result.
5. The method for evaluating a battery pack of an electric vehicle according to claim 4, wherein the obtaining of the battery temperature consistency scoring result specifically comprises:
acquiring temperature data of each battery in the battery pack of the electric automobile;
calculating the temperature difference between the batteries according to the temperature data of each battery;
and scoring according to the temperature difference between the batteries to obtain a battery temperature consistency scoring result.
6. The method for evaluating a battery pack of an electric vehicle according to claim 5, wherein the obtaining of the battery internal resistance consistency scoring result specifically comprises:
acquiring voltage data and current data of each battery in the battery pack of the electric automobile;
calculating the internal resistance of each battery according to the voltage data and the current data of each battery;
obtaining the internal resistance difference between the batteries according to the internal resistance of each battery;
and scoring according to the internal resistance difference between the batteries to obtain a battery internal resistance consistency scoring result.
7. An electric vehicle battery pack evaluation system, comprising:
the first acquisition module is used for acquiring basic information of the battery pack of the electric automobile;
the first scoring module is used for scoring battery parameters according to basic information of the battery pack of the electric automobile to obtain battery parameter scoring results, wherein the battery parameter scoring results comprise battery capacity scoring results, battery self-discharge rate scoring results, battery voltage consistency scoring results, battery temperature consistency scoring results and battery internal resistance consistency scoring results;
and the prediction module is used for inputting the battery parameter scoring result into a preset prediction model to predict the service life of the battery, so that the evaluation of the battery pack of the electric automobile is realized.
8. The electric vehicle battery pack assessment system of claim 7, wherein the first scoring module comprises a battery capacity scoring module, a battery self-discharge rate scoring module, a battery voltage uniformity scoring module, a battery temperature uniformity scoring module, and a battery internal resistance uniformity scoring module, the battery capacity scoring module comprising:
the second acquisition module is used for acquiring capacity historical data and charging frequency historical data of the electric automobile battery pack;
the construction module is used for establishing a capacity prediction model of the electric vehicle battery pack based on capacity historical data and charging frequency historical data by using a gray prediction algorithm;
the input module is used for inputting the current charging frequency historical data of the electric automobile battery pack into the capacity prediction model to obtain the current capacity of the electric automobile battery pack;
and the second scoring module is used for scoring according to the current capacity and the original capacity to obtain a battery capacity scoring result.
9. The electric vehicle battery pack evaluation system of claim 8, wherein the battery self-discharge rate scoring module comprises:
the third acquisition module is used for acquiring the self-discharge rate historical data of the electric automobile battery pack;
the fitting module is used for fitting the self-discharge rate historical data to obtain a self-discharge rate fitting coefficient of the electric vehicle battery pack;
the execution module is used for predicting according to the fitting coefficient and the discharge times of the electric automobile battery pack to obtain the current battery self-discharge rate of the electric automobile battery pack;
and the third scoring module is used for scoring according to the current self-discharge rate of the battery and the self-discharge rate of the original battery to obtain a scoring result of the self-discharge rate of the battery.
10. The electric vehicle battery pack evaluation system of claim 9, wherein the battery voltage uniformity scoring module comprises:
a fourth obtaining module, configured to obtain voltage history data of each battery in the electric vehicle battery pack;
the generating module is used for generating a voltage state sequence of each battery according to the voltage history data of each battery;
the fourth scoring module is used for scoring the battery voltage consistency according to the voltage state sequence of each battery to obtain a battery voltage consistency scoring result;
the battery temperature consistency scoring module includes:
a fifth acquisition module, configured to acquire temperature data of each battery in the electric vehicle battery pack;
the first calculation module is used for calculating the temperature difference between the batteries according to the temperature data of each battery;
the fifth scoring module is used for scoring according to the temperature difference between the batteries to obtain a battery temperature consistency scoring result;
the battery internal resistance consistency scoring module comprises:
the sixth acquisition module is used for acquiring voltage data and current data of each battery in the electric automobile battery pack;
the second calculation module is used for calculating the internal resistance of each battery according to the voltage data and the current data of each battery;
the third calculation module is used for obtaining the internal resistance difference between the batteries according to the internal resistance of each battery;
and the sixth scoring module is used for scoring according to the internal resistance difference between the batteries to obtain a battery internal resistance consistency scoring result.
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