Method and system for predicting residual life of battery
A prediction method and prediction system technology, which is applied in the direction of measuring electricity, measuring devices, measuring electrical variables, etc., can solve the problem of inaccurate prediction of the remaining life of the battery, and achieve the effect of improving accuracy
Active Publication Date: 2021-07-02
BEIJING INST OF TECH XINYUAN INFORMATION TECH CO LTD
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AI Technical Summary
Problems solved by technology
Current predictions of remaining battery life are not accurate enough
Method used
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Embodiment 1
[0079] Select 20 samples of new energy vehicle lithium-ion battery sample data with charge-discharge cycle data reaching 120 weeks.
[0080] The Gaussian process regression model is selected as the battery prediction model, and RQ*LIN+RQ*PER is selected as the combined kernel function. The value of α is selected as 0.1, and the value of l is selected as 1.
[0081] Select the data of the first 100 weeks as a learning sample, optimize the battery prediction model, and adjust the range and size of hyperparameters to obtain the optimized battery prediction model.
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The invention relates to a method and a system for predicting the residual life of a battery. The method comprises the following steps that sample data of battery capacity is obtained; the sample data comprises a battery capacity sequence arranged according to the number of charge and discharge cycles; a Gaussian process regression method is adopted, the capacity in the battery capacity sequence serves as input, and the number of charge and discharge cycles of the battery serves as output to train a battery prediction model; the current capacity of a to-be-predicted battery is inputted into the trained battery prediction model to obtain the current charge and discharge cycle number of the to-be-predicted battery; the end-of-life capacity threshold value of the to-be-predicted battery is inputted into the trained battery prediction model, and the number of charge and discharge cycles when the life of the to-be-predicted battery is ended is obtained; and according to the current charge and discharge cycle number of the to-be-predicted battery and the chargeand discharge cycle number at the end of the life, the residual charge and discharge cycle number of the to-be-predicted battery is determined. The prediction accuracy is improved.
Description
technical field [0001] The invention relates to the field of battery detection, in particular to a method and system for predicting the remaining battery life. Background technique [0002] At present, the market share of new energy vehicles is increasing year by year. As the core component of new energy vehicles, power batteries occupy a pivotal position. According to relevant data predictions, 2022 will usher in the large-scale decommissioning of new energy vehicle power batteries, followed by the issue of power battery recycling. In order to achieve environmental protection and other requirements, for the recycling, cascade utilization and recycling of waste power batteries, among which the cascade utilization is the most researched and discussed, some enterprises and research institutions are also actively conducting research and discussions related to battery residual value evaluation, such as residual Life, remaining capacity, safety performance evaluation and other ...
Claims
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IPC IPC(8): G01R31/392G01R31/367G01R31/36G01R31/00
CPCG01R31/392G01R31/367G01R31/3648G01R31/006
Inventor 王震坡龙超华刘鹏李阳葛付林赵菲菲
Owner BEIJING INST OF TECH XINYUAN INFORMATION TECH CO LTD