Power battery fault diagnosis method and system based on data driving

Abstract

The invention provides a power battery fault diagnosis method and early warning system based on data driving. The method comprises the following steps: 1, collecting the performance parameters of a power battery under various working conditions and various states of the power battery, including the capacity, voltage, internal resistance and power of the power battery; 2, cleaning the acquired data; 3, calculating the state of charge SOC and the state of health SOH of the power battery according to the cleaned data; 4, formulating a fault level according to actual driving experience and automobile safety; 5, making the data obtained in steps 2, 3 and 4 into a data set; 6, putting the training set into a gradient boosting regression tree model, and carrying out iterative training on the training set; and 7, putting the test set into the model, evaluating the accuracy of the model, and adjusting model parameters according to the accuracy. The power battery fault can be accurately predicted, early warning is carried out on the fault, and the safety of the electric vehicle is greatly improved.

Description

technical field [0001] The invention relates to the field of power battery safety of electric vehicles, in particular to a data-driven power battery fault diagnosis method and system. Background technique [0002] As environmental protection issues and energy issues become increasingly prominent, various industries have responded to the national call for energy conservation and emission reduction, and the new energy industry has ushered in a spring. As a pillar industry of the new energy industry, new energy vehicles have received national attention. my country has listed new energy vehicles as one of the seven strategic emerging industries. The current era can be considered the best era for the development of new energy vehicles. [0003] New energy vehicles mainly include pure electric vehicles, fuel cell vehicles and hybrid vehicles, of which pure electric vehicles use the electric energy provided by the battery as the power source to drive the vehicle; fuel cell vehicles...

AI Technical Summary

Problems solved by technology

[0004] At the present stage, power battery fault diagnosis has difficulties in the diversity of diagnostic objects and the complexity of fault states. Therefore, intelligent fault diagnosis and fault diagnosis adaptability need to be continuously improved.

The current mainstream fault diagnosis is divided into two methods: offline diagnosis and online diagnosis. Among them, offline diagnosis can no longer meet the needs of new energy vehicle power battery fault diagnosis. It has the characteristics of low intelligent fault diagnosis and weak adaptability.

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