Lithium ion battery health state estimation method and system based on support vector machine

Abstract

The invention discloses a lithium ion battery health state estimation method and system based on a support vector machine. The method comprises the steps of determining input variables and output variables of support vector machine regression prediction; dividing the input variables and the output variables into a training set data set and a test set data set; performing regression model buildingon normalized training set data to obtain a regression function; substituting the test set data into a trained regression model, thereby predicting an electric quantity charged when constant current charging of a battery reaches a cut-off voltage; and fitting the electric quantity charged when the constant current charging reaches the cut-off voltage and current test capacity obtained after capacity testing, and substituting an electric quantity obtained by prediction based on test set data into a fitted equation to obtain current predicted capacity, so that a health state of the battery is estimated. The estimation method and system can be used for predicting the electric quantity charged when the constant current charging of the lithium ion battery reaches the cut-off voltage in variousconstant current charging environments, and has wide applicability.

Description

technical field [0001] The invention belongs to the technical field of estimation of the state of health of lithium-ion batteries, and in particular relates to a method and system for estimating the state of health of lithium-ion batteries based on a support vector machine. Background technique [0002] Compared with fuel vehicles, electric vehicles have greater advantages in terms of energy saving, emission reduction and environmental protection. Therefore, various countries are scrambling to introduce various incentives to vigorously promote the development of electric vehicles. Lithium batteries have the advantages of high specific energy, long service life, high rated voltage, high power tolerance, and low self-discharge rate, and have been favored by electric vehicle manufacturers since their listing. The rapid development of electric vehicles has made people put forward higher requirements on the performance of lithium batteries, so the state of health (State Of Health...

AI Technical Summary

Problems solved by technology

due to test c M The test cycle is long and will cause waste, so accurate, reliable and convenient estimation of the SOH of the battery is an important task of the battery management system

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