Power lithium battery model parameter identifying and dump energy estimating method

Abstract

The invention discloses a power lithium battery model parameter identifying and dump energy estimating method. The method includes the steps of firstly, establishing a state space equation of a two-order impedance-capacitance model of a lithium battery; secondly, establishing a regression model of the relation of an end voltage and open circuit voltage and a current; thirdly, conducting parameteridentifying based on an iterative learning recursive least-squares method on the regression model; fourthly, conducting identifying based on the iterative learning recursive least-squares method on experimental data meeting the discharge current conditions in the parameter identifying process in the third step to obtain prediction errors, and conducting converging through the prediction errors toobtain a nonlinear function in parameters of the state space equation and a parameter set; fifthly, verifying the battery model precision formed by the nonlinear function and the parameter set obtained in the fourth step; sixthly, collecting current and voltage data, and estimating the dump energy through expanded Kalman filtering. The model parameter identifying precision is high, the dump energyestimation value error is small, and good application prospects are achieved.

Description

Technical field [0001] The invention relates to the technical field of new energy vehicle battery management, and specifically relates to a method for identifying parameters of a power lithium battery model and estimating remaining power. Background technique [0002] In the State Council’s “Thirteenth Five-Year Plan” National Science and Technology Innovation Plan, the development of new energy vehicles is the first project to establish and improve the core technology system of transportation. In the development of new energy vehicles, my country mainly promotes pure electric vehicles, and power lithium batteries are the core energy source of pure electric vehicles. The remaining power of a lithium battery, that is, the percentage of available capacity to rated capacity, is an important parameter to ensure the safe operation of lithium batteries and extend their useful life. The complexity of the electrochemical reactions inside lithium batteries causes strong nonlinearity...

AI Technical Summary

Problems solved by technology

However, for lithium batteries, due to the internal strong nonlinear characteristics, its model parameters will inevitably not be time-invariant and slowly time-varying. The problem of reduced modeling accuracy has become the main factor causing inaccurate estimation of remaining power

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