Method for adaptively and jointly estimating state of charge of lithium ion battery and model parameter

Abstract

The invention relates to a method for adaptively and jointly estimating the state of charge (SOC) of a lithium ion battery and a model parameter. The method comprises the following steps of: 1) constructing an offline model including an open-circuit voltage module and an equivalent circuit model; 2) performing online joint estimation including: establishing an nonlinear state-space equation basedon a current integration method and the offline model; performing sensitivity analysis based on a circuit parameter function and establishing an augmented nonlinear state-space equation; establishingSOC and model parameter adaptive joint estimation model based on a moving horizon estimating strategy, and setting various algorithm parameters; jointly estimating the SOC and the model parameter by using the online estimation model based on detected voltage and current. Compared with the prior art, the method, by means of model parameter online estimation, improves the accuracy and reliability ofthe SOC estimated value of the lithium ion battery in an environment where operating condition property difference and an individual are inconsistent, and finally improves the overall performance ofa battery management system.

Description

technical field [0001] The invention relates to a method for estimating the state of charge of a battery, in particular to a method for jointly estimating the state of charge of a lithium-ion battery and model parameters adaptively. Background technique [0002] Lithium-ion batteries have become the energy storage solution of choice in emerging technology fields such as portable electronic devices, electric vehicles, home energy storage, and space technology. Battery State of Charge (SOC) estimation, as one of the core functions of the lithium battery management system, is crucial to improving battery usage, prolonging battery life, and improving battery safety. When using the battery model for SOC estimation, due to the objective and unavoidable existence of differences in operating conditions and cell inconsistencies, model parameter mismatch often occurs, which seriously affects the performance of SOC estimation. Therefore, it is necessary to find an adaptive joint estim...

AI Technical Summary

Problems solved by technology

When using the battery model for SOC estimation, due to the objective and unavoidable existence of differences in operating conditions and cell inconsistencies, model parameters often do not match, which seriously affects the performance of SOC estimation.

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