Novel lithium ion power cell SOC estimation method

Abstract

The invention discloses a novel lithium ion power cell SOC estimation method. The novel lithium ion power cell SOC estimation method is characterized in that a cell equivalent circuit model can be established, and the identification of the parameters of the established cell model can be carried out by adopting the least squares algorithm; according to the cell open-circuit voltage UOCV acquired by identifying the parameters according to the step one and the corresponding SOC relation, a corresponding function can be acquired by adopting a Shepherd model and a Nernst model in a combined manner, and the function is used for the matching of the UOCV and the SOC relation; the state equation and the observation equation of the SOC estimation can be established, and the STF algorithm has the strong robustness related to the model uncertainty and the extremely strong tracking capability related to the breaking state. The verification of the SOC estimation by adopting the EKF algorithm and the STF algorithm can be carried out by the constant current discharging experiment and the UDDS working condition experiment, and according to the result, the accuracy of the SOC estimation is higher by adopting the STF algorithm than adopting the EKF algorithm, and the convergence performance is better.

Description

technical field [0001] The invention relates to a novel method for estimating the SOC of a lithium-ion power battery. Background technique [0002] The estimation of the battery state of charge has always been the focus and difficulty of the battery management system. Accurate estimation of the battery SOC is of great significance for improving battery usage efficiency, extending battery life, improving battery safety and reliability, and vehicle energy management, but SOC cannot Direct measurement can only be estimated by other battery parameters such as battery output voltage and current. [0003] At present, the commonly used SOC estimation algorithms at home and abroad are: the ampere-hour integral method, which cannot give the initial value of SOC, and the inaccurate current measurement will lead to the cumulative error of SOC; the open circuit voltage method, which uses the corresponding relationship between the open circuit voltage of the battery and SOC It is simple...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the deficiencies in the prior art, the present invention discloses a novel method for estimating the SOC of a lithium-ion power battery, which uses a strong tracking filter to estimate the SOC to overcome the inaccurate shortcoming of the extended Kalman filter for estimating the SOC. The strong tracking filter consists of The extended Kalman filter is transformed, mainly for the inaccurate estimation and divergence of the filter caused by the uncertainty of the system model, and has the following advantages: (1) It has strong robustness to the model uncertainty; (2) The ability to track the sudden change state is extremely strong, even when the system reaches the equilibrium state, it still maintains the ability to track the slow change state and the sudden change state; (3) Moderate computational complexity

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