Research On The Estimation Of The State Of Charge Of Lithium-ion Batteries With A Wide Temperature Range Over The Life Span

The power battery is the main power source of the electric vehicle.The state of charge(SOC)of the battery is equivalent to the fuel gauge of traditional fuel vehicle.The accurate SOC estimation plays an important role in optimizing electric vehicle energy management,improving the capacity of power batteries,preventing overcharge and over-discharge of power batteries,and ensuring the safety performance and long life of power battery in the process of using electric vehicle.Because of the complex electrochemical reactions occurring inside the power battery when it is working,the internal performance of the battery is time-varying and non-linear,which makes it difficult for BMS to accurately know the current state of the battery.In addition,the diversity of external environment and operating conditions leads to the increasing uncertainty of the performance degradation of the power battery.At the same time,with the increase of battery working frequency,the state of health(SOH)will inevitably change,that is,battery aging.This change will further enhance the difficulty of estimating battery SOC.In this paper,the ternary lithium-ion battery for vehicle is analyzed.The influence factors of three-component lithium-ion batteries on battery performance are analyzed from three aspects: different rate,different temperature and different life.The equivalent circuit model is used to establish the battery model,and the battery operating characteristics in full life and wide temperature range are analyzed respectively,and the State-of-charge estimation of li-ion battery based on wide temperature range and life-cycle is realized.Firstly,a lithium-ion battery test system is built.The main performance parameters of the battery and its influencing factors are analyzed from the capacity,voltage,charge and discharge rate,life and state of charge of lithium-ion batteries.According to the experimental data,the performance degradation of the power battery,the influence of temperature and the characteristics under different discharge rates are analyzed.The development of hybrid pulse power characterization(HPPC)experiment is described.The second-order RC equivalent circuit model is established.Based on the experimental data,the model parameters are identified by genetic algorithm(GA),and the battery database with the change of ambient temperature and life is established.The parameters of the model can be adapted to different ambient temperature and different SOH.Secondly,the working principles of Kalman Filtering(KF)and Adaptive Extended Kalman Filter(AEKF)are deduced and analyzed,their advantages and disadvantages are compared and analyzed,and their working principles are analyzed by state equation.The SOC of batteries is estimated by adaptive extended Kalman filter at different temperatures.The accuracy of the model and the robustness of the algorithm are verified under constant and variable temperatures conditions.Finally,the influence of battery aging on SOC is analyzed.With the increase of battery usage frequency,the amount of electricity discharged by the battery will decrease,that is,the battery ages,which will affect the estimation accuracy of battery SOC.Considering the influence of accurate SOH value on the estimation accuracy of battery SOC,this paper updates the input capacity of AEKF algorithm using LSTM algorithm based on the life-cycle test data of power lithium-ion batteries,identifies the parameters of the established model and verifies the accuracy of the model.The Linear Interpolation theory is used to accurately estimate the SOC of the battery under any aging state,and the SOC estimation accuracy under a certain SOH is verified.