Study On State Of Charge And Peak Power Estimation Of Ternary Lithium Ion Power Batteries

As the core component of pure electric vehicles,the technical development level of power batteries is the key support for the large-scale electric transformation of China’s automotive industry.State of charge(SOC)and peak power(SOP)are two important indicators that characterize the dynamic and safety performance of power batteries.The state of charge(SOC)predicts the range of an electric vehicle by describing detailed information about the remaining power of the power battery,and the peak power characterizes the safety performance of the power battery by evaluating the maximum continuous power that does not exceed the threshold value in a short period of time.Therefore,the thesis conducts research on the estimation methods of SOC and SOP for lithium ion power batteries,and the specific work is as follows:(1)Taking the ternary lithium ion battery for vehicles as the research object,the thesis first conducted basic characteristic experiments such as power battery capacity testing experiments,voltage rebound characteristics experiments,open-circuit voltage calibration experiments under different states of charge,battery discharge experiments at different magnification,and Hybrid Pulse Power Characterization(HPPC)tests.Through analyzing the basic characteristics of ternary lithium ion batteries,It lays a foundation for the later research on equivalent circuit model parameter identification and SOC estimation.(2)In this paper,the second-order RC model circuit is used as the battery equivalent circuit model.Firstly,the parameters of the second-order RC circuit model are identified offline and online using the Cftool fitting toolbox method and the Recursive Least Square Method with forgetting factor(FFRLS)algorithm,respectively.The accuracy of the two parameter identification methods is verified in combination with the power battery DST operating conditions.The research results show that the maximum error of the terminal voltage of the power battery obtained based on the offline identification algorithm is within60 m V,and the root mean square error is 1.77%.However,the maximum error of the terminal voltage obtained based on the online identification algorithm is within 40 m V,and the root mean square error is 1.15%.The online identification algorithm has higher accuracy.Subsequent research work such as SOC and SOP estimation uses the online model parameter identification method based on the FFRLS algorithm.(3)Aiming at the problem of incompatibility between the accuracy and robustness of SOC estimation for power batteries,based on the previously obtained second-order RC equivalent circuit model,the thesis uses EKF algorithm and UKF algorithm to estimate and analyze the SOC of lithium ion batteries,and tests the accuracy and robustness of the two algorithms based on the HPPC and DST operating conditions of power batteries.The results show that the root mean square error of SOC estimated based on FFRLS-EKF is 1.17%,while the root mean square error of SOC estimated based on FFRLS-UKF algorithm is 0.9%;The DST condition based on the FFRLS-EKF algorithm requires 300 s to complete convergence,while the FFRLS-UKF algorithm can only complete convergence in 80 s.Therefore,the FFLRS-UKF joint estimation algorithm has superior error accuracy and better robustness in estimating SOC.(4)Aiming at the problem of large SOP estimation error under single parameter constraints,this paper proposes a SOP estimation algorithm based on three constraints: OCV,battery real-time SOC,and battery current limitation.Based on the estimated continuous peak charge and discharge current of the power battery under DST conditions,the corresponding continuous peak charge and discharge power is calculated.The comparison with the experimental values of charge and discharge power shows that the maximum error of continuous peak discharge power is controlled within 3W,and the maximum error of continuous peak charge power is controlled within 2W,effectively improving the estimation accuracy of power battery SOP.