Research On Electrothermal Coupling Modeling,Parameters Identification And State-of-charge Estimation For Power Battery Of Electric Vehicle

With the intensification of energy and environmental issues,electric vehicles have gradually become an important direction for the strong support and development of governments and the automotive industry.The effective management and monitoring of the battery by the battery management system（BMS）is the key to ensure the safe and efficient operation of electric vehicles.However,the battery will exhibit highly nonlinear and time-varying characteristics under the changeable,complex environmental temperature and load conditions of electric vehicles.In BMS,the establishment of a battery model that can accurately reflect the characteristics of the battery under dynamic conditions and a high-precision state of charge（SOC）estimation algorithm have been the key technologies that need to be broken in the field of electric vehicles.The Li Fe PO₄battery is taken as the research object.An electrothermal coupling model that considers the battery heating and the battey parameters changes with different currents,temperatures and SOC ranges is established to improve the accuracy of the battery model under dynamic conditions.An impedance model based on a semi-empirical method is designed to improve the accuracy of battery parameter identification.At the same time,a battery capacity real-time loss model is built and combined with the Cubature Kalman Filter（CKF）to improve the SOC estimation algorithm.Finally,the battery model and SOC estimation algorithm constructed in MATLAB/Simulink are verified under multiple working conditions.The main research is as follows:1.Electro-thermal coupling model of power battery.The working principle and performance parameters of lithium-ion batteries are introduced.The main factors affecting the performance of lithium-ion batteries are analyzed.An electro-thermal coupling model that comprehensively considers the dynamic changes of battery parameters and the influence of battery heating under complex working conditions is bulit.2.Parameter identification and analysis of power battery.Based on the power battery test platform,the parameter identification tests are performed.An impedance model based on the semi-empirical method is bulit by combining the electrochemical mechanism and the results of impedance parameter identification tests.A simplified open circuit voltage model that considered the hysteresis voltage characteristics is established.The heat exchange coefficient of the test battery is also identified by the battery cooling test.3.SOC estimation algorithm of power battery based on a real-time capacity loss model.Based on battery capacity characteristic tests under different conditions,a real-time capacity loss model is bulit.The accuracy and robustness of the commonly used Kalman filter algorithms are analyzed and compared.Then an improved SOC estimation method is improved by combing the real-time capacity loss model and CKF algorithm.4.Simulation and verification.Combining the improved electrothermal coupling model and SOC estimation algorithm,a complete lithium-ion battery simulation model is built in MATLAB/Simulink.The terminal voltage,temperature and SOC of the simulation model are verified under multiple operating conditions.