State-of-charge Estimation And Thermal Imaging Analysis Of Lithium-ion Power Battery

With the constant challenges of global petrochemical energy shortage environmental pollution and extreme weather,the development of new energy vehicle industry has risen to a national strategy,especially in China.Lithium-ion batteries as the main energy source of Electric Vehicles,accurate estimation of its State of Charge(SOC)is one of the core technologies of in electric vehicle applications,and it is also an important guarantee for safe,reliable and efficient operation of batteries.The main research contents of this paper are as follows:(1)The first and second-order Thevenin equivalent circuit models and model parameter identification methods are studied.The offline parameter identification uses the exponential function fitting method,and the online parameter identification based on the recursive least squares method(FRLS)with the forgetting factor.The accuracy of two methods in parameter identification is compared.The influence of various parameter in the model on the accuracy of SOC estimation is analyzed by the control variable method.meanwhile,the effects of the OCV-SOC curve fitted by different orders,the measurement noise of voltage and current on the estimation accuracy of SOC is studied.Last,the influence of battery aging on model parameters is analyzed.(2)An online SOC estimation algorithm based on improved adaptive cubature Kalman filter(ACKF)is proposed in this paper,the improved algorithm introduces an adaptive covariance matching method to automatically adjust the error.the root mean square error(RMSE)of online SOC estimation based on the improved ACKF is less than 0.5% without initial SOC error under the FUDS and NEDC cycles test.Compared with Unscented Kalman filter(UKF)and Cubature Kalman filter(CKF)algorithm,the proposed ACKF algorithm has achieved good results in terms of algorithm accuracy,convergence and robustness.(3)The temperature is one of the important factors affecting the performance and service life of the lithium ion battery.Through temperature changes,thermal imaging and battery thermal models.The surface temperature distribution characteristics of lithium ion power battery during charge and discharge under different current rates and different aging conditions are analyzed comprehensively.It provides a reference for the development of management system which can prolong the service life of batteries and ensure the safe and efficient operation of batteries.