Research On On-line Estimation Method Of Power Battery Core Temperature Based On Kalman Filter

As one of the core components of electric vehicles,power batteries play an important role in the dynamics and safety of electric vehicles.The core temperature of the power battery,as one of the key information of the battery working status,not only affects the internal resistance and capacity of the power battery,but also the necessary input information for the battery management system and vehicle control strategy.Therefore,accurately obtaining the core temperature of power batteries is the basis for efficient and safe use of power batteries.The traditional core temperature monitoring method of power battery based on temperature sensor cannot accurately estimate the core temperature of power battery,and during the data battery power sampling process,random interference such as sensor noise will affect the temperature estimation of power battery.Considering the many advantages of the Kalman Filter(KF)algorithm in system state estimation,this paper combines the battery thermal model with the Kalman filter algorithm to propose a Kalman filter-based core temperature estimation for power batteries Method: On-line estimation of the core temperature of the power battery.In the study of this article,the characteristics of the lithium-ion battery and the function of the battery management system are first introduced,and the theoretical support is provided for improving the use performance and safety performance of the power battery.Then,the lithium-ion battery is modeled,and the electrochemical model and equivalent circuit model of the lithium-ion battery are established.After comprehensive model accuracy,complexity,and research goals,the first-order RC model in the equivalent circuit model is selected as the battery system.Model;and parameter identification of the battery's first-order RC equivalent circuit model based on the least square method.Subsequently,the heat generation mechanism of the lithium ion battery is analyzed,and the battery cell heat generation rate model and the tab heat generation rate model are established respectively;the lithium ion battery heat dissipation mechanism is analyzed,and the battery cell heat dissipation rate model and Heat dissipation rate model of the ears;Based on the law of conservation of energy,the cell thermal model and the ear heat model of the lithium ion battery are established.Finally,the classic Kalman filter algorithm is introduced;the derivation process of the state space equation of the thermal model of the lithium-ion battery is described in detail,and the core temperature estimator of the lithium-ion battery is established in conjunction with the Kalman filter algorithm;The core temperature of the lithium-ion battery is estimated online based on KF under the / Simulink platform,and the accuracy of the algorithm is verified based on the experimental results of the battery temperature.The verification results show that the core battery temperature estimation algorithm based on Kalman filter has good accuracy and reliability.