SOC And SOH Estimation Of Lithium-ion Battery Based On A Coupled Electrochemical-Thermal Model

The advantages of electric vehicle,such as high efficiency,sustainability,clean and environmental protection,have promoted the transformation of automobile industry from traditional vehicle to new energy vehicle.The market penetration of electric vehicle is closely related to the efficiency,lifetime,safety,and cost of battery.Currently,the key challenge of battery management system is to accurately estimate the state of charge and health of battery,so as to provide the estimated value of the remaining driving range of battery under various operating conditions.High fidelity battery model and accurate estimation strategy are indispensable for the state identification of battery.Therefore,in this paper,the coupled electrochemical-thermal model of lithium-ion battery is studied,and SOC/SOH estimation algorithms are designed based on the model,which realize the application of electrochemical and thermal correlated theories in the battery management system.Firstly,based on the internal structure of Li-ion battery and the principle of charge and discharge,the physical,chemical,and electrochemical characteristics of the battery are analyzed,and the electrochemical model combining macroscopic and microscopic aspects of the battery is preliminarily established.The idea of average electrode is applied to simplify the electrochemical model and the large-system theory is adopted to reduce the order of the electrochemical model.According to the Bernardi heat generation equation and Arrhenius equation,this paper analyzes the radial thermal characteristics of the battery,introduces the influence of temperature on the internal electrochemical related parameters of the battery,builds the thermal model,and completes the coupling between the simplified reduced-order electrochemical model and the thermal model.Battery cell multi-rate discharge experiments and 1C discharge experiments at different temperature experiments verify the accuracy of the coupled model.The battery voltage error is generally within 0.2V,and the temperature error is within 1?.Secondly,based on the coupled electrochemical-thermal model,the SOC estimation is researched.Combining the accuracy of the extended Kalman filter algorithm and the robustness of the smooth variable structure filter,a hybrid observer with adaptive filter gain in the estimation process is proposed.Through the effective observation of the lithium-ion concentration in the battery,the SOC estimation method of the lithium-ion battery is established.Compared with the Ampere hour integration method,the SOC observation deviation of the proposed method is less than 4% and has a correction function for the existing initial error.Thirdly,the impacts of battery discharge rate,depth of discharge and cycle number on battery SOH are analyzed.Based on the SOC estimation of battery,the cycle numbers of different discharge depths are calculated by rain flow counting method,and the capacity attenuation factor of battery is designed to build a high-performance aging prediction model.The validity of the algorithm is verified by the experiments of battery cycle aging under different discharge rates and discharge depths.The SOH estimation error of the proposed method is less than 3%.Finally,in order to verify the operation effects of the model and control algorithm in the actual controller,the hardware in the loop test platform of the battery management system is used to create the semi physical simulation of the electric vehicle.The whole vehicle model and the battery pack model are built in the software MATLAB/Simulink,the state estimation algorithm of the lithium-ion battery is compiled by the rapid prototype controller,and the HiL test system documents are established.The validity and robustness of the estimation algorithm in the actual controller is verified by the vehicle NEDC cycle road test.