Electrothermal Coupling Modeling And Multi-state Joint Estimation For Lithium-ion Battery

With the increasingly severe problems of environmental pollution and energy crisis,countries have taken the vigorous development of electric vehicles as an important measure to solve the above problems.The electric vehicle related industry has ushered in a spring of development.As the "internal combustion engine"of electric vehicles,lithium-ion battery has also rapidly popularized and flourished due to its advantages such as high energy density and long cycle life.The safe and reliable operation of electric vehicles not only depends on the quality of lithium-ion battery,but also on the performance of the BMS.The status monitoring,energy management,and fault diagnosis functions of BMS are of great significance for the safe and efficient application of lithium-ion battery.However,due to the relatively closed structure of lithium-ion battery,complex internal electrochemical reactions,and variable environmental temperatures,there are still challenges to the accuracy of battery modeling and state estimation in BMS applications.Therefore,this article focuses on the modeling of electrothermal coupling and multi-state joint estimation of lithium-ion battery.The specific research content is as follows:This paper takes the LiNCM battery as the research object,analyzes its internal working principles,builds a battery testing platform,and designs a battery testing scheme.Then drill holes into the battery and install a temperature sensor to obtain real-time core temperature data of the battery’s operation.Next,conduct testing experiments on perforated battery to provide data support for subsequent research.Finally,analyze the characteristics of battery capacity,DC internal resistance,open circuit voltage,and internal and external temperatures under different environmental temperatures.Aiming at the problem of poor temperature adaptability in traditional lithium-ion battery models,this paper constructs an electrothermal coupling model consisting of a temperature dependent second-order RC equivalent circuit model and a dual state lumped parameter thermal model.The forgetting factor recursive least squares method is used to identify the electrical model parameters at different temperatures and SOC.The accuracy of the model is verified using pulsed discharge and UDDS operating condition test data.The results indicate that the maximum error between the model output voltage and the experimental measurement value is only 30 mV.After analyzing the mechanism of heat generation and dissipation of lithium-ion battery,a two-state lumped parameter model is selected to simulate the thermal behavior of the battery.The adaptive weight particle swarm optimization algorithm is used to identify the thermophysical parameters.The model accuracy is verified using the test data of 1C discharge condition and UDDS condition.After calculation,the maximum error of the model is less than 1℃.The experimental results show that the electrothermal coupling model can accurately describe the electrothermal characteristics of lithium-ion battery.This paper proposes a joint estimation method based on the electrothermal coupling model to address the coupling problem between the SOC and the SOT estimation for lithium-ion battery.Based on traditional unscented Kalman filtering algorithm,an adaptive noise link is added to obtain the AUKF algorithm.To verify the superiority of the AUKF algorithm,the SOC estimation results of three KF class algorithms for DST operating condition are compared horizontally.The results indicate that the AUKF algorithm has better estimation accuracy and convergence speed.Validate the proposed joint estimation algorithm using test data from different rates of charging and discharging conditions,as well as UDDS and DST conditions at different temperatures.Through the analysis of RMSE and MAE of the estimation results,the method has good estimation accuracy and adaptability to operating conditions in a wide temperature range.Aiming at the problem of single constraints on SOP estimation for lithium-ion battery,this paper adds core temperature constraint to the commonly used constraints and proposes a multi-state constraints SOP estimation method for lithium-ion battery that considers core temperature.Based on the previous research on joint estimation of SOC and SOT,the estimation results of SOC and SOT,as well as the output voltage of the model,are used as inputs.The peak current calculation formulas under various constraint conditions are derived in detail.Finally,a multi-state constrained SOP estimation method based on the AUKF algorithm is proposed by combining multiple constraint conditions with battery design limits.To verify the feasibility and robustness of this method,continuous SOP estimation is performed at different sampling time intervals under different temperature and UDDS conditions.After analysis,it is found that the SOP estimation method proposed in this article can effectively limit peak current and peak power,providing assurance for the energy management of BMS and the safe use of lithium-ion battery.