Research On Modeling And Internal Temperature Estimation Of Energy Storage Battery

At present,lithium-ion batteries can withstand the advantages of high energy density,low self-discharge,and long replacement,and have been widely used in power grid energy storage.However,the safety of lithium-ion batteries is still an important factor for its further development,especially the core issue of thermal runaway needs to be solved urgently.The estimation of the internal temperature of the battery is an effective means to prevent thermal runaway,and is also the basis for ensuring the stable operation of the energy storage generator.Starting from the modeling and analysis of lithium-ion batteries,we mainly explore battery internal temperature estimation methods that use model parameters.The research work carried out is mainly as follows:(1)Exploring the method and basis for establishing an impedance model.First,the working principle and characteristic parameters of lithium-ion batteries are introduced,and the working characteristics of lithium-ion batteries for energy storage in power grids are studied through charge and discharge experiments.Then,by analyzing the electrochemical impedance spectroscopy(EIS)of common equivalent components and typical equivalent circuits,the essentials and principles of impedance model establishment are clarified.(2)Established impedance model of energy storage battery.Taking the largecapacity single-cell lithium-ion battery for grid energy storage as an experimental object,an EIS measurement experiment was designed,and the EIS of the battery in different states was obtained,and the correlation between the EIS of the lithium-ion battery and the internal temperature was clarified.At the same time,by comparing the fitting effects of various equivalent models,combining the theory of electrochemical impedance spectroscopy and the EIS characteristics of common equivalent circuit components,the R(CR)(CR)model and the Q(CR)model were established and established The applicable temperature range of the two is that the R(CR)(CR)model is valid below 50?,and the Q(CR)model is suitable for temperatures of 50?and above.(3)Research on battery internal temperature estimation.The software Zsimp Win was used to identify the parameters of the impedance model in all states,and according to the results of the parameter identification,the parameters related to the internal temperature and SOC were found.For the R(CR)(CR)model,the individual parameters have a strong linear relationship with the internal temperature.Through the linear fitting method,a mathematical function relationship between the parameters and the internal temperature is established to predict the internal battery.temperature.In view of the non-linear relationship between the model parameters of Q(CR)and the internal temperature and the inability to establish a clear mathematical function,an internal temperature estimation algorithm based on support vector regression(SVR)was proposed.The cross-validation method is used to optimize the SVR model parameters.Finally,the internal temperature estimation algorithm is verified by analyzing the relative error of the predicted temperature.The final results show that the internal temperature estimation algorithm based on the impedance model parameters can obtain higher accuracy internal temperature estimation results.