Characterization and identification towards dynamic-based electrical modeling of lithium-ion batteries

Lithium-ion batteries are widely recognized as a crucial enabling technology for the advancement of electric vehicles and energy storage systems in the grid.The design of battery state estimation and control algorithms in battery management systems is usually based on battery models,which interpret crucial battery dynamics through the utilization of mathematical functions.Therefore,the investigation of battery dynamics with the purpose of battery system identification has garnered considerable attention in the realm of battery research.Characterization methods in terms of linear and nonlinear response of lithium-ion batteries have emerged as a prominent area of study in this field.This review has undertaken an analysis and discussion of characterization methods,with a particular focus on the motivation of battery system identification.Specifically,this work encompasses the incorporation of frequency domain nonlinear characterization methods and dynamics-based battery electrical models.The aim of this study is to establish a connection between the characterization and identification of battery systems for researchers and engineers specialized in the field of batteries,with the intention of promoting the advancement of efficient battery technology for real-world applications.

Identification of dynamic model parameters for lithium-ion batteries used in hybrid electric vehicles

An electrical equivalent circuit model for lithium-ion batteries used for hybrid electric vehicles （HEV） is presented. The model has two RC networks characterizing battery activation and concentration polarization process. The parameters of the model are identified using combined experimental and extended Kalman filter （EKF） recursive methods. The open-circuit voltage and ohmic resistance of the battery are directly measured and calculated from experimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RC network parameters, are estimated using the EKF method. Experimental and simulation results are presented to demonstrate the efficacy of the proposed circuit model and parameter identification techniques for simulating battery dynamics.

Modeling and Optimization of Heat Dissipation Structure of EV Battery Pack

In order to solve the problems of high temperature and inconsistency in the operation of electric vehicle（ EV） battery pack,computational fluid dynamics（ CFD） simulation method is used to simulate and optimize the heat dissipation of battery pack. The heat generation rate at different discharge magnifications is identified by establishing the heat generation model of the battery. In the forced air cooling mode,the Fluent software is used to compare the effects of different inlet and outlet directions,inlet angles,outlet angles,outlet sizes and inlet air speeds on heat dissipation. The simulation results show that the heat dissipation effect of the structure with the inlet and outlet on the same side is better than that on the different sides; the appropriate inlet angle and outlet width can improve the uniformity of temperature field; the increase of the inlet speed can improve the heat dissipation effect significantly. Compared with the steady temperature field of the initial structure,the average temperature after structure optimization is reduced by 4. 8℃ and the temperature difference is reduced by 15. 8℃,so that the battery can work under reasonable temperature and temperature difference.