Identifying parameters from discharging and relaxation curves of lithium-ion batteries using porous electrode theory

To improve the performance of lithium-ion secondary batteries (LiB) for electric vehicles and hybrid electric vehicles, it is very important to understand the internal transport phenomena and resistance under a high rate condition to increase power density. Numerical simulation of electrochemical reaction and mass transport in the electrode layer is needed to design a heterogeneous porous electrode structure consisting of active material, conductive material, and binder. The values of parameters in this model are essential for accuracy of it. However, some parameters cannot be measured precisely in an experiment. In this study, a method of identifying these parameters was established by using experimental data in various conditions and a complex method. This approach was applied to 1D LiB simulation. Fitting the experimental data of some SOC and some discharge rate conditions was carried out, and RMSE (Root Mean Square Error) to judge this fitting was evaluated. From these results, it was concluded that the parameters can be identified. With the identified parameters, the optimal electrode structure for a high-output power density cell was designed automatically.