Parameter identification method of multi-particle model for lithium-ion batteries

Electrochemical models, characterized by high fidelity and physical interpretability, have been applied in various fields such as fast charging, battery state estimation, and battery material design. Currently, widely utilized single particle-based model exhibits high computational efficiency but suffers from low simulation accuracy under high-rate charge/discharge conditions. In this work, an electrochemical model for lithium-ion batteries based on multi-particle hypothesis is developed. Two particles are employed to represent the electrode characteristics of the positive and negative electrodes, respectively. Through theoretical derivation, mathematical equations are established to describe various processes within the battery, including solid-phase diffusion, liquid-phase diffusion, reaction polarization, and ohmic polarization. In addition, a method for obtaining model parameters is proposed. Finally, the model is experimentally validated by using lithium iron phosphate and nickel-cobalt-manganese lithium-ion batteries under constant current conditions. The identified battery electrochemical model parameters are within reasonable accuracy as evidenced by the experimental validation results.