Parameter sensitivity analysis and parameter identifiability analysis of electrochemical model under wide discharge rate

Abstract

The increasing demand for electric vehicles, grid stability, and high pulse power loads has driven the development of new high-power lithium-ion batteries (LIBs) that are capable of discharging at extremely high C-rates. Accurately identifying physical parameters in electrochemical models is crucial for the rational design and optimization of these new high-power LIBs. Since high-rate discharge can significantly reduce discharge time, it is essential to investigate the impact of double-layer capacitors. In this study, we present a P2D coupled double-layer capacitor model and conduct a comprehensive analysis of the sensitivity of all 32 physical parameters to terminal voltage during constant current discharge over a wide rate range of 1C to 40C. This is the first time such an analysis has been performed. We classified the parameters into three groups based on their normalized parameter sensitivity index: high sensitivity, sensitive, and insensitive, and identified 14 physical parameters that can be recognized under constant current discharge conditions. We used a genetic algorithm to identify these parameters, achieving a root mean square error below 13 mV and an average absolute error below 10 mV between the simulation results of the model and the experimental data. This work provides guidance and inspiration for the parameter identification of high-power LIBs electrochemical models.