A Stepwise Parameter Identification Method for an Electrochemical–Thermal Coupled Model of Lithium-Ion Batteries Based on Global Sensitivity Analysis

The pseudo-two-dimensional (P2D) model provides a physics-based description of lithium-ion battery behavior, but its numerous strongly coupled electrochemical and thermal parameters make simultaneous voltage and temperature prediction challenging. This study proposes a multi-stage parameter identification method for an electrochemical–thermal coupled P2D model. Sobol global sensitivity analysis with Saltelli sampling is first used to quantify the effects of model parameters on voltage and temperature responses under different operating conditions. Based on the sensitivity results, a stage-wise multi-objective identification strategy is developed, with adaptive weights determined from normalized sensitivity indices. A hybrid Whale Optimization Algorithm–Differential Evolution (WOA–DE) method is then employed for parameter optimization. Compared with the original model, voltage prediction errors are reduced by 25.68%, 42.13%, and 47.48% under 0.5 C, HPPC, and DST conditions, respectively, while temperature errors decrease by 37.97%, 45.16%, and 30.96%. Under dynamic conditions, the model achieves RMSEs of 10.21 mV for voltage and 0.115 °C for temperature. The results demonstrate improved prediction accuracy and robustness for coupled voltage–temperature responses.