An electromechanical coupling model-based state of charge estimation method for lithium-ion pouch battery modules

Abstract

The performance of state of charge (SOC) estimation can be improved by using multi-dimensional signals. However, conventional battery models developed for SOC estimation have difficulties in simulating the coupling relationship between the mechanical and electrical characteristics. In this paper, an electromechanical coupling model (EmCM) of a lithium-ion pouch battery module is established for SOC estimation in real-time. To achieve the closed-loop SOC estimation based on force signal feedback, the stack pressure is chosen as the model output. The current and SOC are set as the model input and a state variable, respectively. On this basis, a novel SOC estimation method through current and stack pressure is proposed. The model parameters are identified by a genetic algorithm, and SOC estimation is performed using the Extended Kalman filter algorithm. The experiment results indicate that the proposed EmCM can depict the stack pressure variations with high accuracy. The SOC estimation error can be controlled within ±2.8% for both Li [NiCoMn]O2 cells and LiFePO4 cells.