Improved State of Charge Estimation of Lithium-ion Battery cells

Lithium-ion battery cells are widely used in a variety of applications. An accurate online estimation technique to determine the State of Charge (SOC) can improve the safety of Lithium-ion cells, their performance and life cycle. However, nonlinear cell models bring many estimation challenges. In this work, an estimation technique which combines the Multiple Model Adaptive Estimation (MMAE) and Extended Kalman filter (EKF) is introduced. The combination of these two techniques improves the SOC estimation accuracy and avoids each technique’s drawback. Simulation results for a LiFePO4 Lithium-ion cell demonstrate that this combined technique provides smaller estimation error compared to either MMAE or EKF alone.