Health-Aware Fast Charging for Lithium-ion Batteries: Model Predictive Control, Lithium Plating Detection, and Lifelong Parameter Updates

Traditional charging approaches for lithium-ion batteries (LIBs) face challenges in balancing charging speed, detrimental side reactions, and battery aging. In this study, a novel model-based health-aware optimal fast charging strategy for the lifespan of LIBs is proposed to tackle these issues. It incorporates a control framework with three levels of closed-loop control: (a) small loop for online model predictive control (MPC) charging control; (b) intermediate loop for lithium plating detection; and (c) large loop for model parameter updates. A new thermal-electric coupled decomposed electrode model (DEM) is deployed to accurately obtain two essential states (i.e., the anode potential and cell temperature) of the battery. This approach executes the superior current profile to reduce charging time while minimizing cell degradation based on the online MPC charge. Model parameters are updated once lithium plating is detected after fast charging of aged cells to renew the state of health. Both simulation and experimental results reveal the efficacy of the algorithm for new and aged LIBs. Moreover, this approach offers versatility for adaptation across other types of LIBs and real-world applications.