Model Predictive Battery Health‐Aware DC Fast Charging Control

ABSTRACT The paper presents a model‐based control strategy for direct current fast charging (DCFC) in electric vehicles (EVs). A model predictive control (MPC) framework is developed to generate real‐time charging profiles that balance fast charge time with battery health preservation. Central to this approach is a control‐oriented electrochemical battery model designed to capture the cell dynamics under high‐current charging conditions typical of DCFC events. The proposed closed‐loop control formulation incorporates internal battery states, such as anode potential, that are closely linked to degradation mechanisms and state‐of‐health (SoH). These internal variables are used within a real‐time optimization framework to minimize charging time while enforcing constraints that mitigate long‐term degradation. An integrated DCFC management strategy is also highlighted, combining a baseline charging profile with the proposed MPC‐based supervisory control, enabling practical deployment within embedded automotive control architectures