Model Predictive Control based Optimal Charging for the Health Improvement in Lithium-ion Batteries

Abstract

Electric vehicles (EVs), consumer electronics, and other battery-operated applications extensively use lithium-ion batteries (LiBs). A constant current constant voltage (CCCV) charging profile is used in the majority of these applications as a standard charging procedure. However, this approach falls short in addressing LiB’s state of health (SoH), which is crucial for extending its lifespan. During the CC charging phase, the battery temperature may increase manifold beyond the safety levels if the charging current is relatively high. It may eventually deteriorate LiB’s overall SoH by accelerating the side reactions. In order to address the issues with CCCV, this paper proposes a model predictive control (MPC) based optimal charging procedure to improve the LiB’s SoH by monitoring its temperature rise and extending its overall runtime. Compared to CCCV charging, MPC-based charging reduces the capacity loss and solid-electrolyte interphase (SEI) layer’s resistance by 18.25% and 2.83%, respectively, which leads to an improvement of 2.34% in SoH value.