Model Predictive Control for Optimizes Battery Charging Process

The advantageous features of Li-ion batteries, such as their high energy density and minimal self-discharge, make them extensively employed in industrial environments. The increasing adoption of lithium-ion batteries in diverse industries emphasizes the critical need for optimal charging control. The charging process significantly impacts battery health, safety, and lifespan. To enhance charging efficiency and reduce charging time, various factors must be considered during the charging process, such as state of charge (SoC), charging current and temperature. Balancing the objectives of minimizing charging time and extending battery lifetime poses a challenge for charging operations. This study introduces the application of model predictive control (MPC) to minimize the charging time of lithium-ion batteries while taking into account electrochemical and thermal constraints. The proposed approach employs models to predict the battery's state of charge (SoC) and temperature under a sequence of future charging currents. MPC) algorithm is designed and verified to enable efficient charging of the battery while taking into account the battery's health status, with the objective of maximizing the charging speed.