PSO-Based Energy Management Strategy for Electric Vehicles Integrating Batteries and Supercapacitors

Abstract

This paper presents an advanced energy management system (EMS) for electric vehicles (EVs) equipped with a hybrid energy storage system (HESS) that integrates a lithium-ion battery and supercapacitors. The energy management problem is formulated as a constrained multiobjective optimization problem. It includes both equality and inequality constraints. The optimization process aims to achieve three key objectives: ensuring that the battery meets the average energy demand of the vehicle, maintaining the health of the battery, and enforcing a smooth power profile for the battery with lower dynamic variations compared to the supercapacitor, which handles rapid power fluctuations. The strategy determines the optimal power distribution offline based on predefined driving profiles, while minimizing energy loss and thermal stress on the storage components. The Particle Swarm Optimization (PSO) algorithm is employed to achieve efficient power allocation and energy sharing. The effectiveness of the proposed approach is demonstrated by simulating a driving cycle lasting 400 seconds. The results show that the battery supplies 90.1% of the total power demand, while the supercapacitor contributes 9.9%, and the mean absolute error (MAE) between the battery and the mean demand power is 19%. This optimized strategy improves the system efficiency, minimizes the dynamic variation of the battery power, and extends the battery life, highlighting the effectiveness of the proposed EMS.