Hybrid energy management strategy for ultra-capacitor/battery electric vehicles considering battery degradation

This manuscript presents a hybrid approach for an energy management system in electric vehicles (EVs) with hybrid energy storage, taking into account battery degradation. The proposed approach, named the WSO–DMO method, combines the White Shark Optimizer (WSO) and Dwarf Mongoose Optimizer (DMO) techniques. The main objective is to optimize power distribution between the ultra-capacitor and battery minimizing battery degradation while maintaining vehicle power output. To address battery degradation, a high charge cutoff is implemented to reduce the depth of discharge, while ultra-capacitors are utilized for high energy density discharge. The parallel hybrid energy storage EV consists of a motor, controller, and hybrid energy storage system like a DC/DC converter and battery, ultra-capacitor. The energy management analysis is crucial for the hybrid electric vehicle model, which includes a, motor model, longitudinal dynamic model, driver model, and HESS model. The accelerator and brake pedals are adjusted using a proportional–integral derivative controller, which compares the goal speed with the actual speed. The performance of the proposed hybrid technique is evaluated using MATLAB and contrasted with the present technique. The results show that the hybrid technique efficiently mitigates battery degradation and improves the vehicle's range by 1–2% compared to a vehicle without an ultra-capacitor.