Fuel cell electric vehicles equipped with energy storage system for energy management: A hybrid JS-RSA approach

Energy management strategy (EMS) is crucial in the growth of fuel cell (FC) electric vehicles (EVs) with different energy storage systems (ESS). This manuscript proposes a hybrid technique for the energy management (EM) of a battery-based FC electric vehicle (FCEV) system. The proposed hybrid method is a combination of a jellyfish search optimizer (JSO) and a Reptile Search Algorithm (RSA). Hence, known as the JSO-RSA method. The main objective of the proposed method is the operational mode control, state machine control, dynamic power factor, and equivalent consumption minimization. The novelty of the paper is charging battery with the least amount of hydrogen per joule. The proposed method is done in MATLAB and is examined their performance with existing methods, like Salp Swarm Algorithm (SSA), Seagull Optimization Algorithm (SOA), and Color Harmony Algorithm (CHA). The proposed method shows a high efficiency of 90.2 % and a low operating cost of 568 $ compared with other existing methods.

Automated summary

This manuscript proposes a hybrid technique, called JSO-RSA method, for the energy management of a battery-based FC electric vehicle system. The method aims to minimize the equivalent consumption by controlling the operational mode, state machine, and dynamic power factor. The proposed method demonstrates high efficiency (90.2%) and low operating cost ($568) compared to existing methods.