Optimizing Fuel Economy in Hybrid Electric Vehicles Using the Equivalent Consumption Minimization Strategy Based on the Arithmetic Optimization Algorithm

Houssam Eddine Ghadbane () and Ahmed F. Mohamed
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Houssam Eddine Ghadbane: Département d’Electrotechnique et Automatique, Laboratoire de Génie Électrique de Guelma (LGEG), Université 8 Mai 1945, Guelma 24000, Algeria
Ahmed F. Mohamed: Industrial Engineering Department, College of Engineering and Architecture, Umm Al-Qura University, P.O. Box 5555, Makkah 21955, Saudi Arabia

Mathematics, 2025, vol. 13, issue 9, 1-18

Abstract: Due to their improved performance and advantages for the environment, fuel cell hybrid electric cars, or FCEVs, have garnered a lot of attention. Establishing an energy management strategy (EMS) for fuel cell electric vehicles (FCEVs) is essential for optimizing power distribution among various energy sources. This method addresses concerns regarding hydrogen utilization and efficiency. The Arithmetic Optimization Algorithm is employed in the proposed energy management system to enhance the strategy of maximizing external energy, leading to decreased hydrogen consumption and increased system efficiency. The performance of the proposed EMS is evaluated using the Federal Test Procedure (FTP-75) to replicate city driving situations and is compared with existing algorithms through a comparison co-simulation. The co-simulation findings indicate that the suggested EMS surpasses current approaches in reducing fuel consumption, potentially decreasing it by 59.28%. The proposed energy management strategy demonstrates an 8.43% improvement in system efficiency. This enhancement may reduce dependence on fossil fuels and mitigate the adverse environmental effects associated with automobile emissions. To assess the feasibility and effectiveness of the proposed EMS, the system is tested within a Processor-in-the-Loop (PIL) co-simulation environment using the C2000 launchxl-f28379d Digital Signal Processing (DSP) board.

Keywords: hybrid electric vehicles; energy management strategy; metaheuristic algorithms; online optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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