Volume 15, Issue 4 (12-2025)                   ASE 2025, 15(4): 4871-4886 | Back to browse issues page


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Montazeri M, Zakizadeh M A, Mostashiri A. Durability-Driven Energy Management for Fuel Cell Hybrid EVs: Multi-Scenario Optimization Across Different Traffic and Driving Cycles. ASE 2025; 15 (4) :4871-4886
URL: http://ase.iust.ac.ir/article-1-719-en.html
Abstract:   (114 Views)
The rising demand for sustainable transportation has intensified research on Fuel Cell Hybrid Electric Vehicles (FCHEVs). Integrating fuel cells with lithium-ion batteries provides a pathway to enhance energy efficiency and driving performance, but ensuring the durability of both components under real operating conditions remains a critical challenge. This work proposes an integrated framework to improve FCHEV performance and lifetime through combined modeling, degradation analysis, and optimized energy management. Dynamic vehicle simulations were conducted using the ADVISOR platform under both the Urban Dynamometer Driving Schedule (UDDS) and a real-world cycle based on Tehran traffic data. Degradation models were implemented to capture platinum dissolution in the Proton Exchange Membrane Fuel Cell (PEMFC) and capacity loss in the lithium-ion battery, incorporating the effects of state of charge, temperature, and current rate. An energy management strategy was developed using a Fuzzy Logic Controller (FLC) for fuel cell–battery power distribution, which was further refined with a Genetic Algorithm (GA). The optimization objectives included reducing hydrogen consumption and extending component lifetimes. The GA-optimized FLC extended PEMFC lifetime by 50.6% Tehran and 12.9%  UDDS and reduced battery capacity fade by 10% and 4.9%, respectively. While direct hydrogen consumption increased in Tehran due to more aggressive regenerative-energy routing to the battery, the Equivalent Fuel Consumption (EFC) decreased from 971.32 → 937.21 g/100 km (Tehran) and 794.41 → 782.24 g/100 km (UDDS), reflecting a net efficiency gain once SOC restoration is accounted for.
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Type of Study: Research | Subject: Control

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