Reducing hydrogen consumption in hybrid electric vehicles using aquila optimization algorithm
BACKGROUND AND OBJECTIVES: Fuel cell hybrid electric vehicles have earned significant interest owing to their superior performance and ecological advantages. Implementing an energy management strategy to enhance the performance of fuel cell electric vehicles by optimizing the allocation of power amo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
GJESM Publisher
2025-04-01
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| Series: | Global Journal of Environmental Science and Management |
| Subjects: | |
| Online Access: | https://www.gjesm.net/article_722284_5c7d23fa77d77623b95a3e851806262e.pdf |
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| Summary: | BACKGROUND AND OBJECTIVES: Fuel cell hybrid electric vehicles have earned significant interest owing to their superior performance and ecological advantages. Implementing an energy management strategy to enhance the performance of fuel cell electric vehicles by optimizing the allocation of power among different energy sources is a crucial engineering problem. This approach considers issues such as hydrogen consumption and efficiency. The objectives of this study were: 1) Developing a state-of-the-art energy management system for fuel cell hybrid electric vehicles to maximize electrical efficiency, reduce fuel consumption, and achieve optimal power distribution. 2) Applying the Aquila Optimizer to the proposed system to enhance the external energy maximization strategy.METHODS: Metaheuristic optimization algorithms play a vital role in obtaining the best set of fuel cell electric vehicles’ parameters. The aquila optimization algorithm is one of the most recent and efficient algorithms. It was used in the proposed energy management strategy to optimize the approach of maximizing external energy, resulting in reduced hydrogen use and improved system efficiency. Applying the federal test procedure to simulate the conditions of city driving, the proposed energy management strategy performance was assessed and contrasted with that of eight competent algorithms through a comparative simulation.FINDINGS: The simulation findings illustrated that the suggested energy management strategy surpasses other currently available solutions resulting from competitive optimizers by reducing the consumption of fuel, with a considerable decrease of 52.26 percent. In addition, the suggested energy management technique exhibited a 3.08 percent enhancement in system efficiency.CONCLUSION: The proposed strategy showed outstanding results over the other methods. Furthermore, the enhancement in the energy management strategy has the potential to reduce the dependency on traditional fossil fuels and mitigate the adverse environmental consequences produced by the vehicle’s emissions. Accordingly, transitioning to a sustainable transportation system using renewable hydrogen production will significantly reduce the harmful impacts and support a cleaner and greener environment. |
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| ISSN: | 2383-3572 2383-3866 |