Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations
Computer circuits; Dynamic programming; Energy efficiency; Energy management; Fossil fuel deposits; Fossil fuels; Fuel cells; Fuel storage; Fuzzy logic; Genetic algorithms; Global warming; Greenhouse gases; Hybrid vehicles; Internal combustion engines; Linear programming; Logic Synthesis; Optimizati...
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2023
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my.uniten.dspace-236542023-05-29T14:50:47Z Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations Sulaiman N. Hannan M.A. Mohamed A. Ker P.J. Majlan E.H. Wan Daud W.R. 57188755994 7103014445 57195440511 37461740800 26030028700 35547717400 Computer circuits; Dynamic programming; Energy efficiency; Energy management; Fossil fuel deposits; Fossil fuels; Fuel cells; Fuel storage; Fuzzy logic; Genetic algorithms; Global warming; Greenhouse gases; Hybrid vehicles; Internal combustion engines; Linear programming; Logic Synthesis; Optimization; Particle swarm optimization (PSO); Supercapacitor; Battery; Energy management systems (EMS); Fuel cell hybrid electric vehicles; Hybrid-electric vehicle technologies; Internal combustion engine vehicles; Optimization algorithms; Optimization techniques; Pontryagin's minimum principles; Energy management systems; combustion; electric vehicle; energy storage; equipment component; fossil fuel; fuel cell; fuel consumption; global warming; greenhouse gas; hydrogen; optimization; performance assessment Hybrid electric vehicle technologies emerge mainly because of the instability in fossil fuel prices, resources and the terrible impact of global warming. As most transport systems use fossil fuel and emit greenhouse gases, many researchers have studied the potential of fuel-cell hybrid electric vehicles (FCHEVs). FCHEVs are vehicles with zero greenhouse gas emission because they only depend on hydrogen. Numerous studies have proven that fuel cells with energy storage elements can provide sufficient energy required by FCHEVs. However, end users demand FCHEVs that are not only efficient in delivering the energy required but can also optimize hydrogen consumption and prolong battery lifetime to compete with current internal combustion engine vehicles. Therefore, advanced optimization algorithms for an FCHEV energy management system (EMS) must be developed to improve the performance efficiency of FCHEVs. This paper presents a critical review of the different types of FCHEV EMSs and their optimization algorithms to solve existing limitations and enhance the performance of future FCHEVs. Consequently, a comprehensive review on the major categories of FCHEV EMSs, such as proportional�integral�derivative controller, operational or state mode, rule-based or fuzzy logic, and equivalent consumption minimization strategies, are explained. This paper also describes optimization techniques such as linear programming, dynamic programming, Pontryagin's minimum principle, genetic algorithm, particle swarm optimization and rule-based logic optimization for the EMSs of FCHEVs. Furthermore, it focuses on the various factors and challenges of existing optimization algorithms, hydrogen fuel source, environment and safety, and economical and societal concerns, as well as provides recommendations for designing capable and efficient EMSs for FCHEVs. All the highlighted insights of this review will hopefully lead to increasing efforts toward the development of an advanced optimization algorithm for future FCHEV EMSs. � 2018 Final 2023-05-29T06:50:47Z 2023-05-29T06:50:47Z 2018 Review 10.1016/j.apenergy.2018.07.087 2-s2.0-85050200137 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050200137&doi=10.1016%2fj.apenergy.2018.07.087&partnerID=40&md5=7daeac506352ad99a90bcccc561ebd85 https://irepository.uniten.edu.my/handle/123456789/23654 228 2061 2079 Elsevier Ltd Scopus |
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Computer circuits; Dynamic programming; Energy efficiency; Energy management; Fossil fuel deposits; Fossil fuels; Fuel cells; Fuel storage; Fuzzy logic; Genetic algorithms; Global warming; Greenhouse gases; Hybrid vehicles; Internal combustion engines; Linear programming; Logic Synthesis; Optimization; Particle swarm optimization (PSO); Supercapacitor; Battery; Energy management systems (EMS); Fuel cell hybrid electric vehicles; Hybrid-electric vehicle technologies; Internal combustion engine vehicles; Optimization algorithms; Optimization techniques; Pontryagin's minimum principles; Energy management systems; combustion; electric vehicle; energy storage; equipment component; fossil fuel; fuel cell; fuel consumption; global warming; greenhouse gas; hydrogen; optimization; performance assessment |
| author2 |
57188755994 |
| author_facet |
57188755994 Sulaiman N. Hannan M.A. Mohamed A. Ker P.J. Majlan E.H. Wan Daud W.R. |
| format |
Review |
| author |
Sulaiman N. Hannan M.A. Mohamed A. Ker P.J. Majlan E.H. Wan Daud W.R. |
| spellingShingle |
Sulaiman N. Hannan M.A. Mohamed A. Ker P.J. Majlan E.H. Wan Daud W.R. Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations |
| author_sort |
Sulaiman N. |
| title |
Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations |
| title_short |
Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations |
| title_full |
Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations |
| title_fullStr |
Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations |
| title_full_unstemmed |
Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations |
| title_sort |
optimization of energy management system for fuel-cell hybrid electric vehicles: issues and recommendations |
| publisher |
Elsevier Ltd |
| publishDate |
2023 |
| _version_ |
1806426247271546880 |
| score |
13.222552 |