A comprehensive review of energy management optimization strategies for fuel cell passenger vehicle |
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| Affiliation: | 1. School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, 100044, PR China;2. Suzhou Tsing-standard Automotive Technology Co.,LTD, Suzhou, Jiangsu, 215200, PR China;1. Institute of Geotechnical Engineering, State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi''an University of Technology, Xi''an, 710048, China;2. School of Resources and Safety Engineering, China University of Mining and Technology, Beijing, 100083, China;1. State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing, 400044, China;2. Sir William Wright Technology Center, Queen’s University Belfast, Belfast, BT9 5BS, United Kingdom;3. Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, 650500, China;4. School of Engineering and Materials Science, Queen Mary University of London, London, E1 4NS, United Kingdom;5. Key Laboratory of Advanced Manufacture Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing, 400054, China |
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| Abstract: | With the gradual maturity of fuel cell vehicle technology, it gives a better opportunity for the application of passenger vehicles. In this paper, the energy management optimization strategies of fuel cell passenger vehicle (FCPV) are summarized for the first time. Initially, in this review, the topological configurations of FCPV are classified systematically. The optimization objectives, energy consumption and fuel cell life, are proposed for FCPV. Then the energy management strategies (EMSs) are illustrated and analysed based on the optimization objectives above. In terms of the complex and changeable characteristics of FCPV driving conditions, the latest FCPV EMSs which depend on driving information prediction technologies are discussed and summarized. The purpose of this paper is providing references for the development of new generation FCPV energy management optimization strategies. |
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| Keywords: | FCPV EMS Multi-objective optimization Fuel cell lifetime Fuel consumption Driving information prediction |
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