The DOI matches its Crossref record; 155 of the 155 references it cites were found in a registry or an index.
Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies
Open accessAbstract
Hybrid and electric vehicles have been demonstrated as auspicious solutions for ensuring improvements in fuel saving and emission reductions. From the system design perspective, there are numerous indicators affecting the performance of such vehicles, in which the powertrain type, component configuration, and energy management strategy (EMS) play a key role. Achieving an energy-efficient powertrain requires tackling several conflicting control objectives such as the drivability, fuel economy, reduced emissions, and battery state of charge preservation, which make the EMS the most crucial aspect of powertrain system design. Accordingly, in the present study, various powertrain systems and topologies of (plug-in) hybrid electric vehicles and full-electric vehicles are assessed. In addition, EMSs as applied in the literature are systematically surveyed for a qualitative investigation, classification, and comparison of existing approaches in terms of the principles, advantages, and drawbacks through a comprehensive review. Furthermore, potential challenges considering the gaps in research are addressed, and directives paving the way toward further development of powertrains and EMSs in all respects are thoroughly provided.
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Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
GSA: A Gravitational Search Algorithm
Rashedi, E., Nezamabadi-pour, H., & Saryazdi, S. (2009) · Information Sciences · doi:10.1016/j.ins.2009.03.004 · Cited by 7,358
Cuckoo Search via Lévy flights
Yang, X.-S., & Deb, S. (2009) · 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC) · doi:10.1109/nabic.2009.5393690 · Cited by 6,185
A New Metaheuristic Bat-Inspired Algorithm
Yang, X.-S. (2010) · Studies in Computational Intelligence · doi:10.1007/978-3-642-12538-6_6 · Cited by 4,905
Nature-Inspired Metaheuristic Algorithms
Yang, X. (2008) · Medical Entomology and Zoology · Cited by 4,556
Lee, J. H., Kaisare, N. S., & García, C. E. (2007) · Springer eBooks · doi:10.1002/9781394333325.fmatter · Cited by 3,766
Firefly algorithm, stochastic test functions and design optimisation
Yang, X. S. (2010) · International Journal of Bio-Inspired Computation · doi:10.1504/ijbic.2010.032124 · Cited by 2,729
13 Flower Pollination Algorithm for Global OptimizationPreprint
Yang, X. (2012) · Cited by 2,272
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Elalfy, D. A., Gouda, E., Kotb, M. F., Bureš, V., & Sedhom, B. E. (2024) · Energy Strategy Reviews · doi:10.1016/j.esr.2024.101482 · Cited by 587
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Van Mierlo, J., Berecibar, M., El Baghdadi, M., De Cauwer, C., Messagie, M., Coosemans, T., Jacobs, V., & Hegazy, O. (2021) · World Electric Vehicle Journal · doi:10.3390/wevj12010020 · Cited by 149
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Metadata
- Authors
- Tran, D.-D., Vafaeipour, M., El Baghdadi, M., Barrero, R., Van Mierlo, J., & Hegazy, O.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2020-03
- Volume
- 119
- Pages
- 109596
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2990975667
- Cited by
- 565
- References
- 155
- FWCI
- 23.81
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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