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Energy Management in Plug-in Hybrid Electric Vehicles: Recent Progress and a Connected Vehicles Perspective
Open accessAbstract
Plug-in hybrid electric vehicles (PHEVs) offer an immediate solution for emissions reduction and fuel displacement within the current infrastructure. Targeting PHEV powertrain optimization, a plethora of energy management strategies (EMSs) have been proposed. Although these algorithms present various levels of complexity and accuracy, they find a limitation in terms of availability of future trip information, which generally prevents exploitation of the full PHEV potential in real-life cycles. This paper presents a comprehensive analysis of EMS evolution toward blended mode (BM) and optimal control, providing a thorough survey of the latest progress in optimization-based algorithms. This is performed in the context of connected vehicles and highlights certain contributions that intelligent transportation systems (ITSs), traffic information, and cloud computing can provide to enhance PHEV energy management. The study is culminated with an analysis of future trends in terms of optimization algorithm development, optimization criteria, PHEV integration in the smart grid, and vehicles as part of the fleet.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Bellman, R. E. (2010) · doi:10.1515/9781400835386 · Cited by 14,588
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Metadata
- Authors
- Martinez, C. M., Hu, X., Cao, D., Velenis, E., Gao, B., & Wellers, M.
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 2017-06
- Volume
- 66
- Issue
- 6
- Pages
- 4534-4549
- ISSN
- 0018-9545 (ISSN-L)
- 1939-9359
- OpenAlex
- W2466636338
- Cited by
- 717
- References
- 2
- FWCI
- 69.21
- Type
- journal article
- Language
- en
- Open access
- green
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- Martinez, C. M., Hu, X., Cao, D., Velenis, E., Gao, B., & Wellers, M. (2017). Energy Management in Plug-in Hybrid Electric Vehicles: Recent Progress and a Connected Vehicles Perspective. IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/tvt.2016.2582721
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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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