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Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook

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School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China
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Department of Mechanical Engineering, Tarsus University, Tarsus, Mersin 33400, Turkey
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School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
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Author to whom correspondence should be addressed.
Energies 2020, 13(13), 3352; https://doi.org/10.3390/en13133352
Received: 29 April 2020 / Revised: 25 June 2020 / Accepted: 28 June 2020 / Published: 30 June 2020
(This article belongs to the Special Issue Intelligent Transportation Systems for Electric Vehicles)
Hybrid Electric Vehicles (HEVs) have been proven to be a promising solution to environmental pollution and fuel savings. The benefit of the solution is generally realized as the amount of fuel consumption saved, which by itself represents a challenge to develop the right energy management strategies (EMSs) for HEVs. Moreover, meeting the design requirements are essential for optimal power distribution at the price of conflicting objectives. To this end, a significant number of EMSs have been proposed in the literature, which require a categorization method to better classify the design and control contributions, with an emphasis on fuel economy, providing power demand, and real-time applicability. The presented review targets two main headlines: (a) offline EMSs wherein global optimization-based EMSs and rule-based EMSs are presented; and (b) online EMSs, under which instantaneous optimization-based EMSs, predictive EMSs, and learning-based EMSs are put forward. Numerous methods are introduced, given the main focus on the presented scheme, and the basic principle of each approach is elaborated and compared along with its advantages and disadvantages in all aspects. In this sequel, a comprehensive literature review is provided. Finally, research gaps requiring more attention are identified and future important trends are discussed from different perspectives. The main contributions of this work are twofold. Firstly, state-of-the-art methods are introduced under a unified framework for the first time, with an extensive overview of existing EMSs for HEVs. Secondly, this paper aims to guide researchers and scholars to better choose the right EMS method to fill in the gaps for the development of future-generation HEVs. View Full-Text
Keywords: Hybrid Electric Vehicles (HEVs); energy management strategies (EMSs); driving cycle prediction; optimization Hybrid Electric Vehicles (HEVs); energy management strategies (EMSs); driving cycle prediction; optimization
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Zhang, F.; Wang, L.; Coskun, S.; Pang, H.; Cui, Y.; Xi, J. Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook. Energies 2020, 13, 3352.

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