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World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Articles in this Issue were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on mdpi.com as a courtesy and upon agreement with AVERE.
Open AccessArticle

Study on Power Management Strategy of HEV using Dynamic Programming

1
Department of Mechanical and Aerospace Engineering, Seoul National University, Daehak-dong, Gwanak-gu, Seoul 151-744, Korea
2
Department of Mechanical System Design Engineering, Seoul National University of Science and Technology, Gongrung2-dong, Nowon-gu, Seoul 139-743, Korea
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2016, 8(1), 274-280; https://doi.org/10.3390/wevj8010274
Published: 25 March 2016
PDF [857 KB, uploaded 14 May 2018]

Abstract

For hybrid electric vehicle, it is necessary to control power distribution among multiple power sources to improve fuel economy performance of vehicle. In this paper, power management strategy of hybrid electric vehicle using Dynamic programming is studied. Deterministic dynamic programming could present outstanding fuel economy, while its application as real time control of vehicle is limited. Thus, different kinds of power management strategy using dynamic programming are studied. Stochastic dynamic programming, artificial neural networks and rule-based power management strategy using results from dynamic programming are studied. Simulations using parallel type hybrid electric vehicle model are conducted. Simulation results including fuel economy performance on diverse driving cycles are compared and analysed.
Keywords: HEV(hybrid electric vehicle); optimization; power management; control system HEV(hybrid electric vehicle); optimization; power management; control system
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Lee, H.; Kang, C.; Park, Y.-I.; Cha, S.W. Study on Power Management Strategy of HEV using Dynamic Programming. World Electr. Veh. J. 2016, 8, 274-280.

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