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
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.
Share and Cite
MDPI and ACS Style
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. https://doi.org/10.3390/wevj8010274
AMA Style
Lee H, Kang C, Park Y-i, Cha SW. Study on Power Management Strategy of HEV using Dynamic Programming. World Electric Vehicle Journal. 2016; 8(1):274-280. https://doi.org/10.3390/wevj8010274
Chicago/Turabian StyleLee, Heeyun, Changbeom Kang, Yeong-il Park, and Suk Won Cha. 2016. "Study on Power Management Strategy of HEV using Dynamic Programming" World Electric Vehicle Journal 8, no. 1: 274-280. https://doi.org/10.3390/wevj8010274
