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Appl. Sci. 2018, 8(2), 218; doi:10.3390/app8020218

Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming

Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
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Received: 13 December 2017 / Revised: 26 January 2018 / Accepted: 28 January 2018 / Published: 31 January 2018
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Abstract

This paper proposes a comparison study of energy management methods for a parallel plug-in hybrid electric vehicle (PHEV). Based on detailed analysis of the vehicle driveline, quadratic convex functions are presented to describe the nonlinear relationship between engine fuel-rate and battery charging power at different vehicle speed and driveline power demand. The engine-on power threshold is estimated by the simulated annealing (SA) algorithm, and the battery power command is achieved by convex optimization with target of improving fuel economy, compared with the dynamic programming (DP) based method and the charging depleting–charging sustaining (CD/CS) method. In addition, the proposed control methods are discussed at different initial battery state of charge (SOC) values to extend the application. Simulation results validate that the proposed strategy based on convex optimization can save the fuel consumption and reduce the computation burden obviously. View Full-Text
Keywords: battery power; convex optimization; dynamic programming; engine-on power; plug-in hybrid electric vehicle; simulated annealing battery power; convex optimization; dynamic programming; engine-on power; plug-in hybrid electric vehicle; simulated annealing
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Xiao, R.; Liu, B.; Shen, J.; Guo, N.; Yan, W.; Chen, Z. Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming. Appl. Sci. 2018, 8, 218.

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