NDLI: Rule-Based Control Strategy With Novel Parameters Optimization Using NSGA-II for Power-Split PHEV Operation Cost Minimization

Content Provider	IEEE Xplore Digital Library
Author	Yanhe Li Xiaomin Lu Kar, N.C.
Copyright Year	1967
Abstract	One of the major considerations in the automotive industry is the reduction of hybrid electric vehicle fuel consumption and operation cost. This paper is the first to use the nondominated sorting genetic algorithm-II (NSGA-II) for power-split plug-in hybrid electric vehicle (PHEV) applications. The NSGA-II, one of the most efficient multiobjective genetic algorithms (MOGAs), simultaneously optimized operation cost, including gasoline and electricity consumption. The Pareto optimal solutions are discussed for the parameter calibrations of the rule-based control strategy as a useful guide in PHEV development, particularly in the earlier phases. The optimized operation cost at the different power-split device (PSD) gear ratios is used to determine the ideal PSD gear ratio to further minimize the operation cost. To validate the proposed strategy, dynamic PSD and powertrain models of PHEV are developed in the numerical analysis. The two typically different driving cycles, namely, the Urban Dynamometer Driving Schedule (UDDS) and the Highway Fuel Economic Drive Schedule (HWFET), with different numbers of driving cycles, are used for control strategy optimization.
Sponsorship	IEEE Vehicular Technology Society
Starting Page	3051
Ending Page	3061
Page Count	11
File Size	1974022
File Format	PDF
ISSN	00189545
Volume Number	63
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gears Optimization Fuels Engines Torque Hybrid electric vehicles power split Multiobjective genetic algorithm (MOGA) nondominated sorting genetic algorithm-II (NSGA-II) operation cost plug-in hybrid electric vehicle (PHEV)
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Automotive Engineering Computer Networks and Communications Electrical and Electronic Engineering Aerospace Engineering

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