NDLI: A Power-Management Strategy for Multiple-Unit Railroad Vehicles

Content Provider	IEEE Xplore Digital Library
Author	Shaofeng Lu Hillmansen, S. Roberts, C.
Copyright Year	1967
Abstract	Improved fuel consumption and lower emissions are two of the key objectives for future transportation. Hybrid electric vehicles (HEVs), in which two or more power systems are combined, can meet these objectives through the capture and reuse of regenerated braking energy and through optimized use of the prime mover. However, more complicated power-management strategies are required for such vehicles. This paper explores the potential of applying to advanced power-management strategies for a diesel multiple-unit (DMU) train. These types of vehicles have multiple diesel engines that are commonly operated in a homogenous manner. This paper analyzes the potential energy savings that may be obtained through the independent operation of the engines. Two widely investigated power-management strategies that have been developed for HEVs have been applied to a typical DMU railroad vehicle. Dynamic programming (DP) strategies have been applied to the results produced by a single-train motion simulator to identify the optimal instant power distribution between the engines. An adaptive rule-based online strategy based on the optimization results from the DP solution is then proposed and realized using a nonlinear programming optimization algorithm. Both strategies indicate acceptable agreement and show a fuel cost reduction of around 7%, in comparison with the evenly split engine operation.
Sponsorship	IEEE Vehicular Technology Society
Starting Page	406
Ending Page	420
Page Count	15
File Size	1308985
File Format	PDF
ISSN	00189545
Volume Number	60
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Engines Vehicles Fuels Mathematical model Optimization Acceleration Power demand rule-based online strategy Dynamic programming (DP) energy-management strategy multiple-unit train nonlinear optimization
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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