DocumentCode
115061
Title
A dual decomposition approach to complete energy management for a heavy-duty vehicle
Author
Romijn, T.C.J. ; Donkers, M.C.F. ; Kessels, J.T.B.A. ; Weiland, S.
Author_Institution
Dept. of Electr. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands
fYear
2014
fDate
15-17 Dec. 2014
Firstpage
3304
Lastpage
3309
Abstract
In this paper, we will propose a scalable and systematic procedure to solve the complete vehicle energy management problem, which requires solving a large-scale optimization problem subject to a large number of constraints. We consider a case study of a hybrid heavy-duty vehicle, equipped with an electric machine, a high-voltage battery pack and a refrigerated semi-trailer. The procedure is based on the application of the dual decomposition to the energy management problem. This dual decomposition allows the large-scale optimization problem to be solved by solving several smaller optimization problems, which gives favourable scalability properties. To efficiently decompose the problem, we will decompose the objective function of the optimization problem, being the fuel consumption, into a sum of functions each representing `energy losses´. Using the case study, we will compare the novel methodology based on the dual decomposition with dynamic programming, showing the benefits in terms of computational efficiency of the novel solution strategy. Moreover, we will show the benefits in terms of fuel consumption of complete vehicle energy management.
Keywords
battery powered vehicles; dynamic programming; hybrid electric vehicles; road vehicles; computational efficiency; dual decomposition approach; dynamic programming; electric machine; energy losses; fuel consumption; high-voltage battery pack; hybrid heavy-duty vehicle; large-scale optimization problem; refrigerated semitrailer; solution strategy; vehicle energy management problem; Batteries; Electric machines; Energy management; Engines; Fuels; Optimization; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location
Los Angeles, CA
Print_ISBN
978-1-4799-7746-8
Type
conf
DOI
10.1109/CDC.2014.7039900
Filename
7039900
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