Reference : An Efficient Nonlinear Model-Predictive Eco-Cruise Control for Electric Vehicles

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/5679

Title :	An Efficient Nonlinear Model-Predictive Eco-Cruise Control for Electric Vehicles
Language :	English
Author, co-author :	Schwickart, Tim Klemens [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Voos, Holger [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit > ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)]
	Hadji-Minaglou, Jean-Régis [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Darouach, Mohamed [Université de Lorraine > CRAN UMR-CNRS 7039]
Publication date :	Jul-2013
Main document title :	11th IEEE International Conference on Industrial Informatics, Bochum, Germany, 29-31 July 2013
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	11th IEEE International Conference on Industrial Informatics
Event date :	from 29-07-2013 to 31-07-2013
Event organizer :	Ruhr Universität Bochum
Event place (city) :	Bochum
Event country :	Germany
Keywords :	[en] Driver Assistant Systems ; Optimal Control ; Automotive Control Systems
Abstract :	[en] A nonlinear problem formulation of an energy-saving model-predictive eco-cruise controller for electric vehicles is presented. With regard to the intended application in real-world tests, the model has to include the specific properties of a serial electric vehicle such as energy-recovery and a discontinuous accelerator input giving rise to a binary control variable. These specific features and the nonlinearity of the system dynamics make it a challenging task to formulate the optimisation problem in a way that allows a fast computation in real-time application. The challenges are addressed by using a model of the vehicle dynamics that is formulated in terms of the vehicle position instead of time and by considering the kinetic energy instead of the velocity. Furthermore, various constraints on the input and state variables are introduced for a realistic representation of the vehicle characteristics. A special focus is put on the treatment of a binary input variable in the optimisation. Here, in order to avoid a mixed-integer formulation of the problem, a continuous variable is introduced which is forced to take only discrete values by a penalty term. Finally, first simulation results underline the feasibility of this control approach.
Research centres :	Interdisciplinary Centre for Security Reliability and Trust
Name of the research project :	Eco-Driver Assistance System for Electric Vehicles
Target :	Researchers ; Professionals ; General public
Permalink :	http://hdl.handle.net/10993/5679

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