Reference : A Novel Model-Predictive Cruise Controller for Electric Vehicles and Energy-Efficient...

	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/10993/17482

Title :	A Novel Model-Predictive Cruise Controller for Electric Vehicles and Energy-Efficient Driving
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)]
	Minaglou, Jean-Régis [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Darouach, Mohamed []
Publication date :	Jul-2014
Main document title :	A Novel Model-Predictive Cruise Controller for Electric Vehicles and Energy-Efficient Driving
Peer reviewed :	Yes
Audience :	International
Event name :	2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
Event date :	from 08-07-2014 to 11-07-2014
Keywords :	[en] Model-Predictive Control ; Eco-Driving / Eco-Cruise Control ; Optimal Control
Abstract :	[en] This paper presents a novel energy-efficient model-predictive cruise control formulation for electric vehicles. A predictive eco-cruise controller involves the minimisation of a compromise between terms related to driving speed and energy consumption which are in general both described by nonlinear differential equations. In this work, a coordinate transformation is used which leads to a linear differential motion equation without loss of information. The energy consumption is modeled by the maximum of a set of linear functions which is determined implicitly by the optimisation problem and thus leads to a piecewise linear model. The reformulations finally result in a model-predictive control approach with quadratic cost function, linear prediction model and linear constraints that corresponds to a piecewise linear system behaviour and allows a fast real-time implementation with guaranteed convergence. The controller and the underlying dynamic model are designed to meet the properties of a series-production electric vehicle whose characteristics are identified by measurements. Simulation results of the MPC controller and the simulation model in closed-loop operation finally provide a proof of concept.
Research centres :	Interdisciplinary Centre for Security, Reliability and Trust
Permalink :	http://hdl.handle.net/10993/17482

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