Design and simulation of a real-time implementable energy-efficient model-predictive cruise controller for electric vehicles. Issue 2 (February 2015)

• Record Type: Journal Article
• Authors: Schwickart, T.; Voos, H.; Hadji-Minaglou, J.-R.; Darouach, M.; Rosich, A.
• Is Part Of: Journal of the Franklin Institute. Volume 352:Issue 2(2015:Feb.)
• Page Start: 603
• Page End: 625
• Publication Date: 2015-02
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2014.07.001
• Languages: English
• ISSNs: 0016-0032

Abstract

<abstract abstract-type="author" id="ab0005"> <title id="sect0005">Abstract</title> <sec> <p id="sp0080">This paper presents the design of a novel energy-efficient model-predictive cruise controller for electric vehicles as well a simulation model of the longitudinal vehicle dynamics and its energy consumption. Both, the controller and the dynamic model are designed to meet the properties of a series-production electric vehicle whose characteristics are identified and verified by measurements. 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. Considering the nonlinearities is essential for a proper prediction of the system states over the prediction horizon to achieve the desired energy-saving behaviour. In this work, the vehicle motion equation is reformulated in terms of the kinetic energy of the moving vehicle which leads to a linear differential equation without loss of information. The energy consumption is modeled implicitly by exploiting the special form of the optimisation problem. The reformulations finally lead to 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. Simulation results of the MPC controller and the simulation model in closed-loop operation finally provide a proof of concept.</p> </sec> </abstract>