A fast model-predictive speed controller for minimised charge consumption of electric vehicles

International audienceThis paper presents the design of a real-time implementable energy-efficient model-predictive cruise controller for electric vehicles including the driving speed reference generation. The controller is designed to meet the properties of a series-production electric vehicle whose characteristics are identified and validated by measurements. The predictive eco-cruise controller aims at finding the best compromise between speed-reference tracking and energy consumption of the vehicle using an underlying dynamic model of the vehicle motion and charge consumption. The originally non-linear motion model is transformed into a linear model mainly by using a coordinate transform. To obtain a piecewise linear approximation of the charge consumption map, the measured characteristics are approximated by a convex piecewise linear function represented as the maximum of a set of linear constraint functions. 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 closed-loop operation finally illustrate the effectiveness of the approach