A real-time implementable model-predictive cruise controller for electric vehicles and energy-efficient driving

This paper presents a novel energy-efficient model-predictive cruise control formulation for electric vehicles. 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. 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 map is approximated by the maximum of a set of linear functions which is implicitly determined in 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 in closed-loop operation finally show the effectiveness of the approach.