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Vol: 60(74) No: 1 / March 2015 Three-level Time-Suboptimal Predictive Control of Electric Vehicles for High-Speed Manoeuvres György Max Department of Control Engineering and Information Technology, Budapest University of Technology and Economics, Faculty of Electrical Engineering, H-1117 Budapest, Magyar tudósok krt. 2, Hungary, e-mail: max@iit.bme.hu Béla Lantos Department of Control Engineering and Information Technology, Budapest University of Technology and Economics, Faculty of Electrical Engineering, H-1117 Budapest, Magyar tudósok krt. 2, Hungary, e-mail: lantos@iit.bme.hu Keywords: 4WD electric vehicle, 2WD time-suboptimal control, Optimal force distribution, 4WD model predictive control Abstract In this paper a three-level vehicle control system is presented for the approximately time optimal control of four in-wheel-driven (4WD) electric cars in a path under state and input constraints with initial perturbations. The path is divided into sections allowing that path information for the actual section can vary in real time based on sensor fusion. For each section at top-level, a separate optimum control problem is solved in a receding horizon predictive control (RHPC) fashion using the single-track model (2WD) of the vehicle. The problem is given as a dynamic nonlinear optimal control problem (DNOCP) and solved by reformulating it to a static nonlinear program (NLP) using discretization and direct multiple shooting methods. At medium-level, a novel method is presented to convert the RHPC optimal solution to the optimal control of 4WD cars. The conversion assures similar motion of the CoG points of both models and produces optimal distribution of the longitudinal wheel forces. For closed loop control of 4WD vehicle a discrete time low-level model predictive control (MPC) is proposed which uses the high-level reference signals and the medium-level distributed wheel forces and optimizes the perturbations analytically for initial state errors. Numerical results illustrate the effectiveness of each subtask solution for high-speed aggressive maneuvers. References [1] G. Max and B. Lantos, “Nonlinear Moving Horizon Predictive Control of Ground Vehicles,” in Proceedings of IEEE 15th International Symposium on Computational Intelligence and Informatics CINTI 2014, Budapest, Hungary, 2014, pp. 421–426. [2] Max, G.; Lantos, B., “Time-suboptimal predictive control of four-in-wheel driven electric vehicles,” in Proceedings of IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics SACI 2015, Timisoara, Romania, 2015, pp. 375–380. [3] K. Sawase and Y. 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