An integrated control strategy of active suspension and in-wheel motor control for ride comfort optimization

The dynamics of a vehicle is greatly affected by longitudinal and vertical vibrations caused by uneven road surfaces. The aim of this master’s thesis work is to compensate the longitudinal acceleration oscillations, and to reduce the sprung mass motions in term of heave and pitch. The innovation in this research work is represented by an integration control strategy of active suspension and in-wheel motor control for ride comfort optimization that has not been explored yet. Electric vehicles equipped with in-wheel powertrains provide significantly enhanced wheel torque control performance, because of the accuracy and fast dynamics of electric motors, in comparison with the conventional internal combustion engines and friction brakes. On the downside, in-wheel powertrains significantly increase the ratio between unsprung mass and sprung mass, increasing the vertical and longitudinal vibrations of the sprung and unsprung masses caused by road irregularities and consequently deteriorating the vehicle comfort. However, in-wheel electric powertrains, when combined with pre-emptive control based on the information on the road profile ahead, have the ability to provide some effective compensation. This paper presents a proof-of-concept nonlinear model predictive control (NMPCEM) implementation for a four-wheel-drive EV with in-wheel direct drive powertrains, using the road preview information to compensate the longitudinal acceleration oscillations induced by road irregularities. In addition, a second nonlinear model predictive control (NMPCAS) is proposed for the active suspension control with the aim of reducing the vertical vibration on the sprung mass and compensating the motor torques effect in term of heave and pitch. A CarMaker model of an all-wheel drive electric vehicle with in-wheel motors, including a realistic tire model for ride comfort simulation, is used for the control system assessment. The improvement brought by the proposed road preview controllers is evaluated through objective performance indicators along a variety of maneuvers, and is evident with respect to the same vehicle without the controller. The master’s thesis work has been realized in collaboration with the Centre of Automotive Engineering at the University of Surrey (UK); in particular the work has been supervised by Prof. Aldo Sorniotti, Dr. Umberto Montanaro and PhD student Pietro Stano from “University of Surrey”, and by Prof. Alessandro Vigliani and Dr. Antonio Tota from “Politecnico di Torino”.