Marco Ricco

Marco Ricco

Postgraduate research student

Academic and research departments

Department of Mechanical Engineering Sciences.

My publications


Marco Ricco, Mattia Zanchetta, Giovanni Cardolini Rizzo, Davide Tavernini, Aldo Sorniotti, Christoforos Chatzikomis, Mauro Velardocchia, Marc Geraerts, Miguel Dhaens (2019)On the design of yaw rate control via variable front-to-total anti-roll moment distribution, In: IEEE Transactions on Vehicular Technology IEEE

In vehicle dynamics, yaw rate control is used to improve the cornering response in steady-state and transient conditions. This can be achieved through an appropriate anti-roll moment distribution between the front and rear axles of a vehicle with controllable suspension actuators. Such control action alters the load transfer distribution, which in turn provokes a lateral tire force variation. With respect to the extensive set of papers from the literature discussing yaw rate tracking through active suspension control, this study presents: i) A detailed analysis of the effect of the load transfer on the lateral axle force and cornering stiffness; ii) A novel linearized single-track vehicle model formulation for control system design, based on the results in i); and iii) An optimization-based routine for the design of the non-linear feedforward contribution of the control action. The resulting feedforward-feedback controller is assessed through: a) Simulations with an experimentally validated model of a vehicle with active anti-roll bars (case study 1); and b) Experimental tests on a vehicle prototype with an active suspension system (case study 2).

Johan Theunissen, Aldo Sorniotti, Patrick Gruber, Saber Fallah, Marco Ricco, Michal Kvasnica, Miguel Dhaens (2019)Regionless Explicit Model Predictive Control of Active Suspension Systems with Preview, In: IEEE Transactions on Industrial Electronics Institute of Electrical and Electronics Engineers (IEEE)

Latest advances in road profile sensors make the implementation of pre-emptive suspension control a viable option for production vehicles. From the control side, model predictive control (MPC) in combination with preview is a powerful solution for this application. However, the significant computational load associated with conventional implicit model predictive controllers (i-MPCs) is one of the limiting factors to the widespread industrial adoption of MPC. As an alternative, this paper proposes an explicit model predictive controller (e-MPC) for an active suspension system with preview. The MPC optimization is run offline, and the online controller is reduced to a function evaluation. To overcome the increased memory requirements, the controller uses the recently developed regionless e-MPC approach. The controller was assessed through simulations and experiments on a sport utility vehicle demonstrator with controllable hydraulic suspension actuators. For frequencies

M Ricco, A Percolla, G. Cardolini Rizzo, M Zanchetta, D Tavernini, M Dhaens, M Geraerts, A Vigliani, A Tota, A Sorniotti (2020)On the model-based design of front-to-total anti-roll moment distribution controllers for yaw rate tracking, In: Vehicle system dynamicspp. 1-28 Taylor & Francis

In passenger cars active suspensions have been traditionally used to enhance comfort through body control, and handling through the reduction of the tyre load variations induced by road irregularities. However, active suspensions can also be designed to track a desired yaw rate profile through the control of the anti-roll moment distribution between the front and rear axles. The effect of the anti-roll moment distribution relates to the nonlinearity of tyre behaviour, which is difficult to capture in the linearised vehicle models normally used for control design. Hence, the tuning of anti-roll moment distribution controllers is usually based on heuristics. This paper includes an analysis of the effect of the lateral load transfer on the lateral axle force and cornering stiffness. A linearised axle force formulation is presented, and compared with a formulation from the literature, based on a quadratic relationship between cornering stiffness and load transfer. Multiple linearised vehicle models for control design are assessed in the frequency domain, and the respective controllers are tuned through optimisation routines. Simulation results from a nonlinear vehicle model are discussed to analyse the performance of the controllers, and show the importance of employing accurate models of the lateral load transfer effect during control design.