arXiv subjects

Gaetano Tavolo

Publications and source records attributed to Gaetano Tavolo.

3 recordsLinked to original sources

arXiv2024

Nonlinear Model Predictive Control for Preview-Based Traction Control

This study presents a nonlinear model predictive control (NMPC) formulation for preview-based traction control, which uses the information on the expected tire-road friction coefficient ahead to enhance the wheel slip control performance, in the context of connected vehicles with V2X features. Proof-of-concept experiments on an electric vehicle prototype highlight the real-time capability of the controller, and the wheel slip control performance improvement brought by the tire-road friction coefficient preview. Finally, an experimentally validated simulation model is used in sensitivity analyses, to evaluate the performance benefit of the preview-based controller for different dynamic characteristics (e.g., time constant and pure time delays) of the electric powertrains.

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arXiv2024

Novel pre-emptive control solutions for V2X connected electric vehicles

V2X technologies will become widespread in the next generation of passenger cars, and enable the development of novel vehicle control functionalities. Although a wide literature describes the energy efficiency benefits of V2X connectivity, e.g., in terms of vehicle speed profiling and platooning, there is a gap in the analysis of the potential of vehicle connectivity in enhancing the performance of active safety control systems. To highlight the impact vehicle connectivity could have on future active safety systems, this paper presents two novel control functions for connected vehicles, benefitting from the precise knowledge of the expected path and tire-road friction conditions ahead, as well as the current position of the ego vehicle. These functions, developed within recent and ongoing European projects, are: i) pre-emptive traction control; and ii) pre-emptive braking control.

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arXiv2024

Nonlinear Model Predictive Control for Enhanced Path Tracking and Autonomous Drifting through Direct Yaw Moment Control and Rear-Wheel-Steering

Path tracking (PT) controllers capable of replicating race driving techniques, such as drifting beyond the limits of handling, have the potential of enhancing active safety in critical conditions. This paper presents a nonlinear model predictive control (NMPC) approach that integrates multiple actuation methods, namely four-wheel-steering, longitudinal tyre force distribution, and direct yaw moment control, to execute drifting when this is beneficial for PT in emergency scenarios. Simulation results of challenging manoeuvres, based on an experimentally validated vehicle model, highlight the substantial PT performance improvements brought by: i) vehicle operation outside the envelope enforced by the current generation of stability controllers; and ii) the integrated control of multiple actuators.

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