Optimization-Based Control Allocation for Driving Braking Torque Vectoring in a Race Car - Archive ouverte HAL
Communication Dans Un Congrès Année : 2020

Optimization-Based Control Allocation for Driving Braking Torque Vectoring in a Race Car

Résumé

Most of recent researches on the automotive field focus on autonomous vehicles. These vehicles are equipped with conventional chassis systems. The goal is to control the vehicle's traction, brakes, and front steering. This paper discusses the importance of advanced chassis systems, as driving/braking torque vectoring, for both autonomous and non-autonomous vehicles, especially in a race mode. Reliable co-simulation results show that expanding the vehicle's potential leads to high performances and safety with respect to severe situations when optimal control allocation is ensured. Therefore, future passenger cars shall not only be equipped with additional sensors, but also by advanced systems along with adequate control algorithms.
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Dates et versions

hal-02447091 , version 1 (28-08-2020)

Identifiants

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Moad Kissai, Xavier Mouton, Bruno Monsuez, Adriana Tapus. Optimization-Based Control Allocation for Driving Braking Torque Vectoring in a Race Car. American Control Conference (ACC), 2020, Denver, United States. pp.2268-2275, ⟨10.23919/ACC45564.2020.9147343⟩. ⟨hal-02447091⟩
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