DE PASCALE, Valentina, LENZO, Basilio, FARRONI, Flavio, TIMPONE, Francesco and ZHANG, Xudong (2020). Torque Vectoring Control for fully electric Formula SAE cars. In: Proceedings of XXIV AIMETA Conference 2019. Lecture Notes in Mechanical Engineering . Springer, 1075-1083.
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Abstract
Fully electric vehicles with individually controlled powertrains can achieve significantly enhanced vehicle response, in particular by means of Torque Vectoring Control (TVC). This paper presents a TVC strategy for a Formula SAE (FSAE) fully electric vehicle, the “T-ONE” car designed by “UninaCorse E-team” of the University of Naples Federico II, featuring four in-wheel motors. A Matlab-Simulink double-track vehicle model is implemented, featuring non-linear (Pacejka) tyres. The TVC strategy consists of: i) a reference generator that calculates the target yaw rate in real time based on the current values of steering wheel angle and vehicle velocity, in order to follow a desired optimal understeer characteristic; ii) a high-level controller which generates the overall traction/braking force and yaw moment demands based on the accelerator/brake pedal and on the error between the target yaw rate and the actual yaw rate; iii) a control allocator which outputs the reference torques for the individual wheels. A driver model was implemented to work out the brake/accelerator pedal inputs and steering wheel angle input needed to follow a generic trajectory. In a first implementation of the model, a circular trajectory was adopted, consistently with the "skid-pad" test of the FSAE competition. Results are promising as the vehicle with TVC achieves up to � 9% laptime savings with respect to the vehicle without TVC, which is deemed significant and potentially crucial in the context of the FSAE competition.
Item Type: | Book Section |
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Additional Information: | Series ISSN: 2195-4356 |
Page Range: | 1075-1083 |
SWORD Depositor: | Symplectic Elements |
Depositing User: | Symplectic Elements |
Date Deposited: | 09 Oct 2019 15:51 |
Last Modified: | 31 Mar 2021 01:18 |
URI: | https://shura.shu.ac.uk/id/eprint/24918 |
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