Torque vectoring control for fully electric sae cars

Valentina De Pascale, Basilio Lenzo*, Flavio Farroni, Francesco Timpone, Xudong Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of 24th AIMETA Conference 2019
EditorsAntonio Carcaterra, Giorgio Graziani, Achille Paolone
PublisherSpringer Science and Business Media Deutschland GmbH
Pages1075-1083
Number of pages9
ISBN (Print)9783030410568
DOIs
Publication statusPublished - 2020
Event24th Conference of the Italian Association of Theoretical and Applied Mechanics, AIMETA 2019 - Rome, Italy
Duration: 15 Sept 201919 Sept 2019

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

Conference24th Conference of the Italian Association of Theoretical and Applied Mechanics, AIMETA 2019
Country/TerritoryItaly
CityRome
Period15/09/1919/09/19

Keywords

  • Driver model
  • Fully electric vehicle Formula SAE
  • Torque Vectoring Control

Fingerprint

Dive into the research topics of 'Torque vectoring control for fully electric sae cars'. Together they form a unique fingerprint.

Cite this