Time-optimal Control Strategies for Electric Race Cars with Different Transmission Technologies

Olaf Borsboom, Chyannie A. Fahdzyana, Mauro Salazar, Theo Hofman

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

11 Citations (Scopus)
105 Downloads (Pure)


This paper presents models and optimization methods to rapidly compute the achievable lap time of a race car equipped with a battery electric powertrain. Specifically, we first derive a quasi-convex model of the electric powertrain, including the battery, the electric motor, and two transmission technologies: a fixed-gear transmission (FGT) and a continuously variable transmission (CVT) Second, assuming an expert driver, we formulate the time-optimal control problem for a given driving path and solve it using an iterative convex optimization algorithm. Finally, we showcase our framework by comparing the performance achievable with an FGT and a CVT on the Le Mans track. Our results show that a CVT can balance its lower efficiency and higher weight with a higher-efficiency and more aggressive motor operation, and significantly outperform an FGT.
Original languageEnglish
Title of host publication2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)9781728189598
Publication statusPublished - Nov 2020
Event17th IEEE Vehicle Power and Propulsion Conference (VPPC 2020) - Virtual, Gijon, Spain
Duration: 18 Nov 202016 Dec 2020
Conference number: 17


Conference17th IEEE Vehicle Power and Propulsion Conference (VPPC 2020)
Abbreviated titleVPPC 2020
CityVirtual, Gijon

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Copyright 2021 Elsevier B.V., All rights reserved.


  • Convex optimization
  • Electric vehicles


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