Minimum Race-Time Planning-Strategy for an Autonomous Electric Racecar

Thomas Herrmann, Francesco Passigato, Johannes Betz, Markus Lienkamp

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

22 Zitate (Scopus)

Abstract

Increasing attention to autonomous passenger vehicles has also attracted interest in an autonomous racing series. Because of this, platforms such as Roborace and the Indy Autonomous Challenge are currently evolving.Electric racecars face the challenge of a limited amount of stored energy within their batteries. Furthermore, the thermodynamical influence of an all-electric powertrain on the race performance is crucial. Severe damage can occur to the powertrain components when thermally overstressed. In this work we present a race-time minimal control strategy deduced from an Optimal Control Problem (OCP) that is transcribed into a Nonlinear Problem (NLP). Its optimization variables stem from the driving dynamics as well as from a thermodynamical description of the electric powertrain. We deduce the necessary first-order Ordinary Differential Equations (ODE)s and form simplified loss models for the implementation within the numerical optimization. The significant influence of the powertrain behavior on the race strategy is shown.

OriginalspracheEnglisch
Titel2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9781728141497
DOIs
PublikationsstatusVeröffentlicht - 20 Sept. 2020
Veranstaltung23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020 - Rhodes, Griechenland
Dauer: 20 Sept. 202023 Sept. 2020

Publikationsreihe

Name2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020

Konferenz

Konferenz23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020
Land/GebietGriechenland
OrtRhodes
Zeitraum20/09/2023/09/20

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