TY - GEN
T1 - Minimum Race-Time Planning-Strategy for an Autonomous Electric Racecar
AU - Herrmann, Thomas
AU - Passigato, Francesco
AU - Betz, Johannes
AU - Lienkamp, Markus
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/20
Y1 - 2020/9/20
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85099658783&partnerID=8YFLogxK
U2 - 10.1109/ITSC45102.2020.9294681
DO - 10.1109/ITSC45102.2020.9294681
M3 - Conference contribution
AN - SCOPUS:85099658783
T3 - 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
BT - 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020
Y2 - 20 September 2020 through 23 September 2020
ER -