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.
|Title of host publication||2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers|
|Number of pages||5|
|Publication status||Published - Nov 2020|
|Event||17th IEEE Vehicle Power and Propulsion Conference (VPPC 2020) - Virtual, Gijon, Spain|
Duration: 18 Nov 2020 → 16 Dec 2020
Conference number: 17
|Conference||17th IEEE Vehicle Power and Propulsion Conference (VPPC 2020)|
|Abbreviated title||VPPC 2020|
|Period||18/11/20 → 16/12/20|
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Copyright 2021 Elsevier B.V., All rights reserved.
- Convex optimization
- Electric vehicles