Performance Optimization of a Formula Student Racing Car Using the IPG CarMaker, Part 1: Lap Time Convergence and Sensitivity Analysis
It is increasingly common for simulation and AI tools to aid in the vehicle design process. The IPG CarMaker uses a multibody vehicle model and a learning algorithm for the virtual driver. The goal is to discover the behavior of the learning algorithm from the point of view of reliability and conver...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/79/1/86 |
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| Summary: | It is increasingly common for simulation and AI tools to aid in the vehicle design process. The IPG CarMaker uses a multibody vehicle model and a learning algorithm for the virtual driver. The goal is to discover the behavior of the learning algorithm from the point of view of reliability and convergence. Simulations demonstrate that the lap time converges reliably. We also report that small changes in the vehicle parameters induce small changes in the simulated lap time, i.e., the lap time is a differentiable function of the vehicle parameters. Part 2 of this paper explains the aerodynamics and Drag Reduction System optimization. |
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| ISSN: | 2673-4591 |