Abstract
Formula SAE (FSAE) is a student design competition organized by SAE International. The competition requires student teams to design and manufacture a formula style race car, to compete against other teams. Testing and validation of the vehicle is an integral part of the design and performance during the competition. Drivers for the collegiate competition are typically at an amateur level. As a result, the human factor plays a significant role in the outcome of dynamic events. In order to reduce uncertainty and improve the general performance, emphasis on driver training is necessary. Instead of overall performance of the driver based on an individual lap, the current research focuses on detailed components of the driver's actions throughout different sections of the lap. In order to evaluate the performance of each driver in each of these sections, an AiM data acquisition system was mounted on the EMS17R and EMS18R vehicles along with a multitude of sensors, allowing for everything the driver touches to be recorded as well as dynamic forces seen by the vehicles. The data collected revealed the strengths and weaknesses of individual drivers in comparison to others and the track limits. Providing indications of driver performance vs, the capability and design of the race car itself. This paper outlines a process that FSAE teams can use to collect and analyze data to be used for improving driver performance and engineering design.
Original language | English |
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Journal | SAE Technical Papers |
Volume | 2020-April |
Issue number | April |
DOIs | |
State | Published - Apr 14 2020 |
Event | SAE 2020 World Congress Experience, WCX 2020 - Detroit, United States Duration: Apr 21 2020 → Apr 23 2020 |
Scopus Subject Areas
- Automotive Engineering
- Safety, Risk, Reliability and Quality
- Pollution
- Industrial and Manufacturing Engineering