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Optimizing Gear Ratio Selection for Lap Performance
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Selecting the optimal gear ratios to determine the best overall lap time for a racing vehicle is the goal of the simulation presented in this paper. Given a discrete set of individual gear ratio and final drive ratio options, the simulation chooses the set of gears and final drive that produce the minimum overall lap time. For example, one vehicle studied in this paper, an F2000 formula car, has 32 ratio choices for four forward gears and a final drive that has three different options. The simulation will iterate through the gear options to find the optimal gear selection for the best lap performance, accounting for various factors that could cause improper selection of gears. The simulation accounts for aerodynamic factors, gear shift time, rolling resistance and tire scrub. All values have been estimated from logged vehicle data, but experimental data can be easily used to help improve the vehicle model. Two vehicles were used in this simulation to compare the different types of racing and how that affects the gear selection. The first vehicle is the F2000 racecar, also called a Formula Continental. The F2000 car competes on a high-speed racetrack where aerodynamic loads will have a large effect. The second vehicle is a Formula SAE vehicle which competes on a relatively slow autocross track where traction will play a larger role and the aerodynamic effect will be lower. Therefore, the main losses will be some type of frictional drag. The selection of the optimal gear stack should show where the optimal area to run the engine for each vehicle is located. The optimal gear stack will also highlight the key areas where the vehicle needs full power and where the trade-off is better to not have full power.
CitationFrederick, R. and Dixon, B., "Optimizing Gear Ratio Selection for Lap Performance," SAE Technical Paper 2020-01-0543, 2020, https://doi.org/10.4271/2020-01-0543.
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