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Analyzing the Limitations of the Rider and Electric Motorcycle at the Pikes Peak International Hill Climb Race
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 02, 2019 by SAE International in United States
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This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel. Even though the rider’s heart rate implied a vigorous exercise intensity level, throttle values indicated that the rider wanted to go faster ~33% of the time. The motor reached a steady-state temperature that was approximately 30°C below the maximum allowable temperature and thus could have handled more current. By analyzing additional thermal and current data, it was concluded that the motor controller was likely a limiting factor but not the battery capacity since only ~2/3 of the total available battery energy was consumed. A model that estimates the optimal sprocket ratio was derived and validated; It was determined that using the optimal sprocket ratio of 62/12 would have decreased the finishing time by approximately 2 seconds.
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CitationRodgers, L., Jeunnette, M., Biffard, R., Möller, B. et al., "Analyzing the Limitations of the Rider and Electric Motorcycle at the Pikes Peak International Hill Climb Race," SAE Technical Paper 2019-01-1125, 2019, https://doi.org/10.4271/2019-01-1125.
Data Sets - Support Documents
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