An Experimentally Based Statistical Model for Predicting Motorcycle Shift Patterns

• Main Author: Caffrey, Peter James
• Format: Report
• Language: English
• ISSN: 0148-7191; 2688-3627
• DOI: 10.4271/2020-01-1046

Emissions from manual transmission motorcycles have been shown to be dependent upon transmission shift patterns. Presently, when undergoing an emission test for an Environmental Protection Agency (EPA) certification a manufacturer can designate their own shift points during the cycle or utilize an EPA prescribed shift pattern which uses basic up or down shifts at specific speeds regardless of the type of motorcycle, 40 CFR 86.528-78(h). In order to predict the real-life emissions from motorcycles, a comparative real-life shift pattern has been developed which can then be used to evaluate the suitability of the manufacturer’s shift schedule. To that end, a model that predicts shift points for motorcycles has been created. This model is based on the actual operation of different motorcycles by real life operators in a combined city and highway setting. Recognizing that no model is sufficient to adequately predict user operation in all situations, this model maintains a degree of flexibility in allowing the user to designate various limits to the shift probability, thus representing various rider scenarios. This would include a broad range of probability, and it can also be limited to a much narrower range of probability. It can represent very conservative riders and very aggressive riders in order to represent the broadest range of possibilities to allow for a proper determination of the emissions characteristics when operated at different levels.