Research has been conducted to develop a methodology for the generation of driving and duty cycles for refuse vehicles in conjunction with a larger effort in the design of a hybrid-electric refuse vehicle. This methodology includes the definition of real-world data that was collected, as well as a data analysis procedure based on sequencing of the collected data into micro-trips and hydraulic cycles. The methodology then applies multi-variate statistical analysis techniques to the sequences for classification. Finally, driving and duty cycles are generated based on matching the statistical metrics and distributions of the generated cycles to the collected database. Simulated vehicle fuel economy for these cycles is also compared to measured values.
A large scale design space exploration provides invaluable insight into vehicle design tradeoffs. Performing such a search requires designers to: • define appropriate performance criteria by which to judge the vehicles in the design space; • develop vehicle models to calculate the needed criteria; and • determine suitable velocity profiles as well as grade and terrain conditions to feed into the models. This paper presents a methodology for creating and conducting a design space exploration with particular application to heavy duty series hybrid electric-trucks.
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