Quantifying Repeatability of Real-World On-Road Driving Using Dynamic Time Warping
Quantifying Repeatability of Real-World On-Road Driving Using Dynamic Time Warping
- Neue Suche nach: Daily, Jeremy
- Neue Suche nach: Rayno, Mars
- Neue Suche nach: Lobato, Peter
- Neue Suche nach: Bradley, Thomas
- Neue Suche nach: Daily, Jeremy
- Neue Suche nach: Rayno, Mars
- Neue Suche nach: Lobato, Peter
- Neue Suche nach: Bradley, Thomas
There are numerous activities in the automotive industry in which a vehicle drives a pre-defined route multiple times such as portable emissions measurement systems testing or real-world electric vehicle range testing. The speed profile is not the same for each drive cycle due to uncontrollable real-world variables such as traffic, stoplights, stalled vehicles, or weather conditions. It can be difficult to compare each run accurately. To this end, this paper presents a method to compare and quantify the repeatability of real-world on-road vehicle driving schedules using dynamic time warping (DTW). DTW is a well-developed computational algorithm which compares two different time-series signals describing the same underlying phenomenon but occurring at different time scales. DTW is applied to real-world, on-road drive cycles, and metrics are developed to quantify similarities between these drive cycles. This methodology is vehicle-agnostic and can be applied to conventional light-duty, hybrid, fully electric or heavy-duty on-road vehicles.
Dokumentinformationen
Quantifying Repeatability of Real-World On-Road Driving Using Dynamic Time Warping
Sae Technical Papers
WCX SAE World Congress Experience ; 2022
2022-03-29
Aufsatz (Konferenz)
Englisch
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