A comparative study on data segregation for mesoscopic energy modeling |
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Institution: | 1. Department of Automation, Tsinghua University, Beijing 100084, China;2. Bourns College of Engineering – Center for Environmental Research & Technology (CE-CERT), University of California, Riverside, 92507 CA, USA;1. National Research Council – Construction Technologies Institute, Padova, c.so Stati Uniti, 4, 35127 Padova, Italy;2. Department of Engineering and Management, Università degli Studi di Padova, Stradella S. Nicola, 3, 36100 Vicenza, Italy;3. Department of Industrial Engineering, Università degli Studi di Padova, via Venezia 1, 35131 Padova, Italy;1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China;2. Centre for Automotive Engineering, Cranfield University, Cranfield, Bedfordshire MK430AL, UK |
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Abstract: | On-road vehicles have been considered as one of the major contributors to energy consumption and air pollutant emissions. In order to quantify the corresponding environmental impacts, great efforts have been dedicated to the microscopic and macroscopic modeling for vehicle energy consumption and emissions. However, the mesoscopic modeling research that is focused on estimating trip-based energy consumption and is critical to some ITS applications (e.g., environmentally-friendly navigation), is relatively deficient. This study aims to investigate the effects of different data segregation methods on the mesoscopic modeling for vehicle energy consumption. A variety of novel methods, including the so-called conditional operating mode based method, have been proposed and evaluated using field data. Based on real-world data, statistical analyses have demonstrated the superior performance of enhanced models (i.e., conditional operating mode/VSP based models) in estimating vehicle energy consumption on a trip basis, compared to the other four models (velocity binning, time snipping, distance snipping and VSP based models) tested in this study. |
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Keywords: | Mesoscopic energy consumption model Data segregation Operating mode |
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