Building Tianjin driving cycle based on linear discriminant analysis

Driving cycles are standardized measurement procedure for the certification of vehicles’ economy and emission, and could help evaluate driving distance and new vehicular technologies. Thus driving cycle is always a hot research topic in vehicle industry. Linear discriminant analysis is a typical multivariate statistical method which has been used in many fields such as geology and economics in recent years, but its application to driving cycles is scarce. In this paper, Tianjin driving cycle is developed by using linear discriminant analysis. The effectiveness of the developed driving cycle is confirmed by comparing the parameter of the driving cycle and real-world driving data and evaluating the economy of electric vehicle. The uniqueness of this methodology is also discussed compared with traditional methodology in cycle development. This research could offer a new methodology for building driving cycles and has reference value to related researches.

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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
Supplemental Notes:
- Abstract reprinted with permission of Elsevier.
Authors:
- Jing, Zhecheng
- Wang, Guolin
- Zhang, Shupei
- Qiu, Chengqun
Publication Date: 2017-6

Language

English

Media Info

Media Type: Web
Features: Figures; Photos; References; Tables;
Pagination: pp 78-87
Serial:
- Transportation Research Part D: Transport and Environment
- Volume: 53
- Publisher: Elsevier
- ISSN: 1361-9209
- Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

TRT Terms: Cluster analysis; Discriminant analysis; Electric vehicles; Measurement; Speed; Time
Uncontrolled Terms: Driving cycles
Geographic Terms: Tianjin (China)
Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

Accession Number: 01639100
Record Type: Publication
Files: TRIS
Created Date: Jun 6 2017 4:18PM