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.

Language

  • English

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Filing Info

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