Feasibility assessment for battery electric vehicles based on multi-day activity-travel patterns.

Details

• Creators:
  Kang, Jee Eun ; Zhang, Anpeng ; Kwon, Changhyun
• Corporate Creators:
  State University of New York at Buffalo. Department of Industrial and Systems Engineering
• Corporate Contributors:
  University Transportation Research Center
• Subject/TRT Terms:
  • Travel patterns
  • Electric vehicles
  • Feasibility analysis
  • Sustainable transportation Activity-travel patterns
  • day-to-day variability
  • battery electric vehicles feasibility assessment
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  University Transportation Research Center
• Abstract:
  A Battery Electric Vehicle (BEV) feasibility considering State Of Charge (SOC) level is ; assessed using multiday activity-travel patterns to overcome the limitations of using one-day ; activity-travel patterns. Since multi-day activity-travel patterns are not readily available, ; we generate multi-day activity-travel patterns through sampling from readily available ; single-day household travel survey data with considerations of day-to-day intrapersonal ; variability. One of the key observation we make is that the distribution of interpersonal ; variability in single-day travel activity datasets is similar to the distribution of intrapersonal ; variability in multi-day datasets. Thus, interpersonal variability observed in cross-sectional ; single-day data of a large population can be used to generate the day-to-day intrapersonal ; variability. The proposed sampling method is based on activity-travel pattern type ; clustering, travel distance and variability distribution to extract such information from single-day ; data. Validation and stability tests of the proposed sampling methods are presented. ; BEV feasibility assessment results show that our sampling method combined with trivial ; method provide better estimation of population wide BEV feasibility than using cross-sectional ; data only.
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• Format:
  PDF
• Funding:
  49198-22-27
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32340/dot_32340_DS1.pdf
• File Type:
  [PDF - 3.73 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:6ef067bf47bac5e0d1898352785abbb9466f064d060acfe21f0ff9b1b48dd0cba0aedb79bb76092d7be7006eb1856ae67ca8fbb01513aae3a3cf34b1662be0e5