Skip to main content
OSTI.GOVU.S. Department of Energy Office of Scientific and Technical Information
U.S. Department of Energy
Office of Scientific and Technical Information
 

Analyzing battery electric vehicle feasibility from taxi travel patterns: The case study of New York City, USA

Journal Article · · Transportation Research Part C: Emerging Technologies
 [1];  [1];  [2];  [3]
  1. Iowa State Univ., Ames, IA (United States). Dept. of Civil, Construction and Environmental Engineering
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Transportation Research Center
  3. Southeast Univ., Nanjing (China). Development Research Inst. of Transportation Governed by Law
+ Show Author Affiliations
Electric taxis have the potential to improve urban air quality and save driver’s energy expenditure. Although battery electric vehicles (BEVs) have drawbacks such as the limited range and charging inconvenience, technological progress has been presenting promising potential for electric taxis. Many cities around the world including New York City, USA are taking initiatives to replace gasoline taxis with plug-in electric vehicles. This study extracts ten variables from the trip data of the New York City yellow taxis to represent their spatial-temporal travel patterns in terms of driver-shift, travel demand and dwell, and examines the implications of these driving patterns on the BEV taxi feasibility. The BEV feasibility of a taxi is quantified as the percentage of occupied trips that can be completed by BEVs of a given driving range during a year. It is found that the currently deployed 280 public charging stations in New York City are far from sufficient to support a large BEV taxi fleet. However, adding merely 372 new charging stations at various locations where taxis frequently dwell can potentially make BEVs with 200- and 300-mile ranges feasible for more than half of the taxi fleet. Finally, the results also show that taxis with certain characteristics are more suitable for switching to BEV-200 or BEV-300, such as fewer daily shifts, fewer drivers assigned to the taxi, shorter daily driving distance, fewer daily dwells but longer dwelling time, and higher likelihood to dwell at the borough of Manhattan.
Research Organization:
Iowa State Univ., Ames, IA (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1474658
Alternate ID(s):
OSTI ID: 1548903
Journal Information:
Transportation Research Part C: Emerging Technologies, Journal Name: Transportation Research Part C: Emerging Technologies Vol. 87; ISSN 0968-090X
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (23)

New York City Taxi Trip Data (2010-2013) dataset January 2016
Large-scale deployment of electric taxis in Beijing: A real-world analysis journal April 2016
Predicting the market potential of plug-in electric vehicles using multiday GPS data journal July 2012
Analysis on spatial-temporal features of taxis' emissions from big data informed travel patterns: a case of Shanghai, China journal January 2017
A review on lithium-ion battery ageing mechanisms and estimations for automotive applications journal November 2013
The optimal design and cost implications of electric vehicle taxi systems journal September 2014
Electric vehicles: How much range is required for a day’s driving? journal December 2011
Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data journal January 2014
Deploying public charging stations for electric vehicles on urban road networks journal November 2015
Optimizing the locations of electric taxi charging stations: A spatial–temporal demand coverage approach journal April 2016
Battery capacity design for electric vehicles considering the diversity of daily vehicles miles traveled journal November 2016
A data-driven optimization-based approach for siting and sizing of electric taxi charging stations journal April 2017
Empirically quantifying city-scale transportation system resilience to extreme events journal June 2017
How can the taxi industry survive the tide of ridesourcing? Evidence from Shenzhen, China journal June 2017
Siting public electric vehicle charging stations in Beijing using big-data informed travel patterns of the taxi fleet journal December 2014
Optimal locations of electric public charging stations using real world vehicle travel patterns journal December 2015
Predicting market potential and environmental benefits of deploying electric taxis in Nanjing, China journal December 2016
Optimization models for placement of an energy-aware electric vehicle charging infrastructure journal July 2016
How much does curation cost? journal January 2016
Analysis of Berlin's taxi services by exploring GPS traces conference June 2015
A Graph-Based Approach to Measuring the Efficiency of an Urban Taxi Service System journal September 2016
Stochastic Modeling of Battery Electric Vehicle Driver Behavior: Impact of Charging Infrastructure Deployment on the Feasibility of Battery Electric Vehicles
  • Dong, Jing; Lin, Zhenhong
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2454, Issue 1 https://doi.org/10.3141/2454-08
journal January 2014
A Feasibility Test on Adopting Electric Vehicles to Serve as Taxis in Daejeon Metropolitan City of South Korea journal September 2016

Cited By (1)

Experience: Understanding Long-Term Evolving Patterns of Shared Electric Vehicle Networks conference August 2019

Figures / Tables (15)

Fig. 1.(p. 5)figure Fig. 1.
Table 1(p. 6)table Table 1
Table 2(p. 7)table Table 2
Fig. 2.(p. 10)figure Fig. 2.
Table 3(p. 10)table Table 3
Fig. 3.(p. 12)figure Fig. 3.
Fig. 4.(p. 13)figure Fig. 4.
Fig. 5.(p. 14)figure Fig. 5.
Fig. 6.(p. 15)figure Fig. 6.
Fig. 7.(p. 16)figure Fig. 7.
Fig. 8.(p. 17)figure Fig. 8.
Fig. 10.(p. 18)figure Fig. 10.
Fig. 9.(p. 18)figure Fig. 9.
Table 4(p. 19)table Table 4
Table 5(p. 19)table Table 5

Similar Records

Optimization-based trip chain emulation for electrified ride-sourcing charging demand analyses
Journal Article · Wed May 04 20:00:00 EDT 2022 · Transportation Letters · OSTI ID:1991275
Feasibility Analysis of Taxi Fleet Electrification
Conference · Mon Jun 17 00:00:00 EDT 2019 · OSTI ID:1528853
Deployment priority of public charging speeds for increasing battery electric vehicle usability
Journal Article · Wed Oct 25 20:00:00 EDT 2023 · Transportation Research. Part D, Transport and Environment · OSTI ID:2217704

Related Subjects

25 ENERGY STORAGE
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
GPS data
battery electric vehicle (BEV) feasibility
charging infrastructure
electric taxis
spatial-temporal travel patterns