DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: The impact of reliable range estimation on battery electric vehicle feasibility

Abstract

Range limitation is a significant obstacle to market acceptance of battery electric vehicles (BEVs). Range anxiety is exacerbated when drivers could not reliably predict the remaining battery range or when their journeys were unexpectedly extended. This paper quantifies the impact of reliable range estimation on BEV feasibility using GPS-tracked travel survey data, collected over an 18-month period (from November 2004 to April 2006) in the Seattle metropolitan area. BEV feasibility is quantified as the number of days when travel adaption is needed if a driver replaces a conventional gasoline vehicle (CGV) with a BEV. The distribution of BEV range is estimated based on the real-world fuel efficiency data. A driver is assumed to choose between using a BEV or a substitute gasoline vehicle, based on the cumulative prospect theory (CPT). BEV is considered feasible for a particular driver if he/she needs to use a substitute vehicle on less than 0.5% of the travel days. By varying the values of some CPT parameter, the percentage of BEV feasible vehicles could change from less than 5% to 25%. Additionally, the numerical results show that with a 50% reduction in the standard deviation and 50% increase in the mean of the BEV rangemore » distribution BEV feasibility increases from less than 5% of the sampled drivers to 30%.« less

Authors:
 [1];  [2];  [3]; ORCiD logo [4];  [1]
  1. Iowa State Univ., Ames, IA (United States)
  2. Lamar Univ., Beaumont, TX (United States)
  3. Walmart Labs, San Bruno, CA (United States)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Vehicle Technologies Office
OSTI Identifier:
1657906
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
International Journal of Sustainable Transportation
Additional Journal Information:
Journal Volume: 14; Journal Issue: 11; Journal ID: ISSN 1556-8318
Publisher:
Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; battery electric vehicles (BEVs); cumulative prospect theory (CPT); daily vehicle miles traveled (DVMT); range anxiety

Citation Formats

Dong, Jing, Wu, Xing, Liu, Changzheng, Lin, Zhenhong, and Hu, Liang. The impact of reliable range estimation on battery electric vehicle feasibility. United States: N. p., 2019. Web. doi:10.1080/15568318.2019.1639085.
Dong, Jing, Wu, Xing, Liu, Changzheng, Lin, Zhenhong, & Hu, Liang. The impact of reliable range estimation on battery electric vehicle feasibility. United States. https://doi.org/10.1080/15568318.2019.1639085
Dong, Jing, Wu, Xing, Liu, Changzheng, Lin, Zhenhong, and Hu, Liang. Tue . "The impact of reliable range estimation on battery electric vehicle feasibility". United States. https://doi.org/10.1080/15568318.2019.1639085. https://www.osti.gov/servlets/purl/1657906.
@article{osti_1657906,
title = {The impact of reliable range estimation on battery electric vehicle feasibility},
author = {Dong, Jing and Wu, Xing and Liu, Changzheng and Lin, Zhenhong and Hu, Liang},
abstractNote = {Range limitation is a significant obstacle to market acceptance of battery electric vehicles (BEVs). Range anxiety is exacerbated when drivers could not reliably predict the remaining battery range or when their journeys were unexpectedly extended. This paper quantifies the impact of reliable range estimation on BEV feasibility using GPS-tracked travel survey data, collected over an 18-month period (from November 2004 to April 2006) in the Seattle metropolitan area. BEV feasibility is quantified as the number of days when travel adaption is needed if a driver replaces a conventional gasoline vehicle (CGV) with a BEV. The distribution of BEV range is estimated based on the real-world fuel efficiency data. A driver is assumed to choose between using a BEV or a substitute gasoline vehicle, based on the cumulative prospect theory (CPT). BEV is considered feasible for a particular driver if he/she needs to use a substitute vehicle on less than 0.5% of the travel days. By varying the values of some CPT parameter, the percentage of BEV feasible vehicles could change from less than 5% to 25%. Additionally, the numerical results show that with a 50% reduction in the standard deviation and 50% increase in the mean of the BEV range distribution BEV feasibility increases from less than 5% of the sampled drivers to 30%.},
doi = {10.1080/15568318.2019.1639085},
journal = {International Journal of Sustainable Transportation},
number = 11,
volume = 14,
place = {United States},
year = {Tue Nov 05 00:00:00 EST 2019},
month = {Tue Nov 05 00:00:00 EST 2019}
}

Works referenced in this record:

Experiencing Range in an Electric Vehicle: Understanding Psychological Barriers: EXPERIENCING RANGE
journal, October 2011


Big-data framework for electric vehicle range estimation
conference, October 2014

  • Rahimi-Eichi, Habiballah; Chow, Mo-Yuen
  • IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society
  • DOI: 10.1109/IECON.2014.7049362

Characterization of urban commuter driving profiles to optimize battery size in light-duty plug-in electric vehicles
journal, May 2011

  • Smith, R.; Shahidinejad, S.; Blair, D.
  • Transportation Research Part D: Transport and Environment, Vol. 16, Issue 3
  • DOI: 10.1016/j.trd.2010.09.001

Curvature of the Probability Weighting Function
journal, December 1996


Rapid estimation of electric vehicle acceptance using a general description of driving patterns
journal, February 2015

  • Tamor, Michael A.; Moraal, Paul E.; Reprogle, Briana
  • Transportation Research Part C: Emerging Technologies, Vol. 51
  • DOI: 10.1016/j.trc.2014.10.010

A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis
journal, November 2000


A User Equilibrium Model Based on Cumulative Prospect Theory for Degradable Transport Network
conference, April 2011

  • Wang, Qian; Xu, Wei
  • 2011 Fourth International Joint Conference on Computational Sciences and Optimization (CSO)
  • DOI: 10.1109/CSO.2011.62

Myopic Loss Aversion and the Equity Premium Puzzle
journal, February 1995

  • Benartzi, S.; Thaler, R. H.
  • The Quarterly Journal of Economics, Vol. 110, Issue 1
  • DOI: 10.2307/2118511

Optimizing and Diversifying Electric Vehicle Driving Range for U.S. Drivers
journal, November 2014


Cost analysis of plug-in hybrid electric vehicles using GPS-based longitudinal travel data
journal, May 2014


Estimation of Energy Use by Plug-In Hybrid Electric Vehicles: Validating Gamma Distribution for Representing Random Daily Driving Distance
journal, January 2012

  • Lin, Zhenhong; Dong, Jing; Liu, Changzheng
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2287, Issue 1
  • DOI: 10.3141/2287-05

User decision-making and technology choices in the U.S. carsharing market
journal, October 2016


Uncertainty, loss aversion, and markets for energy efficiency
journal, July 2011


Fuel reduction and electricity consumption impact of different charging scenarios for plug-in hybrid electric vehicles
journal, August 2011


Electrification of Household Travel by Electric and Hybrid Vehicles
conference, February 1982

  • Kiselewich, S. J.; Hamilton, W. F.
  • SAE International Congress and Exposition, SAE Technical Paper Series
  • DOI: 10.4271/820452

Intrapersonal variability in daily urban travel behavior: Some additional evidence
journal, May 1995

  • Pas, Eric I.; Sundar, Subramanian
  • Transportation, Vol. 22, Issue 2
  • DOI: 10.1007/BF01099436

Simplified electric vehicle power train models and range estimation
conference, September 2011

  • Hayes, John G.; de Oliveira, R. Pedro R.; Vaughan, Sean
  • 2011 IEEE Vehicle Power and Propulsion Conference (VPPC)
  • DOI: 10.1109/VPPC.2011.6043163

Electric vehicles: How much range is required for a day’s driving?
journal, December 2011

  • Pearre, Nathaniel S.; Kempton, Willett; Guensler, Randall L.
  • Transportation Research Part C: Emerging Technologies, Vol. 19, Issue 6
  • DOI: 10.1016/j.trc.2010.12.010

A statistical approach to estimating acceptance of electric vehicles and electrification of personal transportation
journal, January 2013

  • Tamor, Michael A.; Gearhart, Chris; Soto, Ciro
  • Transportation Research Part C: Emerging Technologies, Vol. 26
  • DOI: 10.1016/j.trc.2012.07.007

Day-to-Day Travel Variability in the Commute Atlanta, Georgia, Study
journal, January 2007

  • Elango, Vetri Venthan; Guensler, Randall; Ogle, Jennifer
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2014, Issue 1
  • DOI: 10.3141/2014-06

Advances in prospect theory: Cumulative representation of uncertainty
journal, October 1992

  • Tversky, Amos; Kahneman, Daniel
  • Journal of Risk and Uncertainty, Vol. 5, Issue 4
  • DOI: 10.1007/BF00122574

Stochastic Modeling of Battery Electric Vehicle Driver Behavior: Impact of Charging Infrastructure Deployment on the Feasibility of Battery Electric Vehicles
journal, January 2014

  • Dong, Jing; Lin, Zhenhong
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2454, Issue 1
  • DOI: 10.3141/2454-08

Coping with unreliable transportation when collecting children: Examining parents’ behavior with cumulative prospect theory
journal, June 2009

  • Schwanen, Tim; Ettema, Dick
  • Transportation Research Part A: Policy and Practice, Vol. 43, Issue 5
  • DOI: 10.1016/j.tra.2009.01.002

Reference Points in Commuter Departure Time Choice: A Prospect Theoretic Test of Alternative Decision Frames
journal, January 2004

  • Senbil, Metin; Kitamura, Ryuichi
  • Journal of Intelligent Transportation Systems, Vol. 8, Issue 1
  • DOI: 10.1080/15472450490437726

Violations of the betweenness axiom and nonlinearity in probability
journal, March 1994

  • Camerer, Colin F.; Ho, Teck-Hua
  • Journal of Risk and Uncertainty, Vol. 8, Issue 2
  • DOI: 10.1007/BF01065371

The Loss of Loss Aversion: Will It Loom Larger Than Its Gain?
journal, April 2018

  • Gal, David; Rucker, Derek D.
  • Journal of Consumer Psychology, Vol. 28, Issue 3
  • DOI: 10.1002/jcpy.1047

Lithium-ion battery cell degradation resulting from realistic vehicle and vehicle-to-grid utilization
journal, April 2010


Impact of stochastic driving range on the optimal charging infrastructure expansion planning
journal, December 2017


Analysis of plug-in hybrid electric vehicles’ utility factors using GPS-based longitudinal travel data
journal, August 2015

  • Wu, Xing; Aviquzzaman, Md.; Lin, Zhenhong
  • Transportation Research Part C: Emerging Technologies, Vol. 57
  • DOI: 10.1016/j.trc.2015.05.008

Battery Electric Vehicle Driving and Charging Behavior Observed Early in The EV Project
journal, April 2012

  • Smart, John; Schey, Stephen
  • SAE International Journal of Alternative Powertrains, Vol. 1, Issue 1
  • DOI: 10.4271/2012-01-0199

Modelling public-transport users’ behaviour at connection point
journal, May 2013


Adaptive route choices in risky traffic networks: A prospect theory approach
journal, October 2010

  • Gao, Song; Frejinger, Emma; Ben-Akiva, Moshe
  • Transportation Research Part C: Emerging Technologies, Vol. 18, Issue 5
  • DOI: 10.1016/j.trc.2009.08.001

A decision-making rule for modeling travelers’ route choice behavior based on cumulative prospect theory
journal, April 2011

  • Xu, Hongli; Zhou, Jing; Xu, Wei
  • Transportation Research Part C: Emerging Technologies, Vol. 19, Issue 2
  • DOI: 10.1016/j.trc.2010.05.009

Prospect Theory: An Analysis of Decision under Risk
journal, March 1979

  • Kahneman, Daniel; Tversky, Amos
  • Econometrica, Vol. 47, Issue 2
  • DOI: 10.2307/1914185

Development of an enhanced route choice model based on cumulative prospect theory
journal, October 2014


An empirical assessment of the feasibility of battery electric vehicles for day-to-day driving
journal, August 2014

  • Greaves, Stephen; Backman, Henry; Ellison, Adrian B.
  • Transportation Research Part A: Policy and Practice, Vol. 66
  • DOI: 10.1016/j.tra.2014.05.011

Travelers' Risk Attitude Classification Method Based on Cumulative Prospect Theory and Experimental Results
conference, September 2015

  • Yang, Chao; Liu, Binbin; Zhao, Lianyan
  • 2015 IEEE 18th International Conference on Intelligent Transportation Systems - (ITSC 2015)
  • DOI: 10.1109/ITSC.2015.146

Genetic Algorithm to Estimate Cumulative Prospect Theory Parameters for Selection of High-Occupancy-Vehicle Lane
journal, January 2010

  • Chow, Joseph Y. J.; Lee, Gunwoo; Yang, Inchul
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2157, Issue 1
  • DOI: 10.3141/2157-09

Parameter-Free Elicitation of Utility and Probability Weighting Functions
journal, November 2000


Predicting the market potential of plug-in electric vehicles using multiday GPS data
journal, July 2012


Form Matters: Informing Consumers Effectively
journal, January 2013


Prospect theory based estimation of drivers’ risk attitudes in route choice behaviors
journal, December 2014


Battery capacity design for electric vehicles considering the diversity of daily vehicles miles traveled
journal, November 2016

  • Li, Zhiheng; Jiang, Shan; Dong, Jing
  • Transportation Research Part C: Emerging Technologies, Vol. 72
  • DOI: 10.1016/j.trc.2016.10.001

Evaluation of Risk Perception in Route Choice Experiments: An Application of the Cumulative Prospect Theory
conference, September 2015

  • Luca, Stefano de; Pace, Roberta Di
  • 2015 IEEE 18th International Conference on Intelligent Transportation Systems - (ITSC 2015)
  • DOI: 10.1109/ITSC.2015.60

Mainstream consumers driving plug-in battery-electric and plug-in hybrid electric cars: A qualitative analysis of responses and evaluations
journal, January 2012

  • Graham-Rowe, Ella; Gardner, Benjamin; Abraham, Charles
  • Transportation Research Part A: Policy and Practice, Vol. 46, Issue 1
  • DOI: 10.1016/j.tra.2011.09.008

Analysing the Energy Consumption of the BMW ActiveE Field Trial Vehicles with Application to Distance to Empty Algorithms
journal, January 2014


Identification of Parameters for a Prospect Theory Model for Travel Choice Analysis
journal, January 2008

  • Avineri, Erel; Bovy, Piet H. L.
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2082, Issue 1
  • DOI: 10.3141/2082-17

Actual Versus Estimated Utility Factor of a Large Set of Privately Owned Chevrolet Volts
journal, April 2014

  • Smart, John; Bradley, Thomas; Salisbury, Shawn
  • SAE International Journal of Alternative Powertrains, Vol. 3, Issue 1
  • DOI: 10.4271/2014-01-1803

Within-day recharge of plug-in hybrid electric vehicles: Energy impact of public charging infrastructure
journal, July 2012

  • Dong, Jing; Lin, Zhenhong
  • Transportation Research Part D: Transport and Environment, Vol. 17, Issue 5
  • DOI: 10.1016/j.trd.2012.04.003