Modeling charging behavior of battery electric vehicle drivers: A cumulative prospect theory based approach

Hu, Liang; Dong, Jing; Lin, Zhenhong

doi:10.1016/j.trc.2019.03.027

Title: Modeling charging behavior of battery electric vehicle drivers: A cumulative prospect theory based approach

Journal Article · Tue Apr 02 00:00:00 EDT 2019 · Transportation Research Part C: Emerging Technologies

DOI:https://doi.org/10.1016/j.trc.2019.03.027· OSTI ID:1558513

Hu, Liang ^[1];

^[1];

^[2]

Iowa State Univ., Ames, IA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

The behavior of drivers in charging a battery electric vehicle (BEV) can be influenced by psychological factors such as personality and risk preference. This paper proposes a cumulative prospect theory (CPT) based modeling framework to describe the charging behavior of BEV drivers. CPT captures an individual’s attitude and preference toward risk in the decision-making process. A BEV mass-market scenario is constructed using the 2017 National Household Travel Survey (NHTS) data. This work applies the CPT-based charging behavior model to study the battery state-of-charge (SOC) when drivers decide to charge their vehicles, charging timing and location choices, and charging power demand profile under the mass-market scenario. In addition, sensitivity analyses are used to examine the drivers’ risk attitudes and public charger network coverage. BEV drivers who reflect a higher degree of risk-seeking tend to charge vehicles at a lower SOC. Some home charging shifts to workplace and public charging as the public charger network expands, but home charging still plays the most significant role in BEV use. The power demand from public chargers increases critically with BEV expansion and has a larger impact on the power grid. The time-of-use (TOU) electricity rate can shift peak power demand to off-peak periods from midnight to early morning.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1558513

Alternate ID(s):: OSTI ID: 1547573

Journal Information:: Transportation Research Part C: Emerging Technologies, Vol. 102, Issue C; ISSN 0968-090X

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 61 works

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Title: Modeling charging behavior of battery electric vehicle drivers: A cumulative prospect theory based approach

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