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

Abstract 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 paper 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 display 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 significantly 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.