Abstract for presentation (Poster or Podium)
Sustainable Transportation & Urban Development
Kenny Chandra Wijaya, Purdue ID Card
Student
Purdue University
Lafayette, Indiana, United States
Konstantina Gkritza, F. ASCE (she/her/hers)
Professor
Purdue University
West Lafayette, IN, United States
Prasanna Humagain, Phd
Senior research associate
Metro analytics
Logan, Utah, United States
Samuel Labi, n/a
Professor
Purdue University
west lafayette, Indiana, United States
Kenny Chandra Wijaya
Purdue University
Lafayette, Indiana, United States
Public charging is one of the critical components for driving electric vehicle (EV) adoption. Understanding factors that affect charging decision making from the experienced and non-experienced perspectives is equally important for two reasons. (1) enhance public charging utility perception to attract more public charger users; (2) increase the shifting rate of current non-EV users from internal combustion engine vehicles to EVs. This study designed and conducted an SP survey in Indiana to capture the characteristics of charging decision making. A total of 24 scenarios of long EV trip were designed and grouped into 4 question blocks (each 6 questions); each respondent was asked to answer a random question block. The decisions (dependent variables) include charging level (level 2 and DC fast charging, DCFC), and emerging technologies such as dynamic power transfer (DWPT). Each scenario consisted of multiple attributes including (3 levels state of charge, 12 levels trip cost, 6 levels access time, 8 levels charging time, 6 levels waiting time, etc.). After filtering the data with certain criteria, a total of 1208 and 6068 observations from experienced and non-experienced EV users, respectively were obtained. A nested logit model was estimated to identify explanatory variables that influence charging choices (level 2 and DCFC versus DWPT) for both experienced and non-experienced EV users. Although both groups depict a similarity of charging preference distribution (± 25% level 2, ± 50% DCFC, and ± 25% DWPT), however, the results show that the impact and significance of explanatory variables differ across experienced and non-experienced EV users. For instance, non-experienced respondents take into account the availability of amenities for making decisions, meanwhile this attribute does not seem to influence experienced EV users significantly. Knowing which aspects are substantial from each group’s perspective may help policymakers to identifying set of policy guidelines to enhance public charging utilization rate and attract more EV adopters.