Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
June 13, 2026IET Intelligent Transport SystemsOpen Access

Behaviour‐Driven Optimization of Multi‐Type Fast‐Charging Configuration in Highway Service Areas Under Bounded Rationality

View Full Paper
Ask AI
Bookmark
Share

Authors

PZPengfei ZhaoXSXintian SongXSXu Sun

Discussion

Loading...

Member takes

Overview

Randomized trial examines optimal charging setups for electric vehicles, suggesting effective infrastructure deployment.

Key Points

  • This research aims to determine the best charging configurations for electric vehicles in highway service areas based on user preferences and rationality limits.
  • Conducted a stated-preference survey with 348 valid responses, both face-to-face and online.
  • Fitted multinomial logit and mixed logit models to analyze preferences for charging modes.
  • Developed a profit-maximization model considering charging capacity, pile numbers, and user demand penalties.
  • Optimal DCFC/HPC ratios and operator profits varied according to user volume and charging capacity.
  • Sensitivity analyses demonstrated significant impacts of waiting penalties on charging configurations.
  • The proposed framework aids in strategic planning for EV charging infrastructure deployment.

Cite This Study

Zhao et al. (2026) studied this question.

synapsesocial.com/papers/6a2cf500faef96ed7f0572e5https://doi.org/10.1049/itr2.70253
View Full Paper
Ask AI
Bookmark
Share