Stochastic Modeling and Analysis of Public Electric Vehicle Fleet Charging Station Operations

Tianyang Zhang, Xi Chen, Bin Wu, Mehmet Dedeoglu, Junshan Zhang, Ljiljana Trajkovic

Research output: Contribution to journalArticlepeer-review

Abstract

The electric vehicle (EV) fleet is gradually growing into a major part of public transportation. Proper planning and operation of EV supply equipment (EVSE) is essential to ensure the efficient and economic operations of the EV fleets. Charging stations (CS) have gained market attention due to their lower cost and versatility. Battery swapping stations (BSS) have also received considerable attention because of their promise to provide fast and sustainable battery replacements. However, their commercial viability is unclear due to their requirement for large capital and infrastructure deployment. In this paper, we develop a stochastic model for interactions between CS/BSS and taxi/bus fleets. The model is based on a realistic abstraction of users' behavior defined by various stochastic processes. It also considers the dynamic impacts of the road congestion. Analytical revenue boundaries are derived and verified by simulations. These simulation results may prove valuable for future studies of public transit.

Original languageEnglish (US)
JournalIEEE Transactions on Intelligent Transportation Systems
DOIs
StateAccepted/In press - 2021

Keywords

  • Batteries
  • Electric vehicle
  • Electric vehicle charging
  • electric vehicle supply equipment
  • EV charging networks
  • public transit
  • Public transportation
  • Roads
  • smart grids.
  • State of charge
  • Stochastic processes
  • Urban areas

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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