This paper presents different approaches to optimize battery electric vehicles (BEVs) fast charging strategy. A rule-based model was built to simulate BEV charging behavior. Monte Carlo analysis was performed to explore the potential variance of congestion at fast charging stations, which could cause longer than four-hour waiting at the most congested station. Genetic algorithm was performed to explore the potential minimum waiting time at fast charging stations, and it can decrease the waiting time at the most congested station to be shorter than one hour. A deterministic approach results in feasible suggestions that people could consider to take fast charging as soon as the state of charge is approaching 40-miles range while remaining relative short waiting time at charging stations.
展开▼
