Abstract
Electric vehicles (EVs) are believed to be effective in reducing the use of fossil fuels. However, the increasing penetration of EVs can lead to challenges in managing EV charging/refueling. Typically, when EVs simultaneously gather at the stations, long queueing lengths and waiting times might occur, which might result in EV disutility. Thus, in this article, novel decision-making strategies considering the irrational behaviors of EVs are formulated to ensure the utility of EVs. Three types of EVs are investigated, i.e., plug-in electric vehicles, fuel cell electric vehicles, and plug-in hybrid hydrogen and electric vehicles (PH2EVs). First, three typical types of irrationalities are modeled based on prospect theory and irrational herding theory, including risk attitude irrationality, probability distortion, and irrational herding behaviors. Second, decision-making strategies, including station selection, navigation, and energy purchasing, are modeled based on EV irrationalities. In addition, when making the station selection decision, the selection ranking index is proposed to balance energy price and waiting time. Third, the energy substitution of PH2EV is investigated to determine the optimal energy-purchasing mixture of electricity and hydrogen. Simulation results show that the average waiting time and charging/refueling time of EV users of the proposed model are reduced compared with the other two cases where EV users are assumed to be rational. In addition, the overall utility of EV users is enhanced. © 2023 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 583-595 |
| Journal | IEEE Transactions on Industrial Informatics |
| Volume | 20 |
| Issue number | 1 |
| Online published | 20 Apr 2023 |
| DOIs | |
| Publication status | Published - Jan 2024 |
| Externally published | Yes |
Funding
. This work was supported in part by the Australian Research Council Research Hub under Grant IH180100020, in part by the ARC Training Centre under Grant IC200100023, in part by the ARC Linkage Project under Grant LP200100056, in part by the ARC DP220103881, in part by the Shenzhen Institute of Artificial Intelligence and Robotics for Society, in part by the National Natural Science Foundation of China Key Program under Grant 71931003 and Grant 72061147004, and in part by the National Natural Science Foundation of China under Grant 72171206, and in part by the Shenzhen Key Lab of Crowd Intelligence Empowered Low-Carbon Energy Network under Grant ZDSYS20220606100601002.
Research Keywords
- Charging/refueling navigation
- energy substitution
- integrated electricity-charging and hydrogen-refueling stations
- irrationalities
- plug-in hybrid hydrogen and electric vehicles
- selection ranking index
