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Charging/Refueling Navigation Strategies for Plug-in Hybrid Hydrogen and Electric Vehicles With Irrationalities and Energy Substitution | IEEE Journals & Magazine | IEEE Xplore

Charging/Refueling Navigation Strategies for Plug-in Hybrid Hydrogen and Electric Vehicles With Irrationalities and Energy Substitution


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...Show More

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.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 20, Issue: 1, January 2024)
Page(s): 583 - 595
Date of Publication: 20 April 2023

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