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Electric vehicle (EV) charging infrastructure development is one of the key aspects of the electrification of transportation systems. However, incorporating EV public charging facilities has practical and financial concerns, especially in developing economies. Recently, mobile public charging stations (MPCS) have been considered an alternate, practical, commercially scalable solution. Present research on MPCS operation algorithms assumes centralized algorithm execution and does not offer any features related to consumer data security. Moreover, they do not exploit the multi-port charging facility of MPCS, which is more economical for scheduling services. In this paper, a comprehensive framework for the decentralized execution of the MPCS operation algorithm for EV charging service using a hybrid cloud-edge server architecture is proposed. The decentralized execution enhances EV data security and reduces load on the cloud server, data transmission, and storage charges. Four vehicle routing algorithms, including exact integer programming (IP), Greedy, Greedy+2Opt heuristic, and meta-heuristic Tabu search algorithms, are applied to test the efficacy of the proposed framework. From the studies, the proposed framework with Greedy+2Opt performed well concerning scalability. Compared to one-to-one MPCS-EV charging, the proposed one-to-many charging framework offered a significant reduction in the transportation cost and the required number of MPCSs for a given energy delivered. Further, for a given MPCS battery capacity and service time window, the framework delivered higher energy compared to one-to-one service model.
Ganivada et al. (Sun,) studied this question.
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