Providing Active Charging Services: An Assignment Strategy With Profit-Maximizing Heat Maps for Idle Mobile Charging Stations

In Internet of Electric Vehicles (IoEV), mobile charging stations (MCSs) have been deployed to complement fixed charging stations. Typically, MCSs are assigned to charge the electric vehicles with insufficient electricity which have made charging requests (termed IEVs). Moreover, there are some electric vehicles with insufficient electricity which have not made charging requests (termed quasi-IEVs). If idle MCSs are allowed to actively track quasi-IEVs according to their potential charging demand, then more IEVs could be promptly charged, and thus the charging profits of MCSs could be increased. However, due to the private ownership of electric vehicles, some private information cannot be provided in the potential charging demand of quasi-IEVs (e.g., the destinations and residual electricity), making the potential charging profits of idle MCSs hard to be evaluated, and thereby the proper assignments of idle MCSs are difficult to decide. To this end, we introduce the profit-maximizing heat maps to depict the potential charging demand of quasi-IEVs and evaluate the potential charging profits of idle MCSs. A profit-maximizing heat map remarks the positions around quasi-IEVs and displays them as continuous areas. Specifically, the different shades of colours are used to distinguish the quantities of potential charging profits of idle MCSs, and the sizes of coloured areas are used to indicate the possibility of quasi-IEVs passing through these positions. In this paper, we propose a Profit-Maximizing Assignment Strategy of Idle MCSs (PMASIM) to properly assign the idle MCSs to charge IEVs at selected charging positions, or track some quasi-IEVs according to the profit-maximizing heat maps. Extensive simulations and comparisons demonstrate the superior performance of PMASIM, i.e., with the profit-maximizing heat maps, the charging profits of MCSs are increased, and the proportion of charged IEVs is enhanced as well.