Location Optimization of Electric Vehicle Mobile Charging Stations Considering Multi-Period Stochastic User Equilibrium

Abstract

This study researches the dynamical location optimization problem of a mobile charging station (MCS) powered by a LiFePO 4 battery to meet charging demand of electric vehicles (EVs). In city suburbs, a large public charging tower is deployed to provide recharging services for MCS. The EV’s driver can reserve a real-time off-street charging service on the MCS through a vehicular communication network. This study formulates a multi-period nonlinear flow-refueling location model (MNFRLM) to optimize the location of the MCS based on a network designed by Nguyen and Dupuis (1984). The study transforms the MNFRLM model into a linear integer programming model using a linearization algorithm, and obtains global solution via the NEOS cloud CPLEX solver. Numerical experiments are presented to demonstrate the model and its solution algorithm.

Study of design features of mobile charging units for electric transport for development of sketch design documentation

“…В сценарии инвестирования в СЗС с использованием МЗС инвесторы могут найти лучшие места для СЗС, прежде чем вкладывать значительные средства в расширение сети зарядки. Кроме того, можно будет установить множество МЗС временно, именно тогда и там, где они необходимы [28]. Этот вариант может помочь инвесторам лучше оценить количество запросов на взимание платы и получить больше времени для расширения своей сети СЗС.…”

“…Недостатки МЗС При разработке МЗС необходимо решить несколько серьезных инженерных проблем [28]. Например, разработка конструкции мобильного зарядного устройства и аккумулятора, который может заряжаться и разряжаться непрерывно, с учетом высокой стоимости аккумуляторов и срока службы аккумулятора [11], проблема проектирования и затрат, связанных с силовым электронным оборудованием [31], разработка системы управления [32].…”

A Literature Review on Mobile Charging Station Technology for Electric Vehicles

“…FCSs can offer little charging flexibility. On the contrary, MCSs can store energy during off-peak hours and provide charging services for electric vehicles based on real-time charging demand [22]. ii.…”

Distributed Auction-Based Incentive Mechanism for Energy Trading Between Electric Vehicles and Mobile Charging Stations

“…The studies in [15], [16] optimize the number of MCSs and charging piles at each MCS to reduce the service delay. In [17], the authors propose a nonlinear flow-refueling location model to optimize MCS placements. Similarly, the study in [18] develops an algorithm to determine the optimal placements of MCSs concerning the charging demand and maintenance cost.…”