New logistical issues in using electric vehicle fleets with battery exchange infrastructure

AbstractThere is much reason to believe that fleets of service vehicles of many organizations will transform their vehicles that utilize alternative fuels that are more sustainable. The electric vehicle (EV) is a good candidate for this transformation, especially which “refuels” by exchanging its spent batteries with charged ones. This paper discusses some new logistical issues that must be addressed by such EV fleets, principally the issues related to the limited driving range of each EV's set of charged batteries and the possible detouring for battery exchanges. In particular, the paper addresses (1) the routing and scheduling of the fleet, (2) the locations of battery-exchange stations, and (3) the sizing of each facility. An overview of the literature on the topic is provided and some initial results are presented

New Logistical Issues in Using Electric Vehicle Fleets with Battery Exchange Infrastructure

abstract: There is much reason to believe that fleets of service vehicles of many organizations will transform their vehicles that utilize alternative fuels that are more sustainable. The electric vehicle (EV) is a good candidate for this transformation, especially which “refuels” by exchanging its spent batteries with charged ones. This paper discusses some new logistical issues that must be addressed by such EV fleets, principally the issues related to the limited driving range of each EV's set of charged batteries and the possible detouring for battery exchanges. In particular, the paper addresses (1) the routing and scheduling of the fleet, (2) the locations of battery-exchange stations, and (3) the sizing of each facility. An overview of the literature on the topic is provided and some initial results are presented

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

With the development of alternative fuel (AF) vehicle technologies, studies on finding the potential location of AF refueling stations in transportation networks have received considerable attention. Due to the strong limited driving range, AF vehicles for long-distance intercity trips may require multiple refueling stops at different locations on the way to their destination, which makes the AF refueling station location problem more challenging. In this paper, we consider that AF vehicles requiring multiple refueling stops at different locations during their long-distance intercity trips are capable of making detours from their preplanned paths and selecting return paths that may be different from original paths for their round trips whenever AF refueling stations are not available along the preplanned paths. These options mostly need to be considered when an AF refueling infrastructure is not fully developed on a highway system. To this end, we first propose an algorithm to generate alternative paths that may provide the multiple AF refueling stops between all origin/destination (OD) vertices. Then, a new mixed-integer programming model is proposed to locate AF refueling stations within a preselected set of candidate sites on a directed transportation network by maximizing the coverage of traffic flows along multiple paths. We first test our mathematical model with the proposed algorithm on a classical 25-vertex network with 25 candidate sites through various scenarios that consider a different number of paths for each OD pair, deviation factors, and limited driving ranges of vehicles. Then, we apply our proposed model to locate liquefied natural gas refueling stations in the state of Pennsylvania considering the construction budget. Our results show that the number of alternative paths and deviation distance available significantly affect the coverage of traffic flows at the stations as well as computational time

Dynamic Model for the EV's Charging Infrastructure Planning Through Finite Element Method

The rapid increase in the number of electric vehicles around the world, the high demands on the charging stations, and the challenges for locating the charging stations made researchers around the globe to think for a proper solution. In this paper, a new method to locate EV's charging infrastructures, based on the parallelism between mobility needs and heat equation implemented with Finite Element Method analysis (FEM), is proposed. The method is applied for two cities with similar metropolitan area: Boston (USA) and Milan (Italy), with further results. Although FEM is a mathematical tool for solving physical problems, the behavior of different parameters in this paper is modeled as physical objects. In addition, the parameters are modeled according to the heat equation. Heat density maps are elaborated for the considered case studies. The two cities with extremely different characteristics are chosen to demonstrate the general application of the proposed method. Heat density maps show the likely demand points to establish charging infrastructures for EV's. The annual electricity consumption maps of the two considered cities are reported. The analysis of heat density and electricity consumption maps, together with the considerations of mains supply capacity can give a perspective for the location of charging stations in the future urban environments. The developed method contributes to deploy charging stations in an urban environment