Location Planning for Dynamic Wireless Charging Systems for Electric Airport Passenger Buses

Abstract

Abstract:The majority of the ground vehicles operating on the airside parts of commercial airports are currently powered by diesel engines. These include vehicles such as apron buses, fuel trucks, and aircraft tractors. Hence, these vehicles contribute to the overall CO 2 emissions of the aviation transport system and thus negatively influence its environmental footprint. To reduce this damaging environmental impact, these vehicles could potentially be electrified with on-board batteries as their energy sources. However, the conductive charging of such vehicles via stationary cable connections is rather time-consuming. A dynamic wireless charging system to supply public transportation passenger buses with electric energy while in motion has recently been installed on the Korea Advanced Institute of Science and Technology (KAIST) campus and in the Korean city of Gumi. In this paper, we study configuration problems related to the use of this technology to make airport operations more environmentally sustainable. We concentrate on the power supply for apron buses and analyze the location planning problems related to the distribution of the required power supply and the wireless charging units in the apron road system. To this end, we develop a formal optimization model and discuss the first numerical results.

Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China

“…Regarding e-buses, they have distinct operation characteristics which should be considered when locating e-bus charging stations. Previous studies have investigated the charging infrastructure planning for e-buses, especially since the advent of wireless charging [18,[28][29][30]. Wireless charging facilities are installed at bus stops, which utilizes bus dwelling time at the stops, or are paved under the roads along bus routes, which can charge e-buses when buses are driving on the roads [31,32].…”

“…In this study, the charging stations which are planned are plug-in charging stations. Currently, there are three charging technologies: battery swapping [14,15], plug-in charging [16,17], and wireless charging [18]. Each has its advantages and disadvantages.…”

“…Better Place, the company once well-known for its battery swapping business model, was shut down in 2013 because few customers had battery-swapping needs. Wireless charging is the most promising technology as it allows charging while driving, and facilities for such charging have been installed on the Korea Advanced Institute of Science and Technology campus and in the Korean city of Gumi [18]. Utah State University also demonstrated dynamic wireless charging technology for an electric bus with a peak power of 25 kW at its test track in 2016 [21].…”

Joint Optimization of Regular Charging Electric Bus Transit Network Schedule and Stationary Charger Deployment considering Partial Charging Policy and Time-of-Use Electricity Prices

“…EB charging infrastructure planning varies with EB's charging strategies similarly. Charging lane EB system mainly pursues an optimal location and length of charging lanes [26,27], whereas EB system with station-based charging modes generally requires optimization of charging station sitting and charging facility scheduling. Among the station-based charging modes, the fast-charging mode is usually linked to the distributed deployment format of the fast-charging station, which was investigated at the transit network level by Wei et al [16].…”

Service assignment decision support of one-way carsharing in wireless charging road network

“…At present, some relevant research on wireless charging has emerged. Jang provides an overview of recent studies about wireless charging and concluded that the current research mainly includes several aspects in [3], such as wireless charging infrastructure allocation, pricing policy like in [4], cost and benefit analysis and other decision supporting like [5]. He et al considered its impact on the traffic capacity of the road network and the route selection of travelers in the WCL location optimization decision and established a nonlinear model in [6].…”