Name
Abstract | ||
|---|---|---|
Electric vehicle charging strategies rely on knowledge of future vehicle usage, or implicitly make assumptions about a vehicle's usage. For example, a naïve charging strategy may assume that a full charge is required as soon as possible and simply charge at the maximum rate when plugged in, whereas a smart strategy might make use of the knowledge that the vehicle is not needed for a number of hours and optimise its charging behaviour to minimise its impact on the electricity grid. These charging strategies may also offer vehicle-to-grid services. To achieve this functionality, a driver needs to specify the details of the next trip---or sequence of trips---in order for the charging strategy to perform optimally. This paper explores the value of next-trip information, and presents a potential user interface to assist a driver with providing these details. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2598153.2602229 | AVI |
Keywords | Field | DocType |
design,human factors,smart charging,v2g,graphical user interfaces,smart grid,electric vehicles | Electricity grid,Smart grid,Computer science,Electric vehicle,Human–computer interaction,User interface,Online charging system,Embedded system,Distributed computing | Conference |
Citations | PageRank | References |
1 | 0.40 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul Monigatti | 1 | 10 | 1.95 |
| Mark D. Apperley | 2 | 115 | 19.19 |
| Bill Rogers | 3 | 112 | 19.17 |