A decentralized deadline-driven electric vehicle charging recommendation
- Submitting institution
-
Nottingham Trent University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2 - 701558
- Type
- D - Journal article
- DOI
-
10.1109/jsyst.2018.2851140
- Title of journal
- IEEE Systems Journal
- Article number
- -
- First page
- 3410
- Volume
- 13
- Issue
- 3
- ISSN
- 1937-9234
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
A - Computing and Informatics Research Centre
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This electric vehicle charging station recommendation technique allows the utilization of mobile edge computing for promoting E-Mobility in smart city environment. The work has led an industry collaboration with an EV service provider, Franklin Energy (Robert Byrne, CEO, robert.byrne@franklinenergy.co.uk). The technique has been utilized as software product by the company for recommending charging stations to EV drivers. The collaboration has enlarged as a consortium including Transport for Greater Manchester (Liam Potts, project director, liam.potts@tfgm.com) and CleanCar (Alexander Baker, CEO CleanCar, alex@cleancar.io). The consortium has recently submitted an E-Mobility infrastructure development bid CANAL+ with Innovate UK.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
