ElBanhawy, Eiman (2015) To understand, model and design an e-mobility system in its urban context. Doctoral thesis, Northumbria University.
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Abstract
The electric vehicles (EVs) are emerging as an alternative solution to the conventional gasoline vehicles. The EV market faces different issues related to limited range, which are associated with the battery technology and the charging network. A clear emphasis is placed on how well the supporting recharging facilities (RFs) are deployed in order to reduce the limited range. The aim of this study is to investigate how suitably the locations for RFs can be chosen in order to satisfy the demand. Charging demand is a multifaceted problem, the majority of them charge at home and do not experience the maximum range of the EV in an attempt to avoid being stranded with a flat battery, and the deployment of rapid chargers is costly. A desired balance between supply and demand can be achieved by identifying the most influential factors affecting the design and use of the RFs. The fundamental monitoring of the use of RFs would reflect the quality of design, highlight the emerging design needs, and assist with the strategic deployment of the RFs. The interest in alternative transport is shaped primarily by consumer perceptions and users’ feedback. This thesis integrates visual and statistical elements in order to understand the end-‐user emerging design needs and to model the RFs. In this thesis, over 12,725 charging events were analysed in conjunction to 20 interviews with EV users and stakeholders. With the use of an agent-‐based modelling technique, it has been possible to capture and simulate the electric-‐mobility system. By means of integrated spatiotemporal modelling, the results indicated that the proposed model is capable of identifying candidate locations for deploying RFs. A multi method approach is presented to understand the concepts of, model and design the RFs. The outcome of this research should be of interest to planning authorities and policy makers of alternative means of transport.
Item Type: | Thesis (Doctoral) |
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Uncontrolled Keywords: | Agent architecture, charging behaviour, charging infrastructure, clustering analysis, EV users, recharging facilities, simulation modelling, space syntax |
Subjects: | K400 Planning (Urban, Rural and Regional) |
Department: | Faculties > Engineering and Environment > Architecture and Built Environment University Services > Graduate School > Doctor of Philosophy |
Depositing User: | Becky Skoyles |
Date Deposited: | 03 Apr 2017 12:14 |
Last Modified: | 31 Jul 2021 23:09 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/30320 |
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