• Login
• Admin

SUKKAEW, PAPHATSARA (2019) Modelling highway networks for electric vehicles in the UK. [Dissertation (University of Nottingham only)]

PDF - Registered users only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader Download (4MB)

Abstract

Gases emission of transportation has been one major impact on an environmental issue in the world over the decades. Then, electric vehicles (EVs) has become a significant solution to environmentally friendly issues with renewable energy and zero-emission. However, there are some restrictions on EV deployment in real-world transportation such as battery capacity, long recharging time, and shortage of charging stations. Hence, this study aims to develop an efficient model of highway networks for EVs in the mainland of UK (except Northern Ireland) with the shortest path problem. Heuristics of modeled networks is generated as real as actual road networks in the UK, but it is only considered of main roads (motorways and trunk roads). In practice, a new mathematical model is used for computing the problem instead of generated network because of the impact of variation. All test results from 5 variables, which are random seed, number of node (NoN), percentage of equipped roads (PoB), fluctuation, and energy recharging rate (betta), mainly focus on the percentage of path increase through an acceptable route from source to destination with regular roads and wireless charging roads. The computational results show that more path increases result in more NoN. Whereas, when PoB is larger, the amount of path increase is lower. Moreover, fluctuation has no enough results to summarise its impact. Also, PoB30 and NoN169 have no impact on path increase. To summarise, the largest impacts on path increase of highway networks for EVs in the UK are random seed 3 and NoN 225 which lead the total distance to be longest paths, compared to other variables' effect. In the future, network construction may not cover all update information of road segments which could lead some errors to the model. Moreover, time window and more variable with more test frequency should be considered in formulations of constraints for more reliable.

Item Type:	Dissertation (University of Nottingham only)
Depositing User:	SUKKAEW, Paphatsara
Date Deposited:	02 Dec 2022 15:55
Last Modified:	02 Dec 2022 15:55
URI:	https://eprints.nottingham.ac.uk/id/eprint/58104

Actions (Archive Staff Only)

Edit View