Research Objective:
Accurate estimation of vehicle’s energy consumption is a demanding task. However, it might be critical for electric vehicles compared to conventional vehicles because of their limited travel range. Moreover, accurate simulation in real-life driving situations depends on a number of uncertainties such as weather, wind speed, road condition, etc. The aim of this project is to:
- Introduce a better approach that can minimise energy consumption/emission for different types of electric vehicle (EV)
- test and simulate the developed scheme to predict the accurate energy demand on a large scale in the aspect of real-life driving conditions with a vehicle routing problem
- develop a standard method for driving range while considering affects of wind with other external sources that could play a crucial role in order to mitigate range anxiety as well.
Estimation of consumed energy in electric vehicles is still a developing process. A proper solution is required for both the sense and adaptation technology. This research will cover experimental, analytical and numerical solutions for EVs in terms of energy consumption, considering parameters like wind speed, velocity and range of vehicle, which can aid the energy sector and routing applications. The proposed method is highly beneficial to the road transport, logistics and distribution field. Apart from that, some advanced technology, including artificial intelligent methods, data logging, and predictive analysis, could be implemented further on environmental effects, i.e., wind parameters while driving. Therefore, this advanced technology could be highly beneficial along with a large body of work on electric vehicles, leading to the estimation of energy consumption with an optimal approach.
Project start date: 14 February, 2022.
Expected completion date: March 2024.
Student Name: Dyuti Paul
Supervisors: Huadong Mo, Saber Elsayed and Ripon K CHakrabortty
