Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Conference Proceedings
Publisher : IEEE
Source : International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) (pp. 238-244). IEEE
Url : https://ieeexplore.ieee.org/document/9967510
Campus : Bengaluru
School : School of Engineering
Department : Electrical and Electronics
Year : 2022
Abstract : Automotive consumers easily adapt to E-vehicles, and this is because of their low-cost maintenance and stable electricity charge rates. Apart from designing and manufacturing E-vehicles, there is an essential need to build an infrastructure that can provide an interface to communicate with the charging stations and also enhance the conveyance. The proposed design features the ideology of enhancing the EV-infrastructure, where a charging station is recommended and E-vehicle is scheduled using the FCFS algorithm by considering different scenarios and metrics, keeping SOC as a constraint. Also, the shortest path for the same is proposed by comparing the Dijkstra and ACO algorithms. The model is anticipated to devise an optimal and feasible path for an E-vehicle to travel towards the recommended charging station by providing optimal information to the EV-driver to recharge the E-vehicle during his journey. The entire simulation for the proposed design is carried out in MATLAB R2021b.
Cite this Research Publication : Nair, A.H.P. and Sujith, M., 2022, September. Comparative Path Planning Analysis for the Recommended E-Vehicle Charging Station. In 2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) (pp. 238-244). IEEE