Work

Using Electric Vehicle Driver’s Driving Mode for Trip Planning and Routing

Year: 2024

Type: article

Abstract: With the increasing adoption of electric vehicles worldwide, some limitations have emerged in their usage. The main limitations include low autonomy and a scarcity of charging points. In this work, we describe a software architecture for planning a stop at charging stations along a trip, by prediction of battery charge to be spent along the path. We describe the main components of this architecture and evaluate regression methods for the car consumption prediction module. We also use a real dataset built from an electric vehicle usage to validate the architecture concept and its viability analyzing multiple linear regression machine learning models. To further validate the architecture, we make comparisons between simulated and a real trips.

Source: Journal of Internet Services and Applications

DOI: 10.5753/jisa.2024.3805

Authors: Marcelo Dos-Reis, Celso Iwata Frison, Fabiano Costa Teixeira, Humberto Torres Marques-Neto

Institution: Pontifícia Universidade Católica de Minas Gerais

Language: English

Topic: Electric Vehicles and Infrastructure

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $1,490