IoT Based Smart Diagnosis in EVs (Electric Vehicles)

Salu K Binu , Sona Saji , Haarrish Sabu

Keywords: Implementation of smart vehicle,Battery Management System, Smart Driving, Battery Usage Data.

Abstract: Electric vehicles (EVs) are becoming increasingly popular due to their environmental benefits and cost savings.However,the complexity of the EV powertrain and its components can make it difficult to diagnose and repair problems.This paper proposes an IoT based smart diagnosis system foe EVs that uses sensors and data analysis to detect and diagnose faults in the EV powertrain.The system uses sensors to collect data from the EV powertrain and then uses machine learning algorithms to analyze the data and detect any anomalies.Internet of Things (IoT) technology to develop a smart diagnosis system for electric vehicles. The system would use sensors to detect and diagnose faults in the vehicle's electrical system, and provide real-time feedback to the driver. The system would be able to detect and diagnose faults in the vehicle's electrical system, and provide real-time feedback to the driver. The system would also be able to detect and diagnose faults in the vehicle's mechanical system.The Internet of Things (IoT) has revolutionized the way we interact with the world around us. It has enabled us to connect with physical objects and systems in ways that were previously impossible. This has opened up a world of possibilities for the automotive industry, particularly in the area of electric vehicles. This paper will discuss the potential of using IoT-based smart diagnosis in electric vehicles.

Published Paper   E-Certificate

"IoT Based Smart Diagnosis in EVs (Electric Vehicles)", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 3, page no.1382 - 1383, March-2023, Available :https://ijsdr.org/papers/IJSDR2303233.pdf

Volume 8 Issue 3, March-2023

Pages : 1382 - 1383

Paper Reg. ID: IJSDR_204961

Published Paper Id: IJSDR2303233

Downloads: 000347540

Research Area: Engineering

Country: -, -, -

Published Paper PDF: https://ijsdr.org/papers/IJSDR2303233

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2303233

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition