EV Lithium Ion Battery Fault Diagnosis Dataset
Published: 27 June 2024| Version 1 | DOI: 10.17632/t42ynjk936.1
Contributors:
Venkataramana Veeramsetty, , Description
To train and test two ANN models, two separate datasets are developed based on battery modelling in MATLAB. State of Charge (SOC), Temperature and Voltage are the input features in both datasets. Where as against output label column in first dataset 0 represents healthy battery and 1 represents unhealthy battery. Similarly in second dataset 0 represents healthy battery and 1 represents battery has over discharge fault in battery and 2 indicates short circuit fault in the battery.
Files
Steps to reproduce
This data may be used to other researchers who are working on EV battery faults diagnosis using artificial intelligence
Institutions
SR Engineering College
Categories
Battery Charging, Electric Vehicles, Deep Learning, Fault Diagnosis