Sept. 13, 2022, 1:15 a.m. | Pengyu Fu, Liang Chu, Zhuoran Hou, Jincheng Hu, Yanjun Huang, Yuanjian Zhang

cs.CV updates on arXiv.org arxiv.org

In recent years, significant progress has been made in transportation
electrification. And lithium-ion batteries (LIB), as the main energy storage
devices, have received widespread attention. Accurately predicting the state of
health (SOH) can not only ease the anxiety of users about the battery life but
also provide important information for the management of the battery. This
paper presents a prediction method for SOH based on Vision Transformer (ViT)
model. First, discrete charging data of a predefined voltage range is used …

arxiv batteries health prediction state transfer transfer learning transformer vision

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Stagista Technical Data Engineer

@ Hager Group | BRESCIA, IT

Data Analytics - SAS, SQL - Associate

@ JPMorgan Chase & Co. | Mumbai, Maharashtra, India