Original paper

A machine learning-based framework for online prediction of battery ageing trajectory and lifetime using histogram data

Volume: 526, Pages: 231110 - 231110
Published: Apr 1, 2022
Abstract
Accurately predicting batteries’ ageing trajectory and remaining useful life is not only required to ensure safe and reliable operation of electric vehicles (EVs) but is also the fundamental step towards health-conscious use and residual value assessment of the battery. The non-linearity, wide range of operating conditions, and cell to cell variations make battery health prediction challenging. This paper proposes a prediction framework that is...
Paper Details
Title
A machine learning-based framework for online prediction of battery ageing trajectory and lifetime using histogram data
Published Date
Apr 1, 2022
Volume
526
Pages
231110 - 231110
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.