Enabling Unlabelled Field Data for Battery Health Diagnosis by Decoupling Experiment

  • Qiushi Wang
  • , Zhenpo Wang
  • , Peng Liu
  • , Yiwen Zhao
  • , Ni Lin*
  • *Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

There is a rising need for accurate battery state of health (SOH) diagnosis in electric vehicle maintenance and second-life evaluation. However, existing methods suffer from the transition from cell-level tests to realworld vehicle applications due to the ignorance of incorporating laboratory tests with large-scale, timevarying field data. This paper proposes a framework combining the system-level capacity calculation and celllevel decoupling experiment for battery system capacity diagnosis. A modified regional capacity calculation method for online applications is presented, and the regional capacity of the battery under various temperatures and SOHs is experimentally determined to decouple various working conditions. This work highlights the opportunity to integrate laboratory test data to leverage unlabelled field data for capacity diagnosis while revealing the characteristics of battery capacity under different working conditions.

Original languageEnglish
JournalEnergy Proceedings
Volume36
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event9th Applied Energy Symposium: Low Carbon Cities and Urban Energy Systems, CUE 2023 - Tokyo, Japan
Duration: 2 Sept 20237 Sept 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Lithium-ion batteries
  • decoupling experiment
  • electric vehicles
  • field data
  • health diagnosis

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