Model-based dynamic power assessment of lithium-ion batteries considering different operating conditions

Xiaosong Hu, Rui Xiong, Bo Egardt

Research output: Contribution to journalArticlepeer-review

114 Citations (Scopus)

Abstract

This paper is concerned with model-based dynamic peak-power evaluation for LiNMC and LiFePO4 batteries under different operating conditions. The battery test and our prior study on linear-parameter-varying (LPV) battery modeling are briefly introduced. The peak-power estimation method that incorporates an explicit prediction horizon and design constraints on the battery current, voltage, and SOC are elaborated, and its computational load is analyzed. The discharge and charge peak powers are quantitatively assessed under different dynamic characterization tests, in which a comparison with the conventional PNGV-HPPC method and approaches using the less accurate models is conducted. The robustness of the peak-power estimation approach against varying battery temperatures and aging levels is investigated. The methods to improve the credibility of the peak-power assessment in the context of battery degradation are explored.

Original languageEnglish
Article number6623096
Pages (from-to)1948-1959
Number of pages12
JournalIEEE Transactions on Industrial Informatics
Volume10
Issue number3
DOIs
Publication statusPublished - Aug 2014

Keywords

  • Battery management system
  • Li-ion battery
  • battery modeling
  • electrified vehicle
  • peak-power assessment

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