Real-time estimation of battery internal temperature based on a simplified thermoelectric model

Cheng Zhang, Kang Li, Jing Deng

Research output: Contribution to journalArticle

41 Citations (Scopus)

Abstract

Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.
Original languageEnglish
Pages (from-to)146-154
Number of pages9
JournalJournal of Power Sources
Volume302
Early online date27 Oct 2015
DOIs
Publication statusPublished - 20 Jan 2016
Externally publishedYes

Keywords

  • LiFePO4/C battery
  • Internal temperature estimation
  • Simplified thermoelectric model
  • Extended Kalman filter

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