A Battery Management System Using Interleaved Pulse Charging with Charge and Temperature Balancing Based on NARX Network

Tsung Wen Sun, Tsung Heng Tsai*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper proposes a battery management system, including a fast battery charger, battery aging diagnosis, and charge estimation and balancing. The charger adopts a single-inductor single-input dual-output architecture to achieve charge balancing among battery cells. Interleaved pulse charging is proposed to reduce the charging time and slow down the aging process of batteries as well. This method also significantly suppresses the variations of the temperature of battery cells and is beneficial to the implementation of charge balancing. An artificial neural network is proposed to detect the state of health (SOH) of battery cells and improve the accuracy of the state of charge (SOC) estimation. The prototype is implemented in TSMC 0.35-μm process and TensorFlow tools are used. Measurement results show that the interleaved pulse charging reduces 30% variation of the battery temperature and saves 24% charging time when charging four battery cells concurrently. A mean absolute error of SOC estimation of 0.35% is achieved in this work.

Original languageEnglish
Pages (from-to)1811-1819
Number of pages9
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Volume69
Issue number4
DOIs
StatePublished - 1 Apr 2022

Keywords

  • Battery aging detection
  • Battery charger
  • Charge balancing
  • Nonlinear autoregressive with exogenous inputs model (NARX) neural network
  • Pulse charging
  • Temperature balancing
  • Unmanned aerial vehicle (UAV)

Fingerprint

Dive into the research topics of 'A Battery Management System Using Interleaved Pulse Charging with Charge and Temperature Balancing Based on NARX Network'. Together they form a unique fingerprint.

Cite this