Battery state-of-charge estimation using approximate least squares

Research output: Contribution to journalArticlepeer-review

Abstract

In recent years, much effort has been spent to extend the runtime of battery-powered electronic applications. In order to improve the utilization of the available cell capacity, high precision estimation approaches for battery-specific parameters are needed. In this work, an approximate least squares estimation scheme is proposed for the estimation of the battery state-of-charge (SoC). The SoC is determined based on the prediction of the battery's electromotive force. The proposed approach allows for an improved re-initialization of the Coulomb counting (CC) based SoC estimation method. Experimental results for an implementation of the estimation scheme on a fuel gauge system on chip are illustrated. Implementation details and design guidelines are presented. The performance of the presented concept is evaluated for realistic operating conditions (temperature effects, aging, standby current, etc.). For the considered test case of a GSM/UMTS load current pattern of a mobile phone, the proposed method is able to re-initialize the CC-method with a high accuracy, while state-of-the-art methods fail to perform a re-initialization.
Original languageEnglish
Pages (from-to)274-286
Number of pages13
JournalJournal of Power Sources
Volume278
DOIs
Publication statusPublished - 15 Mar 2015

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

Fields of science

  • 202017 Embedded systems
  • 202036 Sensor systems
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202015 Electronics
  • 202022 Information technology
  • 202023 Integrated circuits
  • 202025 Power electronics
  • 202027 Mechatronics
  • 202028 Microelectronics
  • 202037 Signal processing
  • 202041 Computer engineering

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Mechatronics and Information Processing

Cite this