Towards Real-Time Estimation of Li-ion Battery Characteristics for BMS with Storage-Limited Processors

Zhansheng Ning*, S. Azizighalehsari, P. Venugopal, G. Rietveld, T. Batista Soeiro

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
60 Downloads (Pure)

Abstract

In order to improve the efficiency and extend the cycle life of battery systems, accurate estimation algorithms implemented in battery management systems (BMS) are crucial to calculate critical battery performance indices. Real-time state of charge (SOC) and battery capacity determination are vital for battery diagnostics and prognostics and are the core function of these algorithms. However, the present typical algorithms are difficult to implement in BMS designed with computation- and storage-limited processors. Therefore, it is essential to investigate different real-time estimation algorithms' accuracy and computational complexity. After a summary and classification of various SOC and SOH estimation methods, a typical online adaptive model-based state observer framework for SOC and battery capacity estimation is proposed, and their algorithm accuracy and complexity are compared using the processor-in-the-loop (PIL) test. In particular, a co-estimation algorithm combining recursive least squares with the forgetting factor (FF-RLS) and dual-central differential Kalman filter (CDKF) is implemented, resulting in a mean absolute error of less than 0.62 % for SOC and a mean absolute relative error of less than 1.39 % for SOH.

Original languageEnglish
Title of host publication2023 IEEE 8th Southern Power Electronics Conference and 17th Brazilian Power Electronics Conference (SPEC/COBEP)
Place of PublicationPiscataway, NJ
PublisherIEEE
Number of pages7
ISBN (Electronic)979-8-3503-2112-8
ISBN (Print)979-8-3503-2113-5
DOIs
Publication statusPublished - 2023
Event8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC/COBEP 2023 - Florianopolis, Brazil
Duration: 26 Nov 202329 Nov 2023
Conference number: 6

Publication series

NameIEEE Southern Power Electronics Conference and Brazilian Power Electronics Conference (SPEC/COBEP)
PublisherIEEE
Volume2023
ISSN (Print)2832-2983

Conference

Conference8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC/COBEP 2023
Abbreviated titleSPEC/COBEP
Country/TerritoryBrazil
CityFlorianopolis
Period26/11/2329/11/23

Keywords

  • Battery
  • Battery capacity
  • Processor-in-the-Loop (PIL) test
  • SOC
  • State observer
  • 2024 OA procedure

Fingerprint

Dive into the research topics of 'Towards Real-Time Estimation of Li-ion Battery Characteristics for BMS with Storage-Limited Processors'. Together they form a unique fingerprint.

Cite this