Advanced battery management system design for SOC/SOH estimation for e-bikes applications

In this work, state of charge (SOC) and state of health (SOH) estimation algorithms for battery management system are proposed and compared. These algorithms are developed on a battery pack designed specifically for light electric vehicle (electric scooter or bicycles) applications. The advanced battery management system is designed in order to evaluate the instantaneous charge available in the battery and at the same time to monitor the slowly varying battery aging parameters. Two SOC estimation algorithms are proposed: an extended Kalman filter (EKF) and an adaptive extended Kalman filter (AEKF). With the adaptive version of Kalman filter a proper value of the model noise covariance is adaptively set using the information coming from the online innovation analysis. In the second part of this paper, a new estimation algorithm based on least squares is proposed to estimate the battery SOH. A general framework for a combined evaluation of SOC/SOH is discussed.

• Record URL:
  • https://doi.org/10.1504/IJPT.2016.081795
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/17424267
• Supplemental Notes:
  • Copyright © 2016 Inderscience Enterprises Ltd.
• Authors:
  • Taborelli, Carlo
  • Onori, Simona
  • Maes, Sebastien
  • Sveum, Peter
  • Al-Hallaj, Said
  • Al-Khayat, Naz
• Publication Date: 2016

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 325-357
• Serial:
  • International Journal of Powertrains
  • Volume: 5
  • Issue Number: 4
  • Publisher: Inderscience Enterprises Limited
  • ISSN: 1742-4267
  • EISSN: 1742-4275
  • Serial URL: https://www.inderscience.com/jhome.php?jcode=ijpt

Subject/Index Terms

• TRT Terms: Algorithms; Bicycles; Electric batteries; Electric vehicle charging; Scooters
• Subject Areas: Energy; Highways; Pedestrians and Bicyclists; Vehicles and Equipment;

Filing Info

• Accession Number: 01631668
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 31 2017 5:10PM