TR2014-056

Fast UD Factorization-Based RLS Online Parameter Identification for Model-Based Condition Monitoring of Lithium-ion Batteries


    •  Kim, T.; Wang, Y.; Sahinoglu, Z.; Wada, T.; Hara, S.; Qiao, W., "Fast UD Factorization-based RLS Online Parameter Identification for Model-based Condition Monitoring of Lithium-ion Batteries", American Control Conference (ACC), DOI: 10.1109/ACC.2014.6859108, ISSN: 0743-1619, ISBN: 978-1-4799-3272-6, June 2014, pp. 4410-4415.
      BibTeX Download PDF
      • @inproceedings{Kim2014jun,
      • author = {Kim, T. and Wang, Y. and Sahinoglu, Z. and Wada, T. and Hara, S. and Qiao, W.},
      • title = {Fast UD Factorization-based RLS Online Parameter Identification for Model-based Condition Monitoring of Lithium-ion Batteries},
      • booktitle = {American Control Conference (ACC)},
      • year = 2014,
      • pages = {4410--4415},
      • month = jun,
      • publisher = {IEEE},
      • doi = {10.1109/ACC.2014.6859108},
      • issn = {0743-1619},
      • isbn = {978-1-4799-3272-6},
      • url = {http://www.merl.com/publications/TR2014-056}
      • }
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  • Research Areas:

    Dynamical Systems, Electronics & Communications, Mechatronics, Power, Predictive Modeling


This paper proposes a novel parameter identification method for model-based condition monitoring of lithium-ion batteries. A fast UD factorization-based recursive least square (FUDRLS) algorithm is developed for identifying time-varying electrical parameters of a battery model. The proposed algorithm can be used for online state of charge, state of health and state of power estimation for lithium-ion batteries. The proposed method is more numerically stable than conventional recursive least square (RLS)-based parameter estimation methods and faster than the existing UD RLS-based method. Moreover, a variable forgetting factor (VF) is included in the FUDRLS to optimize its performance. Due to its low complexity and numerical stability, the proposed method is suitable for the real-time embedded Battery Management System (BMS). Simulation and experimental results for a polymer lithium-ion battery are provided to validate the proposed method.