A New Method of Lithium Battery Power Estimation based on Adaptive Filtering

Author:

Lei Liu1,Ye Liu1

Affiliation:

1. Institute of Oceanographic Instrmentation, Qilu University of Technology (Shandong Academy of Sciences) and Shandong Provincial Key Laboratory of Ocean Enviromental Monitoring Technology and National Engineering and Technological Research Center of Marine Monitoring Equipment, Qingdao, Shandong province, China

Publisher

ACM

Reference23 articles.

1. Journal of Power Sources Journal of Power Sources Y Wang C. Zhang Z. Chen A method for state-of-charge estimation of LiFePO4 batteries at dynamic currents and temperatures using particle filter[J] 2015

2. 2013. Battery state of the charge estimation using Kalman filtering[J];Mastali M.;Journal of Power Sources,2013

3. 2012. Battery Cell Identification and SOC Estimation Using String Terminal Voltage Measurements[J];Wang L. Y.;IEEE Transactions on Vehicular Technology,2012

4. Journal of Tsinghua University Journal of Tsinghua University L. I. Zhe L. U. Languang M. Ouyang Comparison of methods for improving SOC estimation accuracy through an ampere-hour integeration approach[J] 2010

5. IEEE Computer Society IEEE Computer Society D. Haifeng W. Xuezhe S. Zechang State and Parameter Estimation of a HEV Li-ion Battery Pack Using Adaptive Kalman Filter with a New SOC-OCV Concept[C]// International Conference on Measuring Technology & Mechatronics Automation 2009

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