Battery state of charge estimation based on a combined model of extended kalman filter and neural networks

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2011, Pages 2156-2163

  Chen, Zhihang ^a   Qiu, Shiqi ^a   Masrur, M Abul ^b   Murphey, Yi Lu ^a  

^a Department of Electrical and Computer Engineering   (United States)

^b U S ARMY TARDEC   (United States)

Author keywords

battery SOC; intelligent battery management; Kalman filtering; neural networks

Indexed keywords

BATTERY MANAGEMENT; BATTERY SOC; BATTERY STATE OF CHARGE; CHARGE AND DISCHARGE; COMBINED MODEL; DYNAMIC SOC; ESTIMATION MODELS; HYSTERESIS EFFECT; KALMAN FILTER AND NEURAL NETWORK; KALMAN-FILTERING; LITHIUM-ION BATTERY; NI-MH BATTERIES; TEMPERATURE DATA;

ESTIMATION; EXTENDED KALMAN FILTERS; HYSTERESIS; LEAD ACID BATTERIES; LITHIUM; OPEN CIRCUIT VOLTAGE; POSITION CONTROL;

NEURAL NETWORKS;

EID: 80054766767     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2011.6033495     Document Type: Conference Paper

References (14)

1. H. Guo, J. Jiang, Z. Wang, "Estimating the State of Charge for Ni-MH Battery in HEV by RBF Neural Network", ISA 2009. International Workshop on Intelligent Systems and Applications, 2009.
2. O. Linda, E. J. William, M. Huff, et al. "Intelligent neural network implementation for SOCI development of Li/CFx batteries", Resilient Control Systems, 2009. ISRCS '09. 2nd International Symposium on (13 August 2009), pp. 57-62.
3. C. Piao, W. Fu, J. Wang, Z. Huang; C. Cho, " Estimation of the state of charge of Ni-MH battery pack based on artificial neural network", INTELEC 2009. 31st International Telecommunications Energy Conference, 2009.
4. G. L. Plett, "Battery management system algorithms for HEV battery state-of-charge and state-of-health estimation", Transworld Research Network
5. S. Piller, M. Perrin, A. Jossen, "Methods for state-of-charge determination and their applications", Journal of Power Sources 96 (2001) 113-120
6. G. L. Plett, "Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 1. Background", J. Power Sources 134 252-61, 2004
7. G. L. Plett, "Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 2. Modeling and identification", J. Power Sources 134 262-76, 2004
8. G. L. Plett, "Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 3. State and parameter estimation", J. Power Sources 134 277-92, 2004
9. J. Wang, B. Cao, Q. Chen, F. Wang, Combined state of charge estimator for electric vehicle battery pack, Control Engineering Practice 15 (2007) 1569-1576.
10. J. Wang, J. Guo, L. Ding, An adaptive Kalman filtering based State of Charge combined estimator for electric vehicle battery pack, Energy Conversion and Management 50 (2009) 3182-3186
11. A. Vasebi, M. Partovibakhsh, S. Mohammad Taghi Bathaee, A novel combined battery model for state-of-charge estimation in lead-acid batteries based on extended Kalman filter for hybrid electric vehicle applications, Journal of Power Sources 174 (2007) 30-40
12. K. S. Ng, C. Moo, Y. Chen, Y. Hsieh, Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithiumion batteries, Applied Energy 86 (2009) 1506-1511
13. http://www.mpoweruk.com/
14. http://www.cs.unc.edu/~welch/kalman/