On-board state-of-health monitoring of lithium-ion batteries using linear parameter-varying models

Journal of Power Sources

Volumn 239, Issue , 2013, Pages 689-695

  Remmlinger, Jürgen ^a   Buchholz, Michael ^a   Soczka Guth, Thomas ^b   Dietmayer, Klaus ^a  

^a UNIVERSITY OF ULM   (Germany)

^b Deutsche ACCUmotive GmbH and Co KG   (Germany)

Author keywords

Internal resistance; Lithium ion battery; LPV model; Non linear Kalman filter; State of health

Indexed keywords

BATTERY TEMPERATURE; INTERNAL RESISTANCE; LINEAR PARAMETER VARYING; LITHIUM-ION BATTERY; LPV MODELS; MODEL-BASED MONITORING; MONITORING METHODS; STATE OF HEALTH;

C (PROGRAMMING LANGUAGE); HYBRID VEHICLES; LITHIUM BATTERIES; MONITORING;

LEAD ACID BATTERIES;

EID: 84887109777     PISSN: 03787753     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jpowsour.2012.11.102     Document Type: Article

References (20)

1. J. Remmlinger, M. Buchholz, K. Dietmayer, Methods for monitoring the state of batteries in automotive applications, in: VDE Verlag (Ed.), VDE-Kongress EMobility, 2010.
2. J. Zhang, and J. Lee A review on prognostics and health monitoring of Li-ion battery Journal of Power Sources 196 2011 6007 6014
3. K.B. Hatzell, A. Sharma, H.K. Fathy, Survey of long-term health modeling, estimation, and control of lithium-ion batteries: challenges and opportunities, in: American Control Conference (ACC) 2012.
4. J. Remmlinger, M. Buchholz, M. Meiler, P. Bernreuter, and K. Dietmayer State-of-health monitoring of lithium-ion batteries in electric vehicles by on-board internal resistance estimation Journal of Power Sources 196 2011 5325 5331
5. B.S. Bhangu, P. Bentley, D.A. Stone, C.M. Bingham, State-of-charge and state-of-health prediction of lead-acid batteries for hybrid electric vehicles using non-linear observers, in: Proc. 11th European Conference on Power Electronics and Applications, 2005.
6. G.L. Plett Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs part 3. State and parameter estimation Journal of Power Sources 134 2004 277 292 (Pubitemid 41325995)
7. F. Zhang, G. Liu, L. Fang, Battery state estimation using unscented Kalman filter, in: IEEE International Conference on Robotics and Automation 2009. ICRA '09, 2009, pp. 1863-1868.
8. I.-S. Kim A technique for estimating the state of health of lithium batteries through a dual-sliding-mode observer IEEE Transactions on Power Electronics 25 2010 1013 1022
9. R. Tóth Modeling and Identification of Linear Parameter-Varying Systems 2010 Springer Berlin
10. Y. Hu, and S. Yurkovich Linear parameter varying battery model identification using subspace methods Journal of Power Sources 196 2011 2913 2923
11. J.W. Brewer Kronecker products and matrix calculus in system theory IEEE Transactions on Circuit and Systems 25 9 1978 772 781
12. W.E. Larimore, M. Buchholz, ADAPT-LPV software for identification of nonlinear parameter-varying systems, in: Proceedings of the 16th IFAC Symposium on System Identification (SYSID 2012) 2012, pp. 1820-1825.
13. L. Ljung System Identification: Theory for the User second ed. 1999 Prentice Hall Upper Saddle River
14. M. Buchholz Subspace-Identification zur Modellierung von PEM-Brennstoffzellen-Stacks Schriften des Instituts für Regelungs- und Steuerungssysteme vol. 07 2010 Karlsruher Institut für Technologie, KIT Scientific Publishing Karlsruhe
15. G.L. Plett Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs part 1. Background Journal of Power Sources 134 2004 252 261 (Pubitemid 41325993)
16. G.L. Plett Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs part 2. Modeling and identification Journal of Power Sources 134 2004 262 276 (Pubitemid 41325994)
17. G.L. Plett Sigma-point Kalman filtering for battery management systems of LiPB-based HEV battery packs part 1: introduction and state estimation Journal of Power Sources 161 2006 1356 1368 (Pubitemid 44738778)
18. G.L. Plett Sigma-point Kalman filtering for battery management systems of LiPB-based HEV battery packs part 2: Simultaneous state and parameter estimation Journal of Power Sources 161 2006 1369 1384 (Pubitemid 44738780)
19. R. van der Merwe, Sigma-point Kalman filters for probabilistic inference in dynamic state-space models, Ph.D. thesis, Oregon Health & Science University, 2004.
20. J. Fox Robotergestützte Parameterschätzung für inertiale Messsysteme 2007 Logos Verlag Berlin