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STATE OF HEALTH DETERMINATION OF LITHIUM ION CELLS IN AND OUTSIDE THE VEHICLE
Technical Paper
2011-39-7235
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
There is an enormous effort to implement safety functionality into battery systems to prevent any accidents with the poisonous and inflammable ingredients of the electrolytes and electrode materials. But not only the safety regulation for lithium ion batteries will be different in comparison to the home electronics application, also the operating strategy must be different to guaranty the required lifetime in the automotive industry up to 10-12 years. This paperwork will show an approach to get offline (on test benches) and/or online (installed inside the car) information regarding the current healthy and state inside the cell. As an approach modeling of physical effects by the help of electro impedance spectroscopy (EIS) will be applied. The test results of cells with different parameters (supplier, cell chemistry, capacity…) will be shown in this paperwork and the conclusion is derived how this could be used to compare different cells with identical attributes (aging effects, production variations) or different attributes (benchmarking).
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Mueller, K., Tittel, D., Zecheng, S., and Feng, L., "STATE OF HEALTH DETERMINATION OF LITHIUM ION CELLS IN AND OUTSIDE THE VEHICLE," SAE Technical Paper 2011-39-7235, 2011, https://doi.org/10.4271/2011-39-7235.Data Sets - Support Documents
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References
- Fuller, Thomas F. Doyle, Marc Newmann, John Simulation and optimization of the dual lithium ion insertion cell Journal of the Electrochemical Society 1994 141 1 10.x
- Rakhmatov, Daler/Vrudhula Sama: An analytical high-level battery model for use in energy management of portable electronic systems Proceedings of the 2001 IEEE/ACM international conference on Computer-aided de-sign 2001 8C 488 493
- Spotnitz, R. Simulation of capacity fade in lithium-ion batteries Journal of Power Sources 2003 1 113 72 80
- Tröltzsch, U. Kanoun, O. Tränkler, H.-R. Diagnose von Gerätebatterien mit Impedanzspektrometrie Technisches Messen 71 509 518 2004
- Plett, G. Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Part 2. Modeling and identification Journal of Power Sources 134 262 276 2004
- Randles, J.E.B. Kinetics of rapid electrode reactions Discussion of the Faraday Society 1 11 19 1947
- De Levie, R. Electrochemical response of porous and rough electrodes Advances in Electrochemistry and Electrochemical Engineering 6 329 397 1967
- Botte, G. G. et al. Mathematical modeling of secondary lithium batteries Electrochimica Acta 45 2595 2609 2000
- Gomadam, P. M. et al. Mathematical modeling of lithium-ion and nickel battery systems Journal of Power Sources 110 267 284 2002
- Kanoun, O. et al. Benefits of evolutionary strategy in modeling of impedance spectra Electrochimica Acta 51 1453 1461 2006
- Lasia, A. Modeling of Impedance of Porous Electrodes in Modern Aspects of Electrochemistry Springer 67 137 2009
- Do, D. V. et al. Impedance Observer for a Li-Ion Battery Using Kalman Filter IEEE Transactions on Vehicular Technology 58 3930 3937 2009
- Danzer, M. A. Electrochemical parameter identification - An efficient method for fuel cell impedance characterization Journal of Power Sources 183 55 61 2008
- Tröltzsch, U. Modellbasierte Zustandsdiagnose von Gerätebatterien PhD Thesis Universität der Bundeswehr 59 ff 2005
- Smola, A. J. et al. A Tutorial on Support Vector Regression, NeuroColt2- TR 1998-030 report 1998
- MacDonald, J. R. Applicability and power of complex nonlinear least squares for the analysis of impedance and admittance data Journal of Electroanalytical Chemistry 131 77 95 1982
- Boukamp, B. A. A nonlinear least squares fit procedure for analysis of immittance data of electrochemical systems Solid State Ionics 20 31 44 1986
- Vandernoot, T. J. et al. The use of genetic algorithms in the nonlinear regression of immitance data Journal of Electroanalytical Chemistry 448 17 23 1998
- Bello, A. et al. Distribution of relaxation times from dielectric spectroscopy using Monte Carlo simulated annealing: Application to α-PVDF Physical Review B 60 12764 12774 1999
- Lee, Jaemoon Nama, Oanyong Choa, B. H. Li-ion battery SOC estimation method based on the reduced order extended Kalman filtering Jour-nal of Power Sources 2007 1 174 9 15
- Plett, Gregory L. Dual and Joint EKF for Simultaneous SOC and SOH Estimation EVS21 2005 1 12
- Xuyun, Feng/Zechang Sun: A battery model including hysteresis for State-of-Charge estimation in Ni-MH battery Vehicle Power and Propulsion Conference, 2008. VPPC ‘08 IEEE 2008 1 5
- VDA VDA test specification for li-ion battery systems for hybrid electric vehicles 2007 1 45