A Data Driven Approach for the Degradation of a Lithium-Ion Battery Based on Accelerated Life Test
Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3300394Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 230
 A. Ulvestad, "A Brief Review of Current Lithium Ion Battery Technology and Potential Solid State Battery Technologies," arXiv preprint arXiv:1803.04317, 2018.
 G. Pistoia, Lithium-ion batteries: advances and applications. Newnes, 2013.
 S. Cheng, B. Li, Z. Yuan, F. Zhang, and J. Liu, "Development of a lifetime prediction model for lithium thionyl chloride batteries based on an accelerated degradation test," Microelectronics Reliability, vol. 65, pp. 274-279, 2016.
 W. B. Nelson, Accelerated testing: statistical models, test plans, and data analysis. John Wiley & Sons, 2009.
 E. Nogueira, V. Orlando, J. Ochoa, A. Fernandez, and M. Vazquez, "Accelerated Life Test of high luminosity blue LEDs," Microelectronics Reliability, vol. 64, pp. 631-634, 2016/09/01/ 2016.
 J. Hao, Y. Rui-Qiang, H.-L. Ke, Q. Sun, and L. jing, "Analysis of the reliability of LED lamps during accelerated thermal aging test by online method," Optik, 2018/09/25/ 2018.
 J. Hao, D. Li, C. He, Q. Sun, and H. Ke, "Step-down accelerated aging test for LED lamps based on nelson models," Optik - International Journal for Light and Electron Optics, vol. 149, pp. 69-80, 2017/11/01/ 2017.
 M. Sawant and A. Christou, "Failure modes and effects criticality analysis and accelerated life testing of LEDs for medical applications," Solid-State Electronics, vol. 78, pp. 39-45, 2012/12/01/ 2012.
 M. Yazdan Mehr, M. R. Toroghinejad, F. Karimzadeh, W. D. van Driel, and G. Q. Zhang, "A review on discoloration and high accelerated testing of optical materials in LED based-products," Microelectronics Reliability, vol. 81, pp. 136-142, 2018/02/01/ 2018.
 Y. T. Kim, K.-B. Kim, Y. E. Hyun, I.-J. Kim, and S. Yang, "Simulation study on the lifetime of electrochemical capacitors using the accelerated degradation test under temperature and voltage stresses," Microelectronics Reliability, vol. 55, no. 12, Part B, pp. 2712-2720, 2015/12/01/ 2015.
 J. Virkki, T. Seppälä, L. Frisk, and P. Heino, "Accelerated testing for failures of tantalum capacitors," Microelectronics Reliability, vol. 50, no. 2, pp. 217-219, 2010/02/01/ 2010.
 J. Kim, D. Yoon, M. Jeon, D. Kang, J. Kim, and H. Lee, "Degradation behaviors and failure analysis of Ni–BaTiO3 base-metal electrode multilayer ceramic capacitors under highly accelerated life test," Current Applied Physics, vol. 10, no. 5, pp. 1297-1301, 2010/09/01/ 2010.
 C. Kalaiselvan and L. B. Rao, "Accelerated life testing of nano ceramic capacitors and capacitor test boards using non-parametric method," Measurement, vol. 88, pp. 58-65, 2016/06/01/ 2016.
 W. Gu, Z. Sun, X. Wei, and H. Dai, "A new method of accelerated life testing based on the Grey System Theory for a model-based lithium-ion battery life evaluation system," Journal of Power Sources, vol. 267, pp. 366-379, 2014/12/01/ 2014.
 E. Chiodo, D. Lauria, N. Andrenacci, and G. Pede, "Accelerated life tests of complete lithium-ion battery systems for battery life statistics assessment," in 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2016, 2016.
 K.-J. Chung and C.-C. Hsiao, "Accelerated Degradation Assessment of 18650 Lithium-Ion Batteries," presented at the 2012 International Symposium on Computer, Consumer and Control, 2012.
 E. V. Thomas, H. L. Case, D. H. Doughty, R. G. Jungst, G. Nagasubramanian, and E. P. Roth, "Accelerated power degradation of Li-ion cells," Journal of Power Sources, vol. 124, no. 1, pp. 254-260, 2003/10/01/ 2003.
 K. Takei et al., "Cycle life estimation of lithium secondary battery by extrapolation method and accelerated aging test," Journal of Power Sources, vol. 97-98, pp. 697-701, 2001/07/01/ 2001.
 M. T. Madi, "Step-Stress Accelerated Life Tests," in International Encyclopedia of Statistical Science, M. Lovric, Ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 1514-1517.
 J. Robinson and W. Nelson, Accelerated Testing: Statistical Models, Test Plans, and Data Analysis. 1991, p. 548.
 K. Chung and C. Hsiao, "Accelerated Degradation Assessment of 18650 Lithium-Ion Batteries," in 2012 International Symposium on Computer, Consumer and Control, 2012, pp. 930-933.
 Paul Wagner, "Techniques to evaluate long term aging of systems," D. G. Paul Lein, David Nicholls, Ed., ed, 2011.
 Q. Sun, H.-N. Dui, and X.-L. Fan, "A statistically consistent fatigue damage model based on Miner’s rule," International Journal of Fatigue, vol. 69, pp. 16-21, 2014/12/01/ 2014.
 D. Kececioglu and J. A. Jacks, "The Arrhenius, Eyring, inverse power law and combination models in accelerated life testing," Reliability Engineering, vol. 8, no. 1, pp. 1-9, 1984/01/01/ 1984.
 L. F. Zhang, M. Xie, and L. C. Tang, "A study of two estimation approaches for parameters of Weibull distribution based on WPP," Reliability Engineering & System Safety, vol. 92, no. 3, pp. 360-368, 2007/03/01/ 2007.