Experimental study and empirical modeling of lithium ion battery lifetime

Document Type : Chemistry Article

Authors

1 Department of Energy, Institute of Mechanics, Iranian Space Research Center, Shiraz, Iran

2 Energy Department, Institute of Mechanics, Iranian space research center, Shiraz, Iran

Abstract

The capacity loss of lithium ion batteries during charge/discharge cycles is one of the important parameters in the evaluation of these kind of batteries, so that battery lifetime is defined as the number of charge/discharge cycles until the battery capacity reaches to 70% of its initial capacity. Therefore, it is important to have a simple mathematical model which can easily predict capacity loss of lithium ion batteries with acceptable accuracy. In this study, capacity loss were measured experimentally for first 10 cycles of Samsung commercial lithium ion battery at three temperatures of 25, 35 and 45oC. Further, a semi empirical model has been introduced including power law concept for temperature and the square root of cycle number to predict the lithium-ion battery lifetime or capacity loss. The parameters of the model have been obtained based on square of error of the prediction of experimental capacity using Levenberg -Marquardt algorithm. Using this model, maximum charge/discharge cycle of the battry is calculated acceptably with less than 15% of error.

Keywords

Main Subjects

References

1] A. J. Crawford, Q. Huang, M. C. Kintner-Meyer, J.-G. Zhang, D. M. Reed, V. L. Sprenkle, et al. , 2018, "Lifecycle comparison of selected Li-ion battery chemistries under grid and electric vehicle duty cycle combinations", Journal of Power Sources, vol. 380, pp. 185-193.
[2] D. Liu, W. Xie, H. Liao, and Y. Peng, 2015, "An integrated probabilistic approach to lithium-ion battery remaining useful life estimation," IEEE Transactions on Instrumentation and Measurement, vol. 64, pp. 660-670.
[3] D. Liu, H. Wang, Y. Peng, W. Xie, and H. Liao, 2013, "Satellite lithium-ion battery remaining cycle life prediction with novel indirect health indicator extraction," Energies, vol. 6, pp. 3654-3668.

[4] احمدی، س؛ بطحایی، م،ت؛ 1396، " مدل‌سازی و شبیه‌سازی راهبردهای بهینه ی مدیریت انرژی در خودروی هیبرید پیل سوختی"، مجله مدل سازی در مهندسی، دوره 15، شماره 50، 1-16.

[5] S. Ramakrishnan, S. Venugopalan, and A. E. Jeyakumar, 2010, "Prediction of Retained Capacity and EODV of Li-ion Batteries in LEO Spacecraft Batteries," arXiv preprint arXiv:1004.448.

[6]  ﻛﺮﻳﻤﻲ‌زاد ﮔﻮﻫﺮی، ف؛ ﺷﺎﻫﺴﻮﻧﺪ، ا؛  علی‌خان محمدآباد، ص؛ 1390، "ﺑﺮرﺳﻲ ﺗﺠﺮﺑﻲ ﻣﺪل و  ﺳﺎزی  اﻧﺘﻘﺎل ﺟﺮم و اﻧﺘﻘﺎل ﺣﺮارت ﻫﻤﺰﻣﺎن در ﻛﺎﻧﺎل اﻓﻘﻲ ﻫﻤﺮاه ﺑﺎ اﺛﺮات دﻳﻮاره"، مجله مدل سازی در مهندسی، دوره 9، شماره 24، 84-95 .

 

[7] ﻛﺮﻳﻤﻲ‌زاد ﮔﻮﻫﺮی، ف؛ ﺷﺎﻫﺴﻮﻧﺪ، ا؛ 1392، " ﻣﻘﺎﻳﺴﻪ ﻧﺘﺎﻳﺞ ﺣﺎﺻﻞ از ﺷﺒﻜﻪ در ﭘﻴﺶ RBF  وMLP  ﻫﺎی ﻋﺼﺒﻲ ﺑﻴﻨﻲ ﻧﺘﺎﻳﺞ ﺣﺎﺻﻞ از ﻫﻤﺰﻣﺎﻧﻲ ﭘﺪﻳﺪه ﻫﺎی اﻧﺘﻘﺎل ﺟﺮم و اﻧﺘﻘﺎل ﺣﺮارت"، مجله مدل سازی در مهندسی، دوره 11، شماره 33، 27-43.

 
 [8] P. Rong and M. Pedram, 2006, "An analytical model for predicting the remaining battery capacity of lithium-ion batteries," IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 14, pp. 441-451.
[9] E. Sarasketa-Zabala, E. Martinez-Laserna, M. Berecibar, I. Gandiaga, L. Rodriguez-Martinez, and I. Villarreal, 2016, "Realistic lifetime prediction approach for Li-ion batteries," Applied Energy, vol. 162, pp. 839-852.
[10]  M. Abe, K. Nishimura, S. E. Seki, H. Haruna, T. Hirasawa, S. Ito, 2012, "Lifetime prediction for heavy-duty industrial lithium-ion batteries that enables highly reliable system design," Hitachi Review, vol. 61, p. 259.
 [11] M. Hu, J. Wang, C. Fu, D. Qin, and S. Xie, "Study on Cycle-Life Prediction Model of Lithium-Ion Battery for Electric Vehicles," International Journal of Electrochemical Science, vol. 11, pp. 577-589, 2016.
[12] J. Schmalstieg, S. Käbitz, M. Ecker, and D. U. Sauer, "From accelerated aging tests to a lifetime prediction model: Analyzing lithium-ion batteries," in Electric Vehicle Symposium and Exhibition (EVS27), 2013 World, 2013, pp. 1-12: IEEE.
[13] M. Ecker et al., "Development of a lifetime prediction model for lithium-ion batteries based on extended accelerated aging test data," Journal of Power Sources, vol. 215, pp. 248-257, 2012.
[14] V. Ramadesigan, P. W. Northrop, S. De, S. Santhanagopalan, R. D. Braatz, and V. R. Subramanian, 2012, "Modeling and simulation of lithium-ion batteries from a systems engineering perspective," Journal of The Electrochemical Society, vol. 159, pp. R31-R45.
[15] D. Marquardt, 1963, "An algorithm for least squares estimation of nonlinear parameters," SIAM Journal of Applied mathematics, vol. 11, pp. 431-441.
[16] E. B. Division, 2010,  "Specification of Product for Lithium-ion Rechargeable Cell- Model : ICR18650-30B," L. Samsung SDI Co. ,first edition.
Journal of Modeling in Engineering
Volume 16, Issue 55
December 2018
Pages 35-40

Files

History

  • Receive Date: 12 December 2017
  • Revise Date: 08 April 2018
  • Accept Date: 15 April 2018

Share

How to cite

Statistics