Remaining Useful Life Predictions in Lithium-ion Battery under Composite Condition

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Published Oct 3, 2016
Yejin Kim Jongsoo Lee

Abstract

In these days, there is a tendency that research of Prognostics and Health Management (PHM) of lithium-ion battery that prevent accidents in advance by predicting the Remaining Useful Life (RUL). However, there is a difficulty in battery evaluation for composite condition of an operating conditions and a storage conditions, due to the time consuming. Research on the RUL of lithium-ion battery in composite condition are progressing by combining an operating condition and a storage condition. Conventional method such as Miner’s Rule may not fully meet the needs of battery evaluation for RUL. Because it does not take into account overloads caused by a variable amplitude loading history. In order to solve the problem of accurately predicting the RUL of lithium-ion battery, two approaches applied to predicting the RUL of lithium-ion battery. We demonstrate the usefulness of two proposed methods by comparing with real-data of composite condition.

How to Cite

Kim, Y., & Lee, J. (2016). Remaining Useful Life Predictions in Lithium-ion Battery under Composite Condition. Annual Conference of the PHM Society, 8(1). https://doi.org/10.36001/phmconf.2016.v8i1.2579
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Keywords

PHM, Lithium-ion battery, Composite condition, capacity prediction, RUL(Remaining Useful Life)

References
Cho, M., Son, Y. M., Nah, D. B., Kil, S. C. and Kim, S. W. (2010). Lithium-Ion Batteries for Plug-In Hybrid Electric Vehicle. Journal of Energy Engineering. Vol.19, No. 2, pp. 81-91.
Goebel, K., Saha, B., Saxena, A., Celaya, J. R. and Christophersen, J. P. (2008). Prognostics in Battery Health Management. IEEE Instrumentation & Measurement Magazine. pp. 33-40.
Arenas. A. C., Onori. S., Guezennec. Y., Rizzoni. G. (2015). Capacity and power fade cycle-life model for plug-in hybrid electric vehicle lithium-ion battery cells containing blended spinel and layered-oxide positive electrodes. Journal of Power Sources. Vol.278, pp. 473-483
Zackrisson. M., Avellan. L., Orlenius. J. (2010). Life cycle assessment of lithium-ion batteries for plug-in hybrid electric. Journal of Cleaner Production. Vol.18, Issue.15, pp. 1519-1529
Xiong. R., He. H., Sun. F., Liu. X., Liu. Z. (2013). Model-based state of charge and peak power capability joint estimation of lithium-ion battery in plug-in hybrid electric vehicles. Journal of Power Sources. Vol.229, pp. 159-169
Jung. H. B., Kim. Y. C., Lee. Y. S. (2010). A multiple model SOC estimation of Li-ion battery in Real time. The Korean Institute of Electrical Engineers Conference. June, pp. 1746-1747
Choi. H. R., Ban. H. S., Mok. H. S. Shin. W. S., Ko. J. M. (2000). A study of Electrical Modeling for Charge/Discharge Analysis of li-polymer Battery. The Korean Institute of Power Electronics. Vol.5, pp. 435-442
Kim. H., Heo. S., Kang. G. (2009). Modeling and Characteristic Analysis of HEV Li-ion Battery Using Recursive Least Square Estimation. The Korean Society of Automotive Engineers. Vol.17, pp. 130-136
Sim. S. H., Gang. J. H., An. D., Kim. S. I., Kim. J. Y., Choi. J. H. (2013). Remaining Useful Life Prediction of Li-Ion Battery Based on Charge Voltage Characteristics. The Korean Society of Mechanical Engineering. Vol.37, pp. 313-322
Kim. Y., Yoon. S. (2012). Electrochemical Characterization Methods for Lithium Secondary Batteries. Polymer Science and Technology. Vol.23, No. 3
PNE solution. http://www.pnesolution.com/kor/html/02_pr
oduct/product02.html?m_cate=65#none
Bloom. I., Cole. B. W., Sohn. J. J., Jones. S. A., Polzin. E. G., Battaglia. V. S., Henriksen. G. L., Motloch. C., Richardson. R., Unkelhaeuser. T., Ingersoll. D., Case. H. L. (2001). An accelerated calendar and cycle life study of Li-ion cells. Journal of Power Sources. Vol.101, pp. 238-247
Han. X., Ouyang. M., Lu. L., Li. J. (2014). Cycle Life of Commercial Lithium-Ion Batteries with Lithium Titanium Oxide Anodes in Electric Vehicles. Energies. Vol.7, pp. 4895-4909
Ramadass. P., Haran. B., White. R., Popov. B. M. (2003). Journal of Power Sources. Vol.123, pp. 230-240
Ma. H. J., Kim. J. H., Lee. S. J., Kim. C. H. (2013). A Study on Life Cycle Estimation of Battery Using Arrhenius Equation. The Korean Institute of Electrical Engineers Conference. October 31- November 2, pp. 208-210
Feinberg. A., Widom. A. (2000). Thermodynamic Extensions of Miner’s Rule to Chemical Cells. Reliability and Maintainability Symposium. January 24-27, Los Angeles, CA. pp. 341-344
Lv. Z., Huang. H. Z., Zhu. S. P., Gao. H., Zuo. F. (2015). A modified nonlinear fatigue damage accumulation model. International Journal of Damage Mechanics. Vol.24, pp. 168-181
Marano. V Onori. S., Guezennec. Y., Rizzoni. G., Madella. N. (2009). Lithium-ion Batteries Life Estimation for Plug-in Hybrid Electric Vehicles Conference. September 7-10, Dearborn, MI. pp. 536-543 Kim. J. G., Kim. S. H., Bae. S. I., Ham. K. C. Song. J. I. (2002). The effects of random, spectrum of hybrid metal matrix composites on the fatigue life. The Korean Society of Mechanical Engineering Conference. May, pp. 367-372
Kim. J. K., Shim. D. S. (1996). Fatigue Cumulative Damage and Life Prediction of GFRP under Random Loading. The Korean Society of Mechanical. Vol. 20,
Section
Technical Research Papers