Prof. Pecht's new Li-ion battery article now available online

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Professor Pecht has co-authored a new article “Lithium-ion battery health prognosis based on a real battery management system used in electric vehicles” with visiting student Yongzhi Zhang, Hongwen, Ju Wang, and Rui Xiong, Beijing Institute of Technology, and Simin Peng of the Yancheng Institute of Technology. The article is now available online through IEEE Xplore Early Access.


This paper developed an effective health indicator to indicate lithium-ion battery state of health and moving-window-based method to predict battery remaining useful life. The health indicator was extracted based on the partial charge voltage curve of cells. Battery remaining useful life was predicted using a linear aging model constructed based on the capacity data within a moving window, combined with Monte Carlo simulation to generate prediction uncertainties. Both the developed capacity estimation and remaining useful life prediction methods were implemented based on a real battery management system used in electric vehicles. Experimental data for cells tested at different current rates, including 1C and 2C, and different temperatures, including 25 °C and 40 °C, was collected and used. The implementation results show that the capacity estimation errors were within 1.5%. During the last 20% of battery lifetime, the root mean square errors of remaining useful life predictions were within 20 cycles, and the 95% confidence intervals mainly cover about 20 cycles.

Please follow this link for the full article as made available by the publisher.

Published August 9, 2018