Battery state-of-health estimation for mobile devices

Citation data:

Proceedings of the 8th International Conference on Cyber-Physical Systems - ICCPS '17, Page: 51-60

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Citations 1
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Liang He, Eugene Kim, Kang G. Shin, Guozhu Meng, Tian He
Association for Computing Machinery (ACM)
Computer Science
conference paper description
Insufficient support of electric current sensing on commodity mobile devices leads to inaccurate estimation of their Battery's state-of-health (SoH), which, in turn, shuts them off unexpectedly and accelerates their Battery fading. In this paper, we design V-BASH, a new Battery SoH estimation method based only on their voltages and is compatible to commodity mobile devices. V-BASH is inspired by the physical phenomenon that the relaxing Battery voltages correlate to Battery SoH. Moreover, it is enabled on mobile devices with a common usage pattern of most users frequently taking a long time to charge their devices. The design of V-BASH is guided by 2; 781 empirically collected relaxing voltage traces with 19 mobile device batteries. We evaluate V-BASH using both laboratory experiments and field tests on mobile devices, showing a <6% error in SoH estimation.

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