Monitoring the aging battery cells is important to maintain battery performance. Capacity is a key indicator of battery aging diagnosis, but capacity can be estimated differently depending on the C-rate. Battery impedance monitoring using electrochemical impedance spectroscopy (EIS) is also recognized as a battery diagnostic method. However, EIS is inefficient when diagnosing a large number of individual battery cells due to complex computation and measurement time. In this article, a harmonic analysis method for monitoring aging battery is proposed. The proposed diagnostic technique applies the designed 1-kHz sinusoidal signal, comprising a sinusoidal current component and a direct current component, to the battery. Harmonics are generated when signals passing through nonlinear systems are distorted. A battery is an asymmetric nonlinear system with different bidirectionality. Comparing the simulation and experimental results, we confirmed that the harmonic signatures are the indicators that distinguish between a normal and an aging battery. Moreover, the proposed in situ technique can be applied during charge/discharge cycles, even in the case of an apparent reduction of even harmonics.
|Journal||IEEE Transactions on Instrumentation and Measurement|
|Publication status||Published - 2021|
Bibliographical noteFunding Information:
Manuscript received November 15, 2020; accepted November 22, 2020. Date of publication December 7, 2020; date of current version December 30, 2020. This work was supported in part by the framework of the international cooperation program managed by the National Research Foundation of Korea (NRF) under Grant 2017K1A4A3013579 and in part by the NRF Grant funded by the Ministry of Science, ICT and Future Planning under Grant NRF-2020R1A2B5B03001692. The Associate Editor coordinating the review process was Dr. Hongrui Wang. (Corresponding author: Yong-June Shin.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea (e-mail: firstname.lastname@example.org). Digital Object Identifier 10.1109/TIM.2020.3043097
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All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering