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Fast Detection Method of Electrochemical Impedance Spectroscopy for Energy Storage Battery Based on Current Excitation |
Wu Jianxin, Yang Lijun, Xiao Yanlin, Xia Yuan |
State Key Laboratory of Power Transmission Equipment Technology Chongqing University Chongqing 400044 China |
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Abstract In recent years, energy storage batteries have become the key equipment of large-scale energy storage systems, and electrochemical impedance spectroscopy (EIS) is widely used in the detection and health status assessment of energy storage battery performance parameters. At present, EIS mainly relies on electrochemical workstations, based on voltage excitation, in the frequency range of 0.01 Hz~1 kHz using frequency-by-frequency scanning detection. The detection time cost is high, which cannot obtain the impedance characteristics of energy storage batteries in time. The input impedance of the detection loop is small, which cannot be in-situ detection of energy storage batteries to achieve thermal runaway warning. Some studies have used single-frequency or several-frequency impedance information to achieve online detection and evaluation of energy storage batteries, but it is still limited to frequencies above 1 Hz. In this paper, a fast detection method is proposed to reconstruct the EIS by measuring the battery response voltage signal with the multi-frequency superimposed current signal as the excitation. A fast EIS detection system is designed for energy storage batteries, which can quickly and accurately obtain the broadband EIS curve of energy storage batteries. Firstly, based on the Discrete Fourier Transform, the excitation signal is changed from a sinusoidal signal with fixed frequency to a time-domain signal with multi-frequency components to accelerate the detection. The influence of the amplitude and phase of each frequency component is analyzed and the modulation method is discussed. Then, the hardware circuit of the detection system is designed and built. The OPA549 is used to convert the voltage signal into current signal as the detection system excitation input to the energy storage battery. The loop current and the voltage response signal of the energy storage battery are detected, and the signal amplitude and phase frequency characteristics are analyzed and the Nyquist diagram is drawn to obtain the EIS curve. Finally, the detection system is used for continuous and repetitive testing of the energy storage battery, and the EIS is also detected for different open-circuit voltage states to verify the repeatability and sensitivity of the detection system. Since the system uses current as excitation, compared with voltage excitation, the test loop has the characteristics of large input impedance, controllable loop current and simple and reliable topology. The test results on actual energy storage batteries show that the detection time to obtain the battery EIS in the frequency of 0.02 Hz~1 kHz is only 120 s, which is 90% shorter compared to the measurement time of electrochemical workstation. The test results are highly repeatable, with a maximum error of only 0.031 67 mΩ, and the detection system can effectively detect the EIS curves of energy storage batteries under different voltage states. The test results show that the pure ohmic resistance Rs of Li-ion battery has a small correlation with the SOC state, and the correlation between Rct and SOC is larger, which is consistent with the results in other related literature, and the low frequency band slope also has a large correlation with SOC. The following conclusions can be drawn from the experimental results: (1) Compared with voltage excitation, the system has the characteristics of large input impedance, controllable loop current, simple and reliable topology, and is suitable for in-situ detection of energy storage batteries. (2) The designed excitation waveform significantly improves the testing efficiency and overcomes the contradiction between rich information in the low frequency band and low detection efficiency. (3) The actual test results show that the system has good repeatability and sensitivity, which can quickly obtain the EIS curve of wide frequency band and greatly improve the detection efficiency.
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Received: 23 July 2022
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