介电谱
电池组
电池(电)
电阻抗
荷电状态
电气工程
电子工程
噪音(视频)
等效电路
工程类
电压
分析化学(期刊)
功率(物理)
计算机科学
物理
化学
电极
电化学
人工智能
图像(数学)
量子力学
色谱法
作者
Zhe Gong,Avram Kachura,Seyed Amir Assadi,Nicholas Cusimano,Joshua Piruzza,James Y. Xu,Olivier Trescases
标识
DOI:10.1109/tie.2022.3215833
摘要
State-of-power (SOP) and state-of-charge (SOC) estimation inaccuracy manifests throughout the electric vehicle (EV) battery lifetime due to the nonlinear degradation trajectory that is unique to each use-case. The inaccuracy leads to premature termination of charge and discharge operations, which results in the virtual loss of battery performance. In-situ electrochemical impedance spectroscopy (EIS) has been proposed to provide real-time battery impedance measurements, which can theoretically improve the SOP/SOC estimation accuracy. In this work, an EV-scale in-situ EIS system is demonstrated experimentally, from impedance measurement to equivalent circuit model (ECM) extraction. The pack-level discharge energy versus SOP/SOC estimation errors is also simulated, which quantifies the virtual loss of battery performance. The measured-impedance error tolerance of three common ECM extraction techniques is then examined through a randomized set of simulated EIS tests with injected measurement noise. Finally, in-situ impedance measurement is performed on 20 battery submodules using an electric pickup truck EIS system. The ECM-predicted voltage output is compared against measured driving data. Experimental results indicate approximately 8%–9% improvement in SOP estimation accuracy at 3$^{\circ }$C and 10$^{\circ }$C between the in-situ extracted models and a representative baseline.
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