Online Battery Impedance Identification Based on Small AC Signal Injection of Inverter
Battery impedance online identification is a nondestructive measurement technique for battery condition estimation and health diagnosis. However, conventional methods are costly, time-consuming, and can only be performed on offline small cells. Spurred by this, we concentrate on the development of a transparent and novel measurement method that, for the first time, uses a controllable sine-sweep perturbation generated by an existing battery-connected inverter. In this article, through inverter control, a small ac excitation signal with controllable amplitude and target frequency can be transferred to the battery due to power flow. This method eliminates the need to disconnect the battery from the operating system or add an additional excitation circuit, which provides a low-cost, high-availability, and real-time means for online battery impedance identification. Once it is developed as an embedded function in a widely used battery-inverter system and performed online during operation continuously or periodically, it could provide a monitoring system for the whole pack as well as a single cell. Simulations and experiments prove its effectiveness. The online electrochemical impedance spectrum (EIS) tests, conducted on a 24-Ah battery module test bench, were completed within 300 s for a frequency range from 0.1 Hz to 10 kHz and within 50 s for a frequency range from 1 Hz to 1 kHz, respectively, much faster than an electrochemical workstation. The accuracy and dynamic performance of the proposed method are validated by contrasting online EIS results with offline results with cell voltage being 3.4 V, 3.5 V, 3.6 V. Moreover, a series of dynamic impedance spectra across varying discharge rates and state of charge highlights its promising potential for battery state estimation.
Authors
- Ding Luo (ORCID: https://orcid.org/0000-0001-9070-2417)
- Min Zhou (ORCID: https://orcid.org/0000-0001-5758-6477)
- Hongyan Qu
- Wei Sun (ORCID: https://orcid.org/0000-0002-2279-6500)
- Dong Jiang
- Xuan Zhao (ORCID: https://orcid.org/0000-0002-8190-7792)
Institutions
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Power Electronics
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1109/tpel.2024.3463795
- Citations
- 7
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 1.42