Online Monitoring of Lithium-Ion Battery Impedance Using DC-DC Converter Self-Excited Switching Oscillations
Online impedance monitoring is an important technique for acquiring the condition information of a Lithium-ion (Li-ion) battery (e.g., state of charge and internal temperature) for safe, reliable, and efficient operation. The existing ac excitation/response method ( Z ( jω ) = V ( jω )/ I ( jω )) ma...
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Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 2024-08, Vol.71 (8), p.1-12 |
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Sprache: | eng |
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Zusammenfassung: | Online impedance monitoring is an important technique for acquiring the condition information of a Lithium-ion (Li-ion) battery (e.g., state of charge and internal temperature) for safe, reliable, and efficient operation. The existing ac excitation/response method ( Z ( jω ) = V ( jω )/ I ( jω )) may interact with the system's normal operation leading to an interrupted measurement and degraded accuracy. To address these challenges, this article proposes an online continuous battery impedance monitoring method by using the high-frequency (HF) electromagnetic oscillations excited by the dc-dc converter's pulse width modulation (PWM) switching in a battery system. First, the principle of the switching oscillation method is analyzed, including the HF equivalent circuit and the analytical expression of the battery switching oscillation current. Then, a battery impedance online monitoring scheme is proposed, where the switching oscillation current is captured by a specially designed noncontact HF oscillation sensor, and the oscillation features including frequency and damping ratio are extracted by the half-power bandwidth algorithm to estimate the battery's equivalent resistance and reactance. Finally, experimental work was carried out on a 24 V/ 6.6 Ah 18 650 Li-ion battery module test system, and the results demonstrate excellent performance, including continuous real-time monitoring, high accuracy, and good robustness to converter dynamic operation. |
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ISSN: | 0278-0046 1557-9948 |
DOI: | 10.1109/TIE.2023.3317850 |