Abstract
Identifying dynamic parameters in lithium-ion batteries is of paramount importance for estimating state-of-charge and state-of-health. An enhanced-STATCOM (E-STATCOM), that is a STATCOM that integrates energy storage, can incorporate battery-parameter identification algorithms without compromising its normal operation. The paper presents a design of an E-STATCOM that ensures that the current harmonics injected into the battery for parameter identification do not alter the grid current. Using the injected current values and the corresponding battery voltage values, a Recursive Least Squares algorithm provides the battery parameters. Thus, the paper describes the E-STATCOM architecture and the proposed control that seamlessly integrates online battery-parameter identification, as well as the validation of the proposed approach.
Original language | English |
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Title of host publication | 2024 IEEE 10th International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1524-1527 |
Number of pages | 4 |
ISBN (Electronic) | 9798350351330 |
DOIs | |
Publication status | Published - 2024 |
Event | 10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia - Chengdu, China Duration: May 17 2024 → May 20 2024 |
Publication series
Name | 2024 IEEE 10th International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia |
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Conference
Conference | 10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia |
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Country/Territory | China |
City | Chengdu |
Period | 5/17/24 → 5/20/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
ASJC Scopus Subject Areas
- Energy Engineering and Power Technology
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Safety, Risk, Reliability and Quality
- Control and Optimization
- Instrumentation
Keywords
- Battery module
- current harmonics
- enhanced static compensator (E-STATCOM)
- parameter identification
- recursive least squares