Modeling Dual Active Bridge Converters in DC Distribution Systems
Abstract
Modeling improvements are proposed for systems containing dual active bridge (DAB) converters. First, a systematic approach to constructing models of multi-converter systems is described. The method generates continuous-time large-signal average models that are suitable for system-level analysis and efficient time-domain simulation. Although the base DAB models are derived using generalized average modeling (GAM), the system-level construction does not require the specification of a base period. Secondly, a method of reconstructing currents in the high-frequency DAB transformer is proposed. This method significantly improves accuracy in modeling transformer current, which is a critical weakness of DAB models derived using GAM. Furthermore, the method is applied offline as needed, so it does not affect the computational complexity of time-domain simulation. Both the system-level model construction procedure and harmonic reconstruction method are validated in switching simulations and hardware experiments.
Recommended Citation
J. A. Mueller and J. W. Kimball, "Modeling Dual Active Bridge Converters in DC Distribution Systems," IEEE Transactions on Power Electronics, vol. 34, no. 6, pp. 5867 - 5879, Institute of Electrical and Electronics Engineers (IEEE), Jun 2019.
The definitive version is available at https://doi.org/10.1109/TPEL.2018.2867434
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Analytical Models; Average Modeling; Computational Modeling; Dual Active Bridge Converter; Generalized Average Model; Harmonic Analysis; Mathematical Model; Numerical Models; Phase Shift Modulation; Switches; Time-Domain Analysis
International Standard Serial Number (ISSN)
0885-8993; 1941-0107
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jun 2019