Optimal Modulation Methodology for Efficient Operation of Single-Stage Indirect Matrix Converter
Single-stage indirect matrix converter (SSIMC) is extensively studied for AC-DC applications due to the several benefits the topology offers. Single-stage operation, elimination of intermediate energy storage, bi-directional power flow capability, and high-power density enable SSIMC in DC fast charger applications. Existing SSIMC modulation methods utilize optimization-based approaches for modulating the primary-side matrix converter and the secondary-side full-bridge converter. These methods primarily focus on achieving a unity power factor and enabling vehicle-to-grid (V2G) operation. However, the interdependency between the primary and secondary side modulations for a wide-range SSIMC operation has not yet been studied. Hence, this paper presents a detailed analysis of the primary and secondary side modulations and, based on the results, proposes an optimal modulation methodology for the efficient operation of SSIMC. The combination of primary and secondary modulations introduces additional system variables, secondary phase shift (SPS), and secondary duty cycle (SDC). To ensure efficient SSIMC operation, the selection of optimal SPS and SDC is crucial and presents a significant challenge. The proposed methodology addresses this challenge with a simple phase-shift control algorithm that determines the optimal SPS and SDC values for a wide-range SSIMC operation. The simulation results validate the proposed methodology, demonstrating a 20%-40% reduction in RMS current in the transformer and a 1.2%-1.5% improvement in efficiency across the operational range of the SSIMC.
Authors
- Woongkul Lee (ORCID: https://orcid.org/0000-0002-2282-6837)
- Avinash Dornala
Institutions
- Purdue University West Lafayette (US)
Publication Details
- Published
- 2025-06-18
- DOI
- https://doi.org/10.1109/itec63604.2025.11098047
- Citations
- 1
- Primary Topic
- Multilevel Inverters and Converters
- Type
- article
- Field-Weighted Citation Impact
- 0.73