Machine Learning Aided Optimized Modulation in Triple Active Bridge Converter
Author:
Affiliation:
1. Kyoto Institute of Technology,Graduate School of Science and Technology,Kyoto,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9968313/9968303/09968640.pdf?arnumber=9968640
Reference17 articles.
1. Extending the ZVS Operating Range of Dual Active Bridge High-Power DC-DC Converters
2. Extended-Phase-Shift Control of Isolated Bidirectional DC–DC Converter for Power Distribution in Microgrid
3. Minimum-Current-Stress Scheme of Dual Active Bridge DC-DC Converter With Unified-phase-shift Control
4. Cooperative Triple-Phase-Shift Control for Isolated DAB DC–DC Converter to Improve Current Characteristics
5. Overview and Comparison of Modulation and Control Strategies for a Nonresonant Single-Phase Dual-Active-Bridge DC–DC Converter
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1. An Online-Optimized ZVS-Current Tracked Soft-Switching Modulation for Triple Active Bridge Converter;IEEE Transactions on Power Electronics;2024-11
2. Deep Reinforcement Learning-based Power Flow Control for Triple Active Bridge Converter;2024 IEEE 10th International Power Electronics and Motion Control Conference (IPEMC2024-ECCE Asia);2024-05-17
3. Triple active bridge converter in nanogrid applications: A direct interface for photovoltaic modules and storage;IET Power Electronics;2024-04-17
4. A Survey on Multi-Active Bridge DC-DC Converters: Power Flow Decoupling Techniques, Applications, and Challenges;Energies;2023-08-10
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