Automatic Triple Phase Shift Modulation for DAB Converter with Minimized Power Loss

Fanfan Lin, Xin Zhang, Xinze Li, Changjiang Sun, Wenjian Cai, Zhe Zhang

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Currently, triple phase shift (TPS) modulation has attracted more and more attention of researchers as an advanced modulation strategy for dual active bridge converter (DAB). Since it has three degrees of freedom, it can realize better performance both in soft switching ranges and power efficiency. However, how to choose these three degrees of freedom to realize optimal power efficiency of DAB converter becomes a concern for researchers. Generally, there exist two difficulties to apply efficiency-oriented TPS modulation. The first difficulty lies in the analysis process in which the main task is to figure out the relationships between modulation parameters and power loss. The three modulation parameters in TPS bring difficulties in analysis and deduction process, which suffers from high computational burden and low accuracy. Additionally, the second difficulty lies in the real-time realization of TPS modulation. If a look-up table is applied to store the optimized modulation parameters, it is highly likely that its discrete nature will result in unsatisfactory modulation performance. Therefore, this paper proposes an efficiency-oriented automatic TPS (ATPS) modulation approach which utilizes neural network, particle swarm optimization and fuzzy inference system respectively in its three stages. The proposed ATPS is able to mitigate labor in computational burden with a highly automatic fashion. Finally, this proposed ATPS has been validated with 1kW hardware experiments
Original languageEnglish
JournalIEEE Transactions on Industry Applications
Number of pages11
ISSN0093-9994
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Dual active bridge
  • Triple Phase Shift
  • Power loss
  • Neural network
  • Particle swarm optimization
  • Fuzzy inference system

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