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Triple phase shift (TPS) is commonly utilized to enhance the efficiency of dual active bridge (DAB) DC/DC converters; however, the formulation of optimal phase-shift ratios poses a significant challenge given the versatility of the DAB converter in four distinct operational scenarios, each comprising five specific cases. Prior research has often sought the most effective local operation phase ratio set by analyzing parameters in every case, neglecting the importance of locating the global solution. Additionally, the expressions for circuit states such as peak or root-mean-square current value, and transmitted power in DAB fluctuate across different cases, further complicating the pursuit of global optimization. Consequently, it is crucial to examine the location of the optimal solution set when analyzing the optimal solution for a multi-case scenario. That is the pivotal task in this paper. A simulation is conducted to validate the case simplification analysis. The discussion space for general optimization is focused on cases 3 and 4, streamlining the analytical process and reducing the time required for comprehensive optimization.

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Mapping Optimal Space Simplification Analysis in Triple Phase Shift Control of Dual Active Bridge Converters

  • 会议论文

  • 发表日期：

    2026年

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  • Wenjie Xu,
  • Junwei Liu,
  • Wenzheng Xu,
  • Yixin Wang,
  • Taiming Chen

摘要

Triple phase shift (TPS) is commonly utilized to enhance the efficiency of dual active bridge (DAB) DC/DC converters; however, the formulation of optimal phase-shift ratios poses a significant challenge given the versatility of the DAB converter in four distinct operational scenarios, each comprising five specific cases. Prior research has often sought the most effective local operation phase ratio set by analyzing parameters in every case, neglecting the importance of locating the global solution. Additionally, the expressions for circuit states such as peak or root-mean-square current value, and transmitted power in DAB fluctuate across different cases, further complicating the pursuit of global optimization. Consequently, it is crucial to examine the location of the optimal solution set when analyzing the optimal solution for a multi-case scenario. That is the pivotal task in this paper. A simulation is conducted to validate the case simplification analysis. The discussion space for general optimization is focused on cases 3 and 4, streamlining the analytical process and reducing the time required for comprehensive optimization.