The dual active bridge (DAB) converter has been popular in many applications for its outstanding power density and bidirectional power transfer capacity. Up to now, triple phase shift (TPS) can be considered as one of the most advanced modulation techniques for DAB converter. It can widen zero voltage switching range and improve power efficiency significantly. Currently, current stress of the DAB converter has been an important performance indicator when TPS modulation is applied for smaller size and higher efficiency. However, to minimize the current stress when the DAB converter is under TPS modulation, two difficulties exist in analysis process and realization process, respectively. Firstly, three degrees of modulation variables in TPS modulation bring challenges to the analysis of current stress in different operating modes. This analysis and deduction process leads to heavy computational burden and also suffers from low accuracy. Secondly, to realize TPS modulation, if a lookup table is adopted after the optimization of modulation variables, modulation performance will be unsatisfactory because of the discrete nature of lookup table. Therefore, an AI-based TPS modulation (AI-TPSM) strategy is proposed in this paper. Neural network (NN) and fuzzy inference system (FIS) are utilized to deal with the two difficulties mentioned above. With the proposed AI-TPSM, the optimization of TPS modulation for minimized current stress will enjoy high degree of automation which can relieve engineers' working burden and improve accuracy. In the end of this paper, the effectiveness of the proposed AI-TPSM has been experimentally verified with a 1 kW prototype.

翻译：双有源桥（DAB）变换器因其卓越的功率密度和双向功率传输能力，在许多应用中备受青睐。目前，三重移相（TPS）可被视为DAB变换器最先进的调制技术之一，它能拓宽零电压开关范围并显著提高功率效率。当前，当采用TPS调制以实现更小尺寸和更高效率时，DAB变换器的电流应力已成为一项重要的性能指标。然而，为了在DAB变换器采用TPS调制时最小化电流应力，分析过程和实现过程中分别存在两个难点。首先，TPS调制中三个调制变量的自由度给不同工作模式下的电流应力分析带来了挑战，这一分析与推导过程导致计算负担沉重，且精度较低。其次，为实现TPS调制，若在调制变量优化后采用查找表，由于查找表的离散特性，调制性能将不尽人意。因此，本文提出一种基于人工智能的TPS调制（AI-TPSM）策略。神经网络（NN）和模糊推理系统（FIS）被用于应对上述两个难点。采用所提出的AI-TPSM后，为最小化电流应力而进行的TPS调制优化将享有高度自动化，这能减轻工程师的工作负担并提高精度。本文最后，通过一个1千瓦的样机实验验证了所提出的AI-TPSM的有效性。