Artificial-Intelligence-Based Triple Phase Shift Modulation for Dual Active Bridge Converter With Minimized Current Stress

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