Advanced control optimization for bidirectional DC-DC converters in electric vehicles using Harris Hawk optimization

In electric vehicle (EV) systems, the bidirectional DC-DC converter has become essential for its ability to support grid interactions and various other applications. Among these, the isolated dual active bridge (DAB) converter stands out due to its isolated operation, high efficiency, and soft-switching capabilities. Optimizing the control of phase shift modulation is critical for achieving both high performance and system stability, especially under transient conditions. This paper presents an advanced proportional-integral (PI) controller, optimized using the harris hawk optimization (HHO) algorithm. Comparative analysis with controllers optimized using Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms shows that the HHO-based approach delivers superior performance, with a lower overshoot of 0.6125% and higher efficiency of 98.27%. Additionally, key performance metrics such as Integral of Time Absolute Error (ITAE), Integral Absolute Error (IAE), and Integral Squared Error (ISE) are significantly reduced, with the ITAE index decreasing to 5.086 compared to the conventional PI controller. The reduction of these indices is critical for achieving faster, more precise, and stable control, particularly in high-performance applications like automotive systems and power electronics.