Smart Neural Network Steers Dual-Input Converter for Electric Vehicles
A 500 W laboratory prototype of a dual-input converter with a modified deep neural network controller achieved a peak efficiency ...
A 500 W laboratory prototype of a dual-input converter with a modified deep neural network controller achieved a peak efficiency ...
A new three-port DC–DC converter design uses an improved Gray Langurs Optimizer to cut a measured weighted RMS-current metric by ...
A Fuzzy Logic controller strategy was successfully applied to a single-input dual-output DC–DC converter, demonstrating superior settling times and voltage ...
George Mason University professor V. Rao Mulpuri has received $80,000 from the Naval Research Laboratory to investigate fundamental defects in ...
Researchers have demonstrated a single-carrier hybrid switching strategy that cuts common-mode voltage in three-level T-type inverters by about 22 percent ...
A constraint-driven multi-objective optimization framework produced a nanocrystalline high-frequency transformer whose design was verified by finite-element analysis and a 150 ...
A 200 W laboratory prototype of a single-switch quadratic DC–DC converter produced a 400 V output from a 25 V ...
A new control framework for solar-integrated EV charging stations combines fuzzy logic, Kalman filtering, and predictive control to achieve high ...
A detailed loss evaluation study reveals that practical implementation factors can increase power electronics losses by up to 21 percent, ...
A new study combines fuzzy logic power allocation with adaptive droop control to stabilize solar-hydrogen DC microgrids, cutting voltage violations ...
© 2026 Scienmag - Science Magazine
© 2026 Scienmag - Science Magazine