Voltage Sensorless Control of Reduced-Order Elementary Super-Lift Luo Converter using Extended Kalman Filter

Sensorless control approaches can enhance system reliability while reducing sensor cost in dc/dc converters. In this paper, an extended Kalman filter based voltage sensorless control system is proposed to estimate both the input and output voltages of an elementary super-lift Luo converter using a reduced-order model, thereby decreasing the number of sensors. To regulate the output voltage of the elementary super-lift Luo converter, a proportional-integral controller with a reduced number of tuning parameters is designed to minimize steady-state error. The proposed method is evaluated in the MATLAB/Simulink environment under stepwise input/output voltage variations and ramp input voltage variation. The voltage sensorless control system achieves high estimation accuracy with mean absolute error values of 0.2082 V (stepwise input voltage variation), 0.2272 V (stepwise output voltage variation), and 0.1620 V (ramp and stepwise input voltage variation) for the three test scenarios, respectively. In addition, the proportional-integral controller provides a settling time of approximately 55 ms while maintaining negligible steady-state error for all scenarios. The obtained results demonstrate that the proposed voltage sensorless control system provides accurate voltage estimation, robust dynamic performance, and reduced sensor dependency, making it a promising solution for high-performance and cost-effective dc/dc converter applications.