Particle Swarm Optimization-Based Sensorless Active Power Decoupling for Active-Front-End Impedance-Source Inverters

The low-frequency harmonics (LFH) problem has been inherent to single-phase Active-Front-End Impedance-Source Inverters (AFE-ISI). The power density and reliability of such inverters have been poor, as large electrolytic capacitors and bulky inductors become obligatory in the active-front-end network (AFEN). In literature, alternatives are researched in the form of Active Power Decoupling Networks (APDNs), in which Boost-type APDN (BAPDN) has attracted a lot of attention for its simple operation and circuitry. The BAPDN consists of two switches, one storage capacitor to store the LFH energy and one transfer inductor for energy transfer from the AFEN capacitor to the storage capacitor. Generally, the implementation of the control loops of BAPDN requires two sensors: one current and one voltage sensor. The current sensor is utilized for the measurement of the LFH current passing through the transfer inductor so that it can be compared with a reference LFH current. The voltage sensor is essential for the measurement of the voltage across the storage capacitor so that the over-voltage protection loop can be constructed. In this paper, a sensorless mechanism is applied to BAPDN, where both sensors can be removed. For the parameter selection of the sensorless controller, the Particle Swarm Optimization (PSO) algorithm is utilized. Finally, with the help of a BAPDN-integrated AFE-ISI hardware prototype, the proposed mechanism is validated with experimental results.