MA – Model predictive control of a boost converter for power factor correction

This master thesis aims to explore „Model Predictive Control“ (MPC) of a boost converter for „Power Factor Correction“ (PFC) and to benchmark its performance against traditional PI controllers, as these have limitations such as failing to provide optimal control for handling dynamic loads or high power demands. So to investigate whether an advanced control technique such as MPC can provide improvements against those limitations and can serve as a benchmark for optimal control or not.

The initial part consist of a literature review on control methods for PFC boost converter and discussing their pros and cons and then developing a code for a mathematical model of a PFC boost converter and a PI control loop of it and tune in the parameters. The feasibility of implementing MPC for PFC in hardware and resources should be assessed. Taking existing simulation programs for MPC of a buck converter as a reference, MPC must be implemented in MATLAB/Simulink for the PFC boost converter and validate using simulations. Evaluation and comparison has to be made for control performance between PI controller and MPC controller under operating conditions focusing on harmonics distortions and response time.

This work aims to present a comprehensive evaluation of MPC as a control strategy for PFC boost converters. The results will contribute to the scientific understanding of advanced control strategies in power electronics and provide practical insights into their feasibility and benefits.

Bearbeiter: Priyansh Harshadbhai Khakhria

Betreuer: Zhi Li (Infineon Technologies AG (IFX))

Verantwortlicher: Prof. Dr.-Ing. Martin März