Advanced Control of a Non Inverting Buck Boost Converter

Nowadays, exploitation of renewable energy and wasted energy is a challenging problem for many engineering fields. This study is linked to thermoelectric generators (TEG) in automotive application; a TEG can be used for recovering waste heat of the exhaust system, but it needs a converter to track the maximum power point of operation. In order to drive the thermoelectric generator, a non-inverting buck-boost (NIBB) converter is used: this topology allows to transfer energy with high efficiency, providing an output voltage higher or lower than the input voltage supplied. The thesis objective is to find an optimal algorithm for the control of the converter. Different control algorithms have been developed and compared: PID, H-infinity, LQR, Sliding Mode and Fuzzy Logic Control. Also, an extended Kalman filter (EKF) is developed to improve available measures and to estimate the states of the system. The control algorithms and the EKF are designed through the model-based approach in Simulink environment, using a model of the converter that works with a switching frequency of 150 kHz and that is connected to two Thevenin equivalents of the input generator and of the output battery. Simulated algorithms are implemented into a TMS320F28379D dual-core microcontroller, and an accurate and intensive campaign of tests were carried out on a real prototype for validation purpose