Modelling, Simulation and Control of Hybrid Excited Synchronous Machines

In the field of electric machines, the development of increasingly efficient and flexible solutions is essential to meet the demands of modern systems. Among the different types of electric motors, wounded rotor (EESM) and hybrid excited motors (HESM) represent two particularly interesting configurations, allowing modulation of the rotor flux employing an external DC current. HESM machines provides also a permanent magnet flux contribution, with the aim of increasing the efficiency, the power density and reducing the DC supply ratings. Being the Hybrid technology a relatively recent one, different configurations can be obtained and investigated, as will be presented. The proposed work can be articulated in three main parts: The first part will be focused on the linearized analytical model extraction, extended to all the saliency scenarios. Then, based on a recent analytical EESM linearized control study, the possible operating regions will be investigated, generalizing for each one the static control trajectories aimed to optimize the Joule losses, taking into account permanent magnets. A Matlab script will be also developed to extract the transitions between the different regions The second part is focused on the creation of custom Matlab scripts, providing the interaction with FEMM simulators to build, simulate and extract the machine parameters through finite element simulations. This suite will be employed to investigate also some recent machine topology. The deviation with respect to the linearized model will also be discussed depending on the machine parameters. At last, in the third part, the developed theory will be translated into PLECS simulator, creating custom linear and nonlinear Voltage Behind Reactance models. Then a control strategy will be implemented for the linearized scenario and simulations will be carried out in order also to validate the FEMM parameter extraction and the theory. Some consideration will also be given to the nonlinear model control.