2017/09/25 by Stefano Nuzzo, Michael Galea, Chris Gerada +1 · 68 citations
Engineering · Materials Science · #Electric Motor Design and Analysis #Magnetic Properties and Applications #Magnetic Bearings and Levitation Dynamics #Commutation #Voltage drop #Control theory (sociology) #Generator (circuit theory) #Rotor (electric) #Engineering #Voltage #Finite element method #Excitation #Electric generator #Rectifier (neural networks) #Diode #Synchronous motor #Electronic engineering #Computer science #Power (physics) #Control engineering #Electrical engineering #Physics
paper · open access · doi:10.1109/tie.2017.2756592
published in IEEE Transactions on Industrial Electronics 65(4), 2996-3007 (Institute of Electrical and Electronics Engineers)
openalex publication_date 2017/09/25 · openalex created_date 2017/10/06 · openalex updated_date 2026/08/08
The traditional generating set is usually comprised of a classical, wound-field, salient-pole, or cylindrical rotor synchronous generator, excited by a separate smaller machine, via a rotating, uncontrolled diode rectifier. The effects of the commutation processes of the diode bridge are often overlooked and neglected. However, due to the uncontrolled nature of this process, the rectified voltage available at the main generator's rotor terminals can be significantly lower than the expected value. This is especially true for low-to-medium power rated systems. In this paper, a detailed investigation of these aspects is done and an accurate voltage drop prediction model is then proposed. The model is validated with finite-element analysis and with experimental results for a particular low-medium rated generating system in the 400 kVA power range. The validated tool is then integrated into an innovative design tool, which first performs an analytical presizing procedure and then utilizes a genetic algorithm approach to identify an optimal excitation system design, aimed at minimizing the voltage drop ensuing from the diode commutations, with minimum impact on the overall efficiency.