Optimal analysis for segmented flux switching machine in more electric engine - Tan, Yun Ann (2019)
Ever since the industry started to focus a lot in the energy conservation, as well as the energy efficiency, the more electric engine (MEE) is being suggested as the promising alternative to the conventional combustion engine. One of the examples of MEE is the flux switching machine. It has advantages such as high output power density, great robustness and reliability, which are suitable for various industrial applications. Thus, the objective of this final year project is to perform a multi-objective and multidomain parametric optimisation analysis on the segmented rotor flux switching machine, by using the analytical methods. This final year project adopted a different approach in analysing the segmented rotor flux switching machine, which saves up the time on building the simulation model for further analysis. A set of multi-variable equations were studied for their correlations with the machine’s performances, in terms of both electromagnetic and thermal. The variables are mostly the geometry parameters of the machine, which include the number of stator teeth and the rotor segments, length of air-gap, radius of both the stator and rotor, etc. The machine’s performance was evaluated based on its output power density, back EMF, electromagnetic torque, cogging torque, losses and the overall heat transfer coefficient of the machine. Lastly, a multi-objective genetic algorithm optimisation model was developed and used in MATLAB to determine the optimum design for the machine.