The objective of the proposed research is to develop methods for the multi-objective design, optimization, and condition monitoring of electric machines, so as to generate the optimal designs and improve machine robustness for electric propulsion. In particular, the selected high-performance electric machines are the switched reluctance machine (SRM) with a simple and robust structure, and the interior permanent magnet (IPM) machine with a high torque density and efficiency. For SRMs, an active current profiling technique integrated multi-objective analytical design and optimization is proposed to generate the optimal design in terms of multiple performance indices, which is proven to be accurate and time-saving, especially for a large search space with multiple prime design variables. The proposed scheme offers machine designers accurate, handy and convenient initial designs, which can be further verified or fine-tuned if necessary. The optimization process is further developed with advanced machine learning algorithms to accelerate the search process and facilitate the final decision-making process with the self-organizing map and t-SNE algorithm. To monitor the demagnetization property of the closed-loop direct torque controlled (DTC) IPMSM, two nonintrusive high-frequency signal injection schemes are proposed for PM temperature estimation via analyzing the PM electrical high-frequency resistance, which is a byproduct of the eddy current loss induced by the applied high-frequency magnetic field. The developed methods bring practical ways to excite a proper amount of high-frequency current into the stator winding, which leads to a simple, accurate, and nonintrusive permanent magnet thermal monitoring scheme for DTC-controlled IPM machines. The demagnetization properties of the IPM machine under the most commonly observed stator inter-turn short circuit fault is also systematically investigated via simulations and experiments, thereby offering machine designers handy information in evaluating the demagnetization fault-tolerant capability of various IPM machine design candidates.
【 预 览 】
附件列表
Files
Size
Format
View
Multi-objective design, optimization, and condition monitoring of high-performance electric machines for electric propulsion