Modeling and design of linear induction motors using a reluctance network method

The methods of modeling and designing of Linear Induction Motors (LIM) are considered as the most important element of competition among manufacturers of this category of motors. Although, the majority of manufacturers employ finite element-based methods to achieve more accurate design. However, these methods still suffer from a longer computation time. Moreover, the Finite Element Method (FEM) require very significant and expensive computing equipment. Researchers have been created a number of analysis techniques to solve this conundrum and expedite computation, but the accuracy of the findings is still below acceptable bounds. In this work, we propose the modeling and design of the LIM using the Reluctance Network Method (RNM) in order to reduce the calculation time and improve the accuracy of the results. sing the COMSOL Multiphysics software, a comparative analysis with the FEM is introduced in order to verify the outcomes of the previous one. Compared to finite elements, the results enabled a computation time reduction of 27 hours. The proposed RNM-based methodology demonstrates the potential to enhance the speed and accuracy of LIM modeling and design, which could provide a competitive advantage for manufacturers in the industry. The enhanced analysis provides a more comprehensive interpretation of the results, highlighting both the technical achievements and practical implications of using RNM for LIM modeling. The key takeaway is that while RNM shows slightly lower accuracy compared to FEM (87% vs 88%), it offers a significant advantage in computation time (77% reduction) while maintaining acceptable accuracy for practical applications.