Abstract
Background: Because the permanent magnet servo motor (PMSM) has the advantages of high efficiency, big torque, energy saving and environment protection, more and more researchers pay attention to it in recent years. This paper did research on the application of the equivalent thermal network method in the motor temperature field calculation.
Methods: The basic theory and the calculation of traditional thermal network method were analyzed. Considering the relatively high deviation of traditional thermal network method, the paper proposed a new method of decreasing the deviation. Taking a 10kW PMSM as an example, the theories of energy conservation and heat conservation are considered, and a new thermal network node model was built. In this model, the key node division was optimized in the position where the heat transfer difference is great. The difference of heat transfer capacity at the edge of the thermally conductive materials and the influence of external heat flow on the calculation of equivalent thermal resistance had been considered properly. Results: The temperature field of the motor was calculated by traditional and optimized thermal network methods respectively. In order to verify the optimized method could improve the accuracy of the traditional method, the temperature field of the motor was also calculated by the finite element method. Comparing the results of traditional and optimized methods with the finite element method, it proved that the optimized method could decrease the difference between the results of equivalent thermal network method and finite element method, and the practicability of the optimized method is also proven. Conclusion: The optimized method provides a new method to increase the accuracy of equivalent thermal network method.Keywords: Permanent magnet servo motor, temperature field, equivalent thermal network method, finite element method, Winding connection mode, magtrol dynamometer machine.
Call for Papers in Thematic Issues
Advancements in Brain Tumor Detection and Treatment using Machine Learning, Deep Learning, and Blockchain Technology
Brain tumors are among the most challenging diseases to diagnose and treat, requiring specialized expertise and advanced technology for accurate detection and effective treatment. In recent years, machine learning and deep learning algorithms have shown promise in improving the accuracy and efficiency of brain tumor detection through medical imaging analysis. ...read more
Advances of Biometric Data Analysis to Boost Intelligent Applications
With the rapid development of artificial intelligence (AI) technology, more and more intelligent devices and applications are appearing in our daily lives, such as smart home, smart agriculture, health diagnosis, educational support, and environmental monitoring. Interaction with these devices or applications has become a pressing issue that can greatly improve ...read more
Attainment of SDGs through the Advancement in Solar Energy Systems
With less than a decade until we reach 2030, it is crucial to address the deep inequalities affecting not only our health but also our quality of life, and the economy of countries worldwide. Few of the UN's Sustainable Development Goals (SDGs) can be directly and indirectly achieved through the ...read more
Emerging Intelligent Computing Techniques and their Applications Using Machine Learning
This special issue will aim to discuss computational intelligence approaches, initiatives and applications in engineering and science fields (including Machine Intelligence, Mining Engineering, Modeling and Simulation, Computer, Communication, Networking and Information Engineering, Systems Engineering, Innovative Computing Systems, Adaptive Technologies for Sustainable Growth, and Theoretical and Applied Sciences). This collection should ...read more
Related Journals
Recent Patents on Engineering
12
1