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Both permanent magnet brushless DC motors and permanent magnet synchronous motors have attracted wide attention and are increasingly used in industrial high-performance applications in recent years. Those motors are known for their good electrical, magnetic and performance characteristics, but there is one parameter known as cogging torque that has a negative influence on the performance characteristics of the motor. This pulsating torque is generated as a result of the interaction between the stator teeth and the permanent magnets. The minimisation of the ripple of this torque in those permanent magnet motors is of great importance and is generally achieved by a special motor design which in the design process involves a variety of many geometrical motor parameters. In this research work, a novel approach will be introduced where two different nature-inspired algorithms, such as genetic algorithm (GA) and cuckoo search (CS) algorithm are used as an optimisation tool, in which the defined equation for the maximum value of the cogging torque is applied as an objective function. Therefore, a proper mathematical presentation of the maximum value of the cogging torque for the analysed synchronous motor is developed and implemented in the research work. For a detailed analysis of the three different motor models, the initial motor and the two optimised motor models are modelled and analysed using a finite element method approach. The cogging torque is analytically and numerically calculated and the results for all the models are presented.
Wydawca
Czasopismo
Rocznik
Tom
Strony
204--217
Opis fizyczny
Bibliogr. 39 poz., rys., tab.
Twórcy
autor
- Ss.Cyril and Methodius University, Faculty of Electrical Engineering and Information Technologies, Skopje, North Macedonia
autor
- Ss.Cyril and Methodius University, Faculty of Electrical Engineering and Information Technologies, Skopje, North Macedonia
Bibliografia
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- Benlamine, R., Dubas, F., Randi, S. A., Lhotellier, D. and Espanet, C., (2013). Design by Optimization of an Axial-Flux Permanent-Magnet Synchronous Motor Using Genetic Algorithms. 2013 International Conference on Electrical Machines and Systems (ICEMS), 23–26, pp. 13–17.
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- Bianchi, N. and Bolognani, S. (2000). Reducing Torque Ripple in PM Synchronous Motors by Pole Shifting. Proceedings of the International Conference on Electrical Machines ICEM, 28–30, pp. 1222–1226.
- Chitara, D., Niazi, K. R., Swarnkar, A., and Gupta, N., (2018). Cuckoo Search Optimization Algorithm for Designing of a Multimachine Power System Stabilizer. IEEE Transactions on Industry Applications, 54(4), pp. 3056–3065.
- Cvetkovski, G. and Petkovska, L. (2016). Multi-Objective Approach of Design Optimization of Axial Flux Permanent Magnet Motor. International Journal of Applied Electromagnetics and Mechanics, 51(s1), pp. S115–S123.
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Bibliografia
Identyfikator YADDA
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