Fuzzy Fitness Distance Balance Gradient-Based Optimization Algorithm (fFDBGBO): An Application to Design and Performance Optimization of PMSM
Küçük Resim Yok
Tarih
2025
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee-Inst Electrical Electronics Engineers Inc
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The exceptional properties of Permanent Magnet Synchronous Motors (PMSMs), including their small construction, high power-torque density, and high efficiency, make them one of the most popular electrical machines. However, the motor structure needs to be optimized for circumstances like boosting the PMSM's energy efficiency, optimizing output power, and lowering motor weight and cogging torque. This research aims to identify the optimal values for the parameters essential to achieving the most efficient design of a 15 kW PMSM. For this purpose, a new optimization algorithm is proposed. This proposed algorithm is an application of the fuzzy logic-based fitness distance balance design to the gradient-based optimization algorithm (GBO). The developed algorithm is called fuzzy Fitness Distance Balance Gradient-Based Optimization (fFDBGBO) algorithm. The proposed algorithm and various optimization algorithms with effective results in the literature were tested for the fitness function determined to find the optimal values of Embrace, Offset, Skew Width, Magnet Thickness, and slot bottom width (Bs1) of PMSM. The results indicate that the suggested algorithm achieves better performance than rival algorithms in terms of effectiveness. Compared to the GBO algorithm, the proposed fFDBGBO method achieves a 0.2979% increase in efficiency. Compared to other algorithms, the suggested algorithm's objective function has the highest slot fill factor (49.9995%), yet it still complies with the specified limit value. Relative to the initial design, the motor efficiency achieved with the fFDBGBO algorithm improved from 91.7788% to 93.0366%, while the magnet weight decreased from 2.14837 to 2.09475, and the total motor weight remained approximately the same as 53.2286 kg and 54.0436 kg.
Açıklama
Anahtar Kelimeler
Optimization, Motors, Torque, Magnetic flux, Forging, Genetic algorithms, Rotors, Permanent magnets, Torque measurement, Permanent magnet motors, Permanent magnet synchronous motor, motor parameter optimization, gradient-based optimization, fuzzy fitness distance balance
Kaynak
IEEE Access
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
13
