Design Optimization of Air-Cored PMLSM With Overlapping Windings by Multiple Population Genetic Algorithm

Li, Liyi; Tang, Yongbin; Pan, Donghua

doi:10.1109/tmag.2014.2329096

Cited by 40 publications

(9 citation statements)

References 5 publications

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“…2. When analyzing the magnetic field of the DSLM, the motor's magnetic field is often simplified as a two-dimensional magnetic field, lateral end effects are often not considered, the demagnetization curve of the magnet is assumed to be a straight line, and the permeability of the secondary core is assumed to be infinite [12][13] . Based on these assumptions and idealizations, the magnetic field of the motor can be calculated using Eq.…”

Section: Structure Of Dslmmentioning

confidence: 99%

New optimization design method for a double secondary linear motor based on R-DNN modeling method and MCS optimization algorithm

Wang

Zhao

Zhou

et al. 2020

Chin. J. Electr. Eng.

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Traditional linear motor optimization methods typically use analytical models combined with intelligent optimization algorithms. However, this approach has disadvantages, e.g., the analytical model might not be accurate enough, and the intelligent optimization algorithm can easily fall into local optimization. A new linear motor optimization strategy combining an R-deep neural network (R-DNN) and modified cuckoo search (MCS) is proposed; additionally, the thrust lifting and thrust fluctuation reductions are regarded as optimization objectives. The R-DNN is a deep neural network modeling method using the rectified linear unit (RELU) activation function, and the MCS provides a faster convergence speed and stronger data search capability as compared with genetic algorithms, particle swarm optimization, and standard CS algorithms. Finally, the validity and accuracy of this work are proven based on prototype experiments.

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Section: Structure Of Dslmmentioning

confidence: 99%

New optimization design method for a double secondary linear motor based on R-DNN modeling method and MCS optimization algorithm

Wang

Zhao

Zhou

et al. 2020

Chin. J. Electr. Eng.

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“…There is obviously an optimum design for a range of duct sizes which also accounts for strong non-linearity due to the laminated steel characteristics. Optimization has been recently used for a variety of machine design studies [13]- [15]. Differential evolution (DE), which includes mutation, crossover, and possibly selection, is a highly recommended method for multi-objective design.…”

Section: Large Scale Automatic Optimization Studymentioning

confidence: 99%

Establishing the Power Factor Limitations for Synchronous Reluctance Machines

et al. 2015

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This paper discusses a "Goodness" index and introduces a "Badness" factor for electric machines with special reference to synchronous reluctance motors. This factor is then used in conjunction with computationally-efficient finite element electromagnetic analysis and a differential evolution optimization algorithm in order to carry out a large-scale design study under comparable specifications with an induction motor. It is shown that for synchronous reluctance machines, careful rotor geometry optimization can improve the performance and that the inherent limitations, including those for the power factor, can be systematically established. The correlations for specific average torque, copper and core losses, and efficiency are also discussed.

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“…Hasanien et al [7] used particle swarm optimisation (PSO) to improve the analytical thrust of the motor. Li et al [8] introduced the multiple population genetic algorithm to optimise the air-cored PMLSM with overlapping windings. The aforementioned analytical method where the constraints and independent variables are given analytically with an equivalent magnetic circuit.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of permanent magnet linear synchronous motors based on Taguchi method

Song

Dong

Zhao

et al. 2017

IET Electric Power Applications

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This study focuses on optimisation design of permanent magnet linear synchronous motors that are applied in laser engraving machines with no cutting force. Traditional analytical optimisation method based on magnetic field with particle swarm optimisation algorithm was introduced to obtain the best combination of motor structure parameters. By contrast, the novel optimisation design method-Taguchi method based on orthogonal array was proposed to optimise the thrust and thrust ripple. After the design of experiments using finite-element analysis, the relative importance of each design parameter was estimated in detail. Experimental results of prototype can certify the superiority and validity of Taguchi optimisation method.

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Design Optimization of Air-Cored PMLSM With Overlapping Windings by Multiple Population Genetic Algorithm

Cited by 40 publications

References 5 publications

New optimization design method for a double secondary linear motor based on R-DNN modeling method and MCS optimization algorithm

New optimization design method for a double secondary linear motor based on R-DNN modeling method and MCS optimization algorithm

Establishing the Power Factor Limitations for Synchronous Reluctance Machines

Optimal design of permanent magnet linear synchronous motors based on Taguchi method

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