Multi-Objective Optimization Design and Analysis of V-Shape Permanent Magnet Synchronous Motor

Wang, Sheng‐Ching; Nien, Yu-Cheng; Huang, San-Ming

doi:10.3390/en15103496

Cited by 17 publications

(7 citation statements)

References 23 publications

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“…With the central composite design method, the response values ρ Tm and k ripple are acquired by the FEM. The ρ Tm and k ripple are presented in Equation (19).…”

Section: Optimization Objectives and Constraintsmentioning

confidence: 99%

“…However, improving the efficiency and accuracy of parameter optimization requires a huge effort to establish the relationship between the input and output of the SVM model. The multi-objective optimal design method based on the response surface method (RSM) only requires a limited amount of sample data to obtain a more accurate model, which greatly improves the optimization efficiency [19,20]. In the type of the proposed SCM-AFPM motor, a notable feature is that its PMs arrangement is no longer limited to one single type, and there are two types of PMs arrangement employed in the rotor.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Optimization Design of a Stator Coreless Multidisc Axial Flux Permanent Magnet Motor

et al. 2022

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The stator coreless axial flux permanent magnet (AFPM) motor with a compact structure, low torque ripple, and high efficiency is particularly suitable as a motor for electric propulsion systems. However, it still requires great effort to design an AFPM motor with higher torque density and lower torque ripple. In this paper, a stator coreless multidisc AFPM (SCM-AFPM) motor with a three-rotor and two-stator topology is proposed. To reduce rotor mass and increase torque density, the proposed SCM-AFPM motor adopts the hybrid permanent magnets (PMs) array with Halbach PMs in the two-terminal rotor and the conventional PMs array in the middle rotor. In addition, a multi-objective optimization model combining response surface method (RSM) and genetic algorithm (GA) is proposed and applied to the proposed SCM-AFPM motor. With the help of the three-dimensional finite-element analysis (3-D FEA), it is found that the torque ripple of the optimized SCM-AFPM motor is 4.73%, while it is 6.21% for the initial motor. Its torque ripple is reduced by 23.8%. Therefore, the proposed multi-objective optimization design method can quickly and reliably obtain the optimal design of the SCM-AFPM motor.

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“…With the central composite design method, the response values ρ Tm and k ripple are acquired by the FEM. The ρ Tm and k ripple are presented in Equation (19).…”

Section: Optimization Objectives and Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization Design of a Stator Coreless Multidisc Axial Flux Permanent Magnet Motor

et al. 2022

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“…This method reduces model parameters, thereby simplifying the optimization process. Recently, the response surface method has become a promising approach for analyzing and optimizing electric machine design, with applications in various areas of motor optimization [13][14][15]. Therefore, this method is well-suited for optimizing and predicting the response variables of complex electric machine systems.…”

Section: Introductionmentioning

confidence: 99%

Torque Optimization Strategy for Outer Rotor Permanent Magnet Brushless DC Motor based on Metamodel and CRITIC-TOPSIS Method

Ye,

Zeng,

Sun

et al. 2024

Preprint

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A metamodel-based torque optimization strategy is proposed for the efficient design and electromagnetic performance optimization of outer rotor permanent magnet brushless DC motors (ORPMBLDCM), which is based on the dimensionality reduction and generalization principles in statistical modeling theory. The strategy combines Criteria Importance through Intercrieria Correlation and Technology for Order Preference by Similarity to an Ideal Solution (CRITIC-TOPSIS) theory. A parameterized two-dimensional finite element calculation model is established using a 10-pole 12-slot ORPMBLDCM as an example. The optimization objectives are set to be the low cogging torque, low torque ripple, and high average electromagnetic torque. The actual model is approximated using coefficient of prognosis and the constructed optimal prediction metamodel, based on variance-based sensitivity analysis. Multi-objective evolutionary algorithms are used to optimize the objectives and obtain the Pareto optimal solution set. Finally, the CRITIC-TOPSIS method is used to globally rank the feasible solution set and determine the optimal structural dimension parameters. The results of the finite element analysis demonstrate a 77.9\% reduction in cogging torque, a 18.5\% improvement in average electromagnetic torque, and a 14.5\% reduction in torque ripple. The effectiveness of torque optimization strategy using metamodel and CRITIC-TOPSIS method in improving the performance of ORPMBLDCM has been validated. The presented torque optimization strategy can guide the design of brushless DC motors.

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“…The proposed design aims to maximize the maximum torque and rated efficiency of BLDC motor and minimize cogging torque. 18 Wang et al 19 proposed a multi-objective optimization algorithm to determine the rotor design parameters which maximize the output torque of the PMSM over three different load conditions (no load, rated load, and maximum speed load). El-Nemr et al 20 proposed an optimal design methodology for SRM using the non-dominated sorting genetic algorithm (NSGA-II) optimization technique.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of the hollow shaft direct drive motor

Wang

Gong

Liu

2023

Advances in Mechanical Engineering

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Surface permanent magnet synchronous motor (SPMSM) is widely used in low-speed and high torque permanent magnet synchronous motor. A multi-objective optimization method of hollow shaft direct drive motor (HSDDM) for double direct drive feed system (DDFS) is proposed in this paper. Several dimensions of HSDDM are considered in the proposed design procedure including pole embrace, thickness of magnet, eccentric distance, and air gap length. A multi-objective optimization model is established to minimize cogging torque, maximize efficiency, and minimize the magnet weight. The Optimized Latin hypercube sampling (OLHS) is used to design the experimental samples, and the sampling results are calculated by the finite element method (FEM). The Kring approximate model is established according to the sampling results. Based on the established approximate model, NSGA II multi-objective genetic algorithm is used to optimize the HSDDM. Compared with that before optimization, the efficiency after optimization is increased by 4.08%, the cogging torque is reduced by 86.78%, and the magnet weight is reduced by 20.24%. Eventually, the integration of NSGA-II and FEM provides an effective approach to obtain the optimal design of HSDDM.

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Multi-Objective Optimization Design and Analysis of V-Shape Permanent Magnet Synchronous Motor

Cited by 17 publications

References 23 publications

Multi-Objective Optimization Design of a Stator Coreless Multidisc Axial Flux Permanent Magnet Motor

Multi-Objective Optimization Design of a Stator Coreless Multidisc Axial Flux Permanent Magnet Motor

Torque Optimization Strategy for Outer Rotor Permanent Magnet Brushless DC Motor based on Metamodel and CRITIC-TOPSIS Method

Multi-objective optimization of the hollow shaft direct drive motor

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