Design Optimization of Transversely Laminated Synchronous Reluctance Machine for Flywheel Energy Storage System Using Response Surface Methodology

Moghaddam, Hossein Azizi; Vahedi, A.; Ebrahimi, Saeed Hasan

doi:10.1109/tie.2017.2716877

Cited by 45 publications

(19 citation statements)

References 17 publications

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“…while sweeping the whole − plane will be much time-consuming [22]. To reduce the computational burden as much as possible without loss of accuracy, the method of response surface methodology (RSM) [23] combined with CE-FEA is utilized to obtain the inverse machine model as follows with a design as an example:…”

Section: Armature Current Calculation For the Representative Pointsmentioning

confidence: 99%

Computationally Efficient Optimization of a Five-Phase Flux-Switching PM Machine Under Different Operating Conditions

Chen

Liu

Demerdash

et al. 2019

IEEE Trans. Veh. Technol.

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This paper investigates the comparative design optimizations of a five-phase outer-rotor flux-switching permanent magnet (FSPM) machine for in-wheel traction applications. To improve the comprehensive performance of the motor, two kinds of large-scale design optimizations under different operating conditions are performed and compared, including the traditional optimization performed at the rated operating point and the optimization targeting the whole driving cycles. Three driving cycles are taken into account, namely, the urban dynamometer driving schedule (UDDS), the highway fuel economy driving schedule (HWFET), and the combined UDDS/HWFET, representing the city, highway, and combined city/highway driving, respectively. Meanwhile, the computationally efficient finite-element analysis (CE-FEA) method, the cyclic representative operating points extraction technique, as well as the response surface methodology (in order to minimize the number of experiments when establishing the inverse machine model), are presented to reduce the computational effort and cost. From the results and discussion, it will be found that the optimization results against different operating conditions exhibit distinct characteristics in terms of geometry, efficiency, and energy loss distributions. For the traditional optimization performed at the rated operating point, the optimal design tends to reduce copper losses but suffer from high core losses; for UDDS, the optimal design tends to minimize both copper losses and PM eddy-current losses in the low-speed region; for HWFET, the optimal design tends to minimize core losses in the high-speed region; for the combined UDDS/HWFET, the optimal design tends to balance/compromise the loss components in both the low-speed and high-speed regions. Furthermore, the advantages of the adopted optimization methodologies versus the traditional procedure are highlighted. SECTION I. Introduction As the most important component in the traction system of electric vehicles (EVs), electric machines should be designed to have high torque density to provide the required acceleration capability in the low-speed region, and high flux-weakening capability to expand the constant-power speed range in the high-speed region. Compared to the conventional machine topologies commonly used in this application, e.g., induction motors [1], switched reluctance motors [2], and permanent magnet synchronous motors (PMSM) [3], flux-switching permanent magnet (FSPM) machines have attracted more attention due to their simple and robust rotor, high torque density, and favorable thermal dissipation [4]. Recently, FSPM machines with various configurations such as original configurations [5], C-and E-core configurations [6], have been presented for a diversity of applications. However, most of these configurations are limited to three-phase inner-rotor machines. Multi-phase motors have shown advantages in terms of their fault-tolerance capability, low torque pulsation, and additional degrees of freedom in the associated control sy...

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Section: Armature Current Calculation For the Representative Pointsmentioning

confidence: 99%

Computationally Efficient Optimization of a Five-Phase Flux-Switching PM Machine Under Different Operating Conditions

Chen

Liu

Demerdash

et al. 2019

IEEE Trans. Veh. Technol.

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“…Then, the optimization algorithms can apply to these models 9 . The popular approximating models are kriging model (KM), response surface methodology (RSM), and artificial neural network (ANN) 10‐12 All of the approximating models need the initial samples data.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis and multiobjective design optimization of flux switching permanent magnet motor using MLP‐ANN modeling and NSGA‐II algorithm

Mahmouditabar

Vahedi

Mosavi

et al. 2020

Int Trans Electr Energ Syst

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Summary The flux switching permanent magnet (FSPM) motor is relatively a new topology of the permanent magnet (PM) motors, which both PM and armature winding are placed at the stator. This feature leads to more robust design, better heat dissipation, and a proper option for a wide range of industrial applications. The critical part of the development of FSPM motor is the design optimization of the structure to improve the electromagnetic performance of the motor. In this article, first to reduce the computation time and required memory of the optimization procedure, the multiobjective sensitivity analysis based on design of experiment is performed to specify the most effective parameters on the objectives. Then, the initial samples data of the optimization procedure is obtained by 2D finite element method (FEM) model of the FSPM motor, which is validated by the prototype of the motor. Furthermore, based on FEM results the multilayers perceptron artificial neural network for the approximation of relation between design variables and objectives is implemented. Finally, using the nondominated sorting genetic algorithm‐II, the optimization procedure of the FSPM motor is done. The accuracy of the presented optimization procedure is validated by a comparison of the initial prototype and final design of the motor.

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“…Despite these advantages, the main drawbacks of SyncRel machines are the poor power factor and high torque ripple [11]. Therefore, the proper SyncRel machine design is an open challenge for researchers to minimise torque oscillations through the rotor skewing, suitable choice of the number of applied flux barriers with respect to stator slots configuration and/or barrier geometry optimisation [11][12][13][14][15][16][17][18]. In [17], an analysis regarding asymmetrical barriers was presented in detail, hence this paper focuses on the optimisation of the barriers that are symmetric with regards to the same arch centre point (see Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, a new approach has been adopted in the literature for the optimum design of SyncRel machines, combining finite element analysis (FEA) with artificial intelligence (AI) techniques [18][19][20][21][22][23][24][25]. In [19] the geometry of a three-layer and a five-layer flux barrier rotor has been optimised using different AI techniques: genetic algorithms (GAs), differential evolution (DE) and simulated annealing (SA).…”

Section: Introductionmentioning

confidence: 99%

Synchronous reluctance machine geometry optimisation through a genetic algorithm based technique

Ruba

Jurca

Czumbil

et al. 2018

IET Electric Power Applications

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In this study, the design optimisation of a synchronous reluctance machine for light electric vehicles is proposed, to increase efficiency and reduce torque ripples. The existing machine was structurally optimised, using dedicated genetic algorithms, replacing only the rotor and keeping the stator and it's winding untouched. Starting from the original design of the rotor implemented in Flux2D, a finite element analysis software, and the genetic algorithm optimisation implemented in Matlab, a complex co-simulation was accomplished to obtain a rotor architecture that increases the machine's performances and decreases the torque ripples. By this, performing rotor skewing is not needed any more, hence the torque loss due to it was cancelled. The optimised rotor design increases the machine performances by higher mean torque, no skewing, <8% torque ripples, higher efficiency and better inductance characteristics. Comparative results obtained both in simulations and experimental measurements prove positive outcomes of the optimisation process.

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Design Optimization of Transversely Laminated Synchronous Reluctance Machine for Flywheel Energy Storage System Using Response Surface Methodology

Cited by 45 publications

References 17 publications

Computationally Efficient Optimization of a Five-Phase Flux-Switching PM Machine Under Different Operating Conditions

Computationally Efficient Optimization of a Five-Phase Flux-Switching PM Machine Under Different Operating Conditions

Sensitivity analysis and multiobjective design optimization of flux switching permanent magnet motor using MLP‐ANN modeling and NSGA‐II algorithm

Synchronous reluctance machine geometry optimisation through a genetic algorithm based technique

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