Multiobjective Optimization of Switched Reluctance Motors Based on Design of Experiments and Particle Swarm Optimization

Ma, Cong; Qu, Liyan

doi:10.1109/tec.2015.2411677

Cited by 194 publications

(119 citation statements)

References 33 publications

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“…The process of design is complex with optimization at many levels. Usually in optimal design process definition of objective function, constraint function and independent variables are required (17) . The objective functions can be cost of active material required, or overall weight/dimensions or performance parameters.…”

Section: Design Considerations In Bdfrmmentioning

confidence: 99%

Optimal Design and Comparative Analysis of Different Configurations of Brushless Doubly Fed Reluctance Machine

Kunte¹,

Bhawalkar²,

Gopalakrishnan³

et al. 2017

IEEJ Journal IA

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The simple and robust construction of reluctance machines and the fact that they need an unsophisticated control have reignited interest in these machines. The constructional modifications and new configurations such as brushless doubly fed reluctance machines (BDFRM) show superior performance compared to their traditional counterparts, especially in variable speed applications such as pumps and wind generators. The design of BDFRM is different from other machines, as there are unusual pole combinations of stator and rotor besides the absence of a winding on the rotor. The operation and performance of the machine greatly depends on the mutual interaction between the stator windings. This interaction is modulated by the rotor with increased saliency. This paper examines a few critical issues in the design of BDFRM. Design optimization is performed using the gradient method from non-linear programming for 6-4-2 pole and 8-6-4 pole configurations of BDFRM. The performance of these optimized machines is examined through finite element analysis employing MAXWELL 16 software and then compared with 2 kW prototypes constructed for laboratory use. A comparative analysis of the two configurations are presented and experimental results show that the BDFRM with the 8-6-4 ducted rotor is superior to BDFRM with the 6-4-2 reluctance and ducted rotor configurations.

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Section: Design Considerations In Bdfrmmentioning

confidence: 99%

Optimal Design and Comparative Analysis of Different Configurations of Brushless Doubly Fed Reluctance Machine

Kunte¹,

Bhawalkar²,

Gopalakrishnan³

et al. 2017

IEEJ Journal IA

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show abstract

“…The reduction of torque ripple is an active research topic and improvement strategies include machine design optimization [7][8][9][10][11] and advanced control techniques [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Effects of Winding Connection on Performance of a Six-Phase Switched Reluctance Machine

Deng

Mecrow

Martin

et al. 2018

IEEE Trans. Energy Convers.

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“…Lengthy FEM solver based design computations resulted in the previous FEM based Differential Evolution (DE) optimization attempts to be rather restricted in terms of the number of objective function calls, with most such investigations taking more than 10 hours to complete and the number of design points explored being limited to about 200 [11] -with simultaneous three objectives to be optimized this number of design points appears to be insufficient. Furthermore, the same difficulty is encountered with the use of Design of Experiments (DoE) based optimizations as the number of objective function calls based on FEM solver is large even if the number of design objectives is less than 3 [12]. Single design-objective based optimizations have shown some success in the past for the machines which exhibited good initial design configurations, i.e.…”

Section: Introductionmentioning

confidence: 99%

Rapid multi‐objective design optimisation of switched reluctance motors exploiting magnetic flux tubes

Stuikys

Sykulski

2018

IET Science, Measurement & Technology

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The magnetic design of Switched Reluctance (SR) motors is inherently a hierarchical process. The design cycle progresses through distinct stages where the accuracy improves but computing times increase greatly, thus it often becomes impractical to furnish extensive multi-objective optimization required to accomplish the optimal design. In order to enable rapid and accurate optimization of SR motors an improved reduced-order computational method of flux tubes is implemented to complement and practically replace the time consuming 2D finite element based magnetic analysis. The paper demonstrates how the use of the improved flux tubes approach to evaluate objective functions results in substantially faster while still accurate multi-objective optimization of SR motors. IntroductionSwitched Reluctance (SR) machines are often regarded as having the simplest mechanical design [1]- [3] compared to other conventional electric machines, such as permanent magnet dc, synchronous reluctance or induction, as they are brushless and have no permanent magnets (PM) or windings on the rotor. These design features make SR machines well suited to a wide range of applications where variable speed operation is required, such as general traction or pump drives. Moreover, the mechanical robustness of SR machines offers cheaper maintenance and better tolerance to harsh environments in which other types of machines cannot operate.Since SR motors are capable of operating in both constant torque and constant power regimes over a wide speed range [4], [5], this operating feature also makes them suitable for the automotive propulsion applications, where the absence of permanent magnets is considered necessary since this industry is very cost sensitive and insists on immunity from unforeseen material price fluctuations, as experienced by PM materials [6]. However, the absence of PM parts makes the SR machines much more difficult to control [7] due to their nonlinear torque-per-ampere characteristic. This operational nonlinearity is a result of the nonlinear magnetic characteristic as the machine's magnetic circuit becomes heavily saturated even during steady-state operation [8].Considering that SR machines are very nonlinear, they require complex analysis and robust design procedures to adequately predict their performance. Until now a rather limited success has been achieved in terms of accurate analytical design procedures for SR machines [9], [10] to provide satisfactory quantification of the machine performance. Most of the magnetic analysis and design is nowadays performed by numerical simulations based on a finite element method (FEM) in order to capture the detailed shape and allow for magnetic nonlinearity. The FEM based solutions can be accurate; however, they are time consuming and lack the intuitive insight into the cause-and-effect relationships between numerous machine design parameters. Moreover, the FEM solutions give only part of the

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Multiobjective Optimization of Switched Reluctance Motors Based on Design of Experiments and Particle Swarm Optimization

Cited by 194 publications

References 33 publications

Optimal Design and Comparative Analysis of Different Configurations of Brushless Doubly Fed Reluctance Machine

Optimal Design and Comparative Analysis of Different Configurations of Brushless Doubly Fed Reluctance Machine

Effects of Winding Connection on Performance of a Six-Phase Switched Reluctance Machine

Rapid multi‐objective design optimisation of switched reluctance motors exploiting magnetic flux tubes

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