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Journal ArticleDOI

Optimization of Three-Phase Induction Motor Design Part I: Formulation of the Optimization Technique

TLDR
In this article, a more comprehensive study on the optimization of a three-phase induction motor design was performed, including the relationship between motor cost, efficiency, and power factor; the effect of the properties of the electrical steel; and other effects as they occur in an optimal design.
Abstract
This two-part paper deals with the optimization of the induction motor designs with respect to cost and efficiency. Most studies on the design of an induction motor using optimization techniques are concerned with the minimization of the motor cost and describe the optimization technique that was employed, giving the results of a single (or several) optimal design(s). In the present paper, a more comprehensive study on the optimization of a three-phase induction motor design was performed. This includes the relationship between motor cost, efficiency, and power factor; the effect of the properties of the electrical steel; and other effects as they occur in an optimal design. In addition, the optimization procedure that was used in this paper includes a design program, where some of the secondary parameters (which are called here variable constants), are modified according to the optimal results, in contrast to other studies where these parameters remain constant for the entire optimization. In this part, a new mathematical formulation of the optimization problem of the induction motor is presented.

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Citations
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Journal ArticleDOI

Multiobjective Optimization of Induction Machines Including Mixed Variables and Noise Minimization

TL;DR: A fast analytical model of a variable-speed induction machine which calculates both motor performances and sound power level of electromagnetic origin is described and a modified NSGA-II algorithm handling mixed variables is detailed.
Dissertation

Reduction of magnetic noise in PWM-supplied induction machines - low-noise design rules and multi-objective optimization

TL;DR: In this paper, the authors focus on the reduction of the audible magnetic noise radiated by induction machines due to air-gap radial Maxwell forces in variable-speed traction application (e.g. subways and light-rail vehicles).
Journal ArticleDOI

Geometric parametrization and constrained optimization techniques in the design of salient pole synchronous machines

TL;DR: The geometry of a salient pole generator so as to achieve a desired field configuration in the airgap is used as an illustrative numerical example to demonstrate the geometric parametrization technique, emphasize the importance of constraints in engineering design, and highlight the advantageous features of the augmented Lagrangian multiplier method for nonlinear constrained optimization.
Journal ArticleDOI

Limitations/capabilities of electric machine technologies and modeling approaches for electric motor design and analysis in plug-in electric vehicle applications

TL;DR: The electrical machine (EM) is a key component in plug-in electric and hybrid vehicle (PEV) propulsion systems as discussed by the authors, and it must be designed for high torque/power densities, wide speed range, over load capability, high efficiency at all speeds, low cost and weight, fast acceleration and deceleration.
Journal ArticleDOI

Comparison of two optimization techniques as applied to three-phase induction motor design

TL;DR: In this paper, two advanced optimization techniques, the boundary search along active constraints and the Han-Powell method, have been compared as applied to a 5-hp three-phase induction motor design.
References
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Journal ArticleDOI

A Globally Convergent Method for Nonlinear Programming

TL;DR: In this paper, a stepsize procedure is proposed to maintain monotone decrease of an exact penalty function, and the convergence of the damped Newton method is globalized in unconstrained optimization.
Journal ArticleDOI

Algorithms for nonlinear constraints that use lagrangian functions

TL;DR: A view of the progress and understanding that has been achieved during the last eight years about Lagrangian functions and its relevance to practical algorithms is given.
Book

Nonlinear programming

Journal ArticleDOI

Practical Least pth Optimization of Networks

TL;DR: It is demonstrated how easily and efficiently extremely near minimax results can be achieved on a discrete set of sample points.
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