Coupled field-circuit problems: trends and accomplishments

Tsukerman, Igor; Konrad, A.; Meunier, G.; Sabonnadière, Jean‐Claude

doi:10.1109/20.250733

Cited by 101 publications

(21 citation statements)

References 28 publications

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“…Especially to optimize and analyze geometry, nonlinearity etc., the coupling of electric networks with distributed models of electrical machines, e.g. transformers, is important, [27].…”

Section: Coupling Typesmentioning

confidence: 99%

Dynamic Iteration for Coupled Problems of Electric Circuits and Distributed Devices

Bartel¹,

Brunk²,

Günther³

et al. 2013

SIAM J. Sci. Comput.

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Coupled systems of differential-algebraic equations (DAEs) may suffer from instabilities during a dynamic iteration. For a general dynamic iteration, we extend the existing analysis on recursion estimates, error transport and stability to a general DAE setting. In this context, we discuss the influence of certain coupling structures and the computational sequence of the subsystems on the rate of convergence. Furthermore, we investigate convergence and divergence for two coupled problems stemming from refined electric circuit simulation in detail. These are the semiconductorcircuit and field-circuit coupling. As a result of our analysis, we quantify the convergence rate and behavior also using Lipschitz constants and suggest an enhanced modeling of the coupling interface in order to improve convergence.

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“…Especially to optimize and analyze geometry, nonlinearity etc., the coupling of electric networks with distributed models of electrical machines, e.g. transformers, is important, [27].…”

Section: Coupling Typesmentioning

confidence: 99%

Dynamic Iteration for Coupled Problems of Electric Circuits and Distributed Devices

Bartel¹,

Brunk²,

Günther³

et al. 2013

SIAM J. Sci. Comput.

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“…The Brushless DC (BLDC) motors are a good choice for applications that require high reliability, high efficiency and high power-to-volume ratio. They are products of multidisciplinary areas including electrical, mechanical and control engineering (Chen et al, 2007;Hemati et al, 1990;De Gersem et al, 2000;Dular et al, 1999;Tsukerman et al, 1993). Precision and performance are determined not only by electromechanical design but also by control methods.…”

Section: Introductionmentioning

confidence: 99%

Infinite-time linear–quadratic optimal control of the BLDC motor exploiting a nonlinear finite element model

Bernat¹,

Stępień

Stranz

et al. 2017

COMPEL

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Purpose This paper aims to present a nonlinear finite element model (FEM) of the Brushless DC (BLDC) motor and the application of the optimal linear–quadratic control-based method to determine the excitation voltage and current waveform considering the minimization of the energy injected to the input circuit and energy lost. The control problem is designed and analyzed using the feedback gain strategy for the infinite time horizon problem. Design/methodology/approach The method exploits the distributed parameters, nonlinear FEM of the device. First, dynamic equations of the BLDC motor are transformed into a suitable form that makes an ARE (algebraic Riccati equation)-based control technique applicable. Moreover, in the controller design, a Bryson scaling method is used to obtain desirable properties of the closed-loop system. The numerical techniques for solving ARE with the gradient damping factor are proposed and described. Results for applied control strategy are obtained by simulations and compared with measurement. Findings The proposed control technique can ensure optimal dynamic response, small steady-state error and energy saving. The effectiveness of the proposed control strategy is verified via numerical simulation and experiment. Originality/value The authors introduced an innovative approach to the well-known control methodology and settled their research in the newest literature coverage for this issue.

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“…The interest of the electric circuit simulation community in embedding PDEs is rather recent because of the increased computational effort, while considering a surrounding circuitry has been very popular in field simulation for a long time. This explains why most research in field-circuit coupling originates in the latter community (Bedrosian, 1993;Lombard and Meunier, 1993;Tsukerman, 1993). Besides couplings between magnetic fields and electric circuits, couplings with magnetic circuits have been initiated (Philips, 2002;.…”

Section: Introductionmentioning

confidence: 99%

“…Later on, the method itself became an object of research. The technique was made more general (Charpentier et al, 1998;Dular et al, 1999a, b;Tsukerman, 1993) and appropriate interpretations integrating the field and circuit concepts were presented (Kettunen, 2001;De Gersem et al, 2004;Hiptmair and Sterz, 2005;Dular et al, 2006). Field-circuit coupling has been combined with the finite-difference (FD) method, finite-element (FE) method, finite integration technique (FIT) (De Gersem and Weiland, 2004a) and the boundary-element (BE) method (Davey and Klimpke, 2000).…”

Section: Introductionmentioning

confidence: 99%

Winding functions in transient magnetoquasistatic field-circuit coupled simulations

Schöps

Gersem

Weiland

2013

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

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Purpose – The purpose of this paper is to review the mutual coupling of electromagnetic fields in the magnetic vector potential formulation with electric circuits in terms of (modified) nodal and loop analyses. It aims for an unified and generic notation. Design/methodology/approach – The coupled formulation is derived rigorously using the concept of winding functions. Strong and weak coupling approaches are proposed and examples are given. Discretization methods of the partial differential equations and in particular the winding functions are discussed. Reasons for instabilities in the numerical time domain simulation of the coupled formulation are presented using results from differential-algebraic-index analysis. Findings – This paper establishes a unified notation for different conductor models, e.g. solid, stranded and foil conductors and shows their structural equivalence. The structural information explains numerical instabilities in the case of current excitation. Originality/value – The presentation of winding functions allows to generically describe the coupling, embed the circuit equations into the de Rham complex and visualize them by Tonti diagrams. This is of value for scientists interested in differential geometry and engineers that work in the field of numerical simulation of field-circuit coupled problems.

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Coupled field-circuit problems: trends and accomplishments

Cited by 101 publications

References 28 publications

Dynamic Iteration for Coupled Problems of Electric Circuits and Distributed Devices

Dynamic Iteration for Coupled Problems of Electric Circuits and Distributed Devices

Infinite-time linear–quadratic optimal control of the BLDC motor exploiting a nonlinear finite element model

Winding functions in transient magnetoquasistatic field-circuit coupled simulations

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