Magnetic shape memory (MSM) alloys are relatively new "smart" alloys which have enormous potential to be used in actuators, sensors and other electrical devices. Their large strain and considerable stress output can be controlled by magnetic fields or mechanical stresses. Maximum magnetic field-induced strain varies from 6 to 12% of the MSM element's length depending on its microstructure. However, very low operational temperature limit is one of the main drawbacks of conventional MSM alloys. This makes their application in high performance actuators challenging due to considerable power losses. This paper discusses different MSM actuator designs optimized particularly for large force output for pneumatic electromagnetic (EM) valve applications. The thermal problem is addressed through analyzing the heat transfer conditions of each particular design and the effects of different cooling systems. An energy-efficient operating cycle for varying actuator load that takes advantage of the shape memory effect is also proposed. This allows minimization of energy losses resulting in acceptable increase in temperature ensuring stable continuous actuation.Index Terms-Actuator design, magnetic shape memory alloys, electromagnetic analysis, thermal analysis, smart materials.

This paper proposes a novel analytical method for the analysis of the dynamics of electrical machines. The method is applied to the analysis of complex permanent magnet (PM)-type magnetic contactors (MCs), which exhibit strong magnetic non-linearities and a high portion of stray and leakage magnetic fluxes. The latter means that the analysis of PM-type MCs using traditional magnetic equivalent circuit (MEC) methods is impossible, thus requiring computationally expensive and time-consuming finite element analysis (FEA). To overcome the limitations of traditional MECs, the magnetic field distribution in PM-type MC is studied in great detail, and a novel non-linear dynamic MEC (ND-MEC) method is proposed. The accuracy of the ND-MEC method is comparable to that of FEA which is achieved by accounting for non-linear effects and dynamic changes in the magnetic flux distribution using a novel stray path elliptical function. Furthermore, the applicability of the ND-MEC is extended to the time domain by combining it with the time difference method (TDM). The complete method, referred to as the non-linear transient path energy method (NT-PEM), combines the ND-MEC, TDM, and a path energy method for the calculation of electromagnetic forces. The validity of the NT-PEM is verified by comparing it with 3D FEA and experimental results obtained from a PM-type MC prototype. The NT-PEM is a fast and inexpensive alternative to FEA, which is particularly advantageous when many designs must be analyzed and optimized while reducing analysis costs. The proposed method can also be applied to the analysis of emerging technologies dealing with multiphysics coupled problems, as in the case of smart materials.INDEX TERMS Magnetic contactor, magnetic equivalent circuit (MEC), nonlinear dynamics, permanent magnets, stray flux modeling.

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Convolutional Neural Networks (CNNs) and Deep Learning (DL) revolutionized numerous research fields including robotics, natural language processing, self-driving cars, healthcare, and others. However, DL is still relatively under-researched in physics and engineering. Recent works on DL-assisted analysis showed enormous potential of CNN applications in electrical engineering. This paper explores the possibility of developing an end-to-end DL analysis method to match or even surpass conventional analysis techniques such as finite element analysis (FEA) based on the ability of CNNs to predict the performance characteristics of electric machines. The required depth in CNN architecture is studied by comparing a simplistic CNN with three ResNet architectures. Studied CNNs show over 90% accuracy for an analysis conducted under a minute, whereas a FEA of comparable accuracy required 200 h. It is also shown that training CNNs to predict multidimensional outputs can improve CNN performance. Multidimensional output prediction with data-driven methods is further discussed in context of multiphysics analysis showing potential for developing analysis methods that might surpass FEA capabilities.

This is the accepted version of the paper.This version of the publication may differ from the final published version. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Magnetic shape memory (MSM) alloys are relatively new and very promising "smart" materials which respond to magnetic fields and exhibit the shape memory effect at room temperature. Maximum strain varies from 6 to 12% of the MSM element's length depending on its microstructure. The shape memory effect and magnetic field-induced reorientation of MSM twin variants in lowtemperature martensite phase are subject to an ongoing research for almost two decades. However, the magnetic field distribution in the MSM elements and effects of its varying magnetic permeability on bias magnetic field are not well studied. In this paper we present an extension to the existing modeling approach for MSM elements applicable to actuator design. The effects arising from single-crystal anisotropy and demagnetization effects due to non-homogeneous multi-variant MSM microstructure are studied and discussed. The proposed approach is validated by comparing computational results with previously reported measurement data. Permanent repository linkIndex Terms-Magnetic shape memory (MSM) alloys, MSM actuators, electromagnetic analysis, non-homogeneous permeability, magnetic anisotropy

Improving the efficiency and end-use of energy distribution can significantly reduce global energy consumption. As the magnetic contactor (MC) is the most common switchgear used for control in most grids, minimizing its energy consumption has motivated the development of a permanent magnet (PM) MC that exhibits several advantages over conventional solenoid MCs. However, analyzing the transient magnetic behavior of a PM MC requires computationally expensive 3D finite element analysis (FEA). Herein, a modified version of a recently proposed nonlinear transient path energy method (NT-PEM) is proposed as an analytical alternative to FEA. Within the modification to NT-PEM, a new topology for nonlinear dynamic magnetic equivalent circuit (ND-MEC) is proposed with a methodology for accurate evaluation of stray and leakage flux path parameters. For coil leakage reluctances, a novel path function based on a conchoid's arc is proposed. For stray reluctances, a path function based on the average length of an elliptical arc is proposed. This path function, along with the proposed permeability correction for nonlinear core reluctance calculation routines, led to a four-fold reduction in NT-PEM analysis time from the original version of the proposed method. The feasibility of the proposed NT-PEM is verified via comparison with commercial 3D FEA and experimental data obtained from a PM MC with a single coil and single PM. NT-PEM and FEA equally displayed accurate results, indicating that NT-PEM is a promising computationally efficient alternative to FEA owing to significantly reduced analysis time, which is essential when considering numerous designs and design parameters.

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