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The Method of Optimum Design of Energy Saving Electromagnets for Levitation Magnetic Transport

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International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018 (EMMFT-2018 2018)

Abstract

The article proposes a method of optimal design of electrical devices, based on solving conditionally-correct inverse problems. The method is used to design electromagnets of levitation magnetic transport. Permanent magnets are built into the design of electromagnets to increase energy saving. The effectiveness of the method is due to the use of the hierarchy of mathematical models. In the first, second, and third stages, inverse problems are solved analytically, and in the fourth, numerically. Such an approach makes it possible to determine the initial approximations of the desired parameters with sufficiently high accuracy and to reduce the total time to solve the problem. At the fourth stage, the finite element method is used to solve direct problems of calculating the magnetic field and forces, and the gradient descent method is used to solve optimization problems. Reduction of time for solving the problem is achieved by transformation of constraints into objective functions and sequential minimization of these functions over a limited number of variables. An algorithm for solving the inverse problem is given. The results of the computational experiment showed a high efficiency of the method in the design of levitation electromagnets with permanent magnets. The method can be used in the design and other electrical devices.

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Acknowledgments

The reported study was funded by RFBR according to the research project â„– 18-01-00204.

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Correspondence to Valeriy Grechikhin .

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Balaban, A., Bakhvalov, Y., Grechikhin, V., Yufanova, J. (2020). The Method of Optimum Design of Energy Saving Electromagnets for Levitation Magnetic Transport. In: Murgul, V., Pasetti, M. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018. EMMFT-2018 2018. Advances in Intelligent Systems and Computing, vol 982. Springer, Cham. https://doi.org/10.1007/978-3-030-19756-8_36

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