Measurements and Analysis of AC Losses in HTS Windings of Electrical Machine for Different Operation Modes

Zanegin, Sergey; Ivanov, Nikolay; Зубко, В.; Kovalev, Konstantin; Shishov, Ivan M.; Shishov, Dmitry; Podguzov, Vladimir

doi:10.3390/app11062741

Cited by 9 publications

(2 citation statements)

References 32 publications

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“…Superconducting propulsion units in hydrogenbased aircraft with specific power density above 20 kW kg −1 are considered for future cryo-electrified aircraft. However, to commercially use these machines in aviation industry, the main challenges are the further reduction of their weight and size to increase the specific power density, manufacturing issues, and AC loss [13][14][15][16].…”

Section: Applications Of Scs and The Challengesmentioning

confidence: 99%

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Yazdani-Asrami

Sadeghi

Song

et al. 2022

Supercond. Sci. Technol.

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More than a century after the discovery of superconductors (SCs), numerous studies have been accomplished to take the advantage of SCs in physics, power engineering, quantum computing, electronics, communications, aviation, health care, and defence-related applications. However, there are still challenges that hinder the full-scale commercialization of SCs, such as the high cost of superconducting wires/tapes, technical issues related to AC losses, the structure of superconducting devices, the complexity and high cost of the cooling systems, the critical temperature, and manufacturing related issues. In the current century, massive advancements have been achieved on artificial intelligence (AI) techniques by offering disruptive solutions to handle engineering problems. Consequently, AI techniques can be implemented to tackle those challenges facing superconductivity and act as a shortcut towards full commercialization of SCs and their applications. AI approaches are capable of providing fast, efficient, and accurate solutions for the technical, manufacturing, and economic problems with a high level of complexity and nonlinearity in the field of superconductivity. In this paper, concept of AI and the widely used algorithms are first given. Then a critical topical review is presented for those conducted studies that used AI methods for improvement, design, condition monitoring, fault detection and location of superconducting apparatuses in large scale power applications, as well as the prediction of critical temperature and the structure of new SCs, and any other related applications. The topical review are presented in three main categories, AI for large-scale superconducting applications, AI for superconducting materials, and AI for physics of superconductors. In addition, the challenges to apply AI techniques to the superconductivity and its applications are given. Eventually, future trends on how to integrate AI techniques with superconductivity towards the commercialization are discussed.

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Section: Applications Of Scs and The Challengesmentioning

confidence: 99%

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Yazdani-Asrami

Sadeghi

Song

et al. 2022

Supercond. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…• In the design optimization and transient analysis of shortcircuits in HTS cables, for power transmission. These are typically characterized by a high number of tapes in parallel and working conditions that include the transition between the hysteretic and resistive models [21][22][23]; • In the supervision and analysis of transient performance of superconducting fault current limiters [24][25][26][27]; • In HTS induction machines where the SC exceeds its critical current during its start-up conditions and reaches its hysteretic state near synchronism [28,29], and; • In the identification of HTS tapes parameters under experimental ac tests [30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Alternative analytical models for HTS tapes considering their AC hysteretic and resistive losses

Fernandes,

Bucho,

Ferreira da Silva

et al. 2024

Supercond. Sci. Technol.

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This work proposes two alternative analytical models to evaluate the ac losses of High-Temperature Superconducting (HTS) tapes during their hysteretic and resistive modes. These models intend to extend the application range of state-of-the-art analytical models for current values higher than the critical one, i.e., for the resistive state, and to correctly predict the ac losses during the transition between the hysteretic and resistive modes. Two analytical models are proposed, one considering an extension of the Norris model for the HTS tape’s resistive mode and the other based on a Sigmoid function to characterize the hysteretic losses and their smooth transition to the resistive mode. Analytical models capable of estimating ac losses of superconducting (SC) tapes are an important tool for the design of complex SC systems, such as SC fault current limiters, SC electrical machines and SC cables. The proposed models are validated experimentally, for a 1st generation BSCCO tape and a 2nd generation ReBCO tape. Finite element simulation is also carried out to verify the accuracy of the proposed models. Results show that the proposed Extended-Norris model presents some deviation at the transition between the hysteretic and resistive modes, while the Sigmoid model presents very accurate results for the whole spectrum of applied current. Also, the parameters of the Sigmoid models are independent of the tape geometry.

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Modelling and experimental research of machine with annular HTS winding using equivalent magnetic permeability

Kovalev

Ivanov

Podguzov

et al. 2021

J. Phys.: Conf. Ser.

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Measurements and Analysis of AC Losses in HTS Windings of Electrical Machine for Different Operation Modes

Cited by 9 publications

References 32 publications

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Alternative analytical models for HTS tapes considering their AC hysteretic and resistive losses

Modelling and experimental research of machine with annular HTS winding using equivalent magnetic permeability

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