arXiv subjects

MohammadSadegh KhajueeZadeh

Publications and source records attributed to MohammadSadegh KhajueeZadeh.

4 recordsLinked to original sources

arXiv2026

Accurate Analytical Modeling of Small-Size Rotary Transformers for Wound-Rotor Resolvers

Rotary transformers are commonly used in wound rotor resolvers to transfer excitation signals to the rotating winding without mechanical contact. In many analyses, the rotary transformer is modeled as an ideal transformer, where the voltage transfer ratio is assumed to be equal to the turns ratio. However, in miniature rotary transformers used in compact resolver systems, leakage inductance can become comparable to the magnetizing inductance due to reduced core dimensions and unavoidable air gaps, leading to deviations from the ideal voltage transfer behavior. This paper presents an accurate equivalent circuit model for miniature rotary transformers employed in wound rotor resolvers. The proposed model analytically derives the magnetizing and leakage inductances using a magnetic equivalent circuit that accounts for flux fringing and air gap effects. The model is validated through three dimensional finite element analysis and experimental measurements on a fabricated prototype under both no load and resolver excitation conditions. The results demonstrate improved prediction accuracy of the secondary voltage compared with conventional models, enabling more reliable characterization of excitation transfer in compact resolver systems.

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arXiv2025

Hybrid Resolver Model Generalization for Fault Condition Modeling: A Promising Tool for Reliability Study

Resolvers, like all electromagnetic devices, are constantly under investigation, both operationally and structurally. In this regard, proposing a modeling methodology that can save significant time without compromising accuracy is a big honor. In this study, a generalized hybrid model is suggested that, in addition to the above benefits, has sufficient capability to ease reliability study in the field of resolvers, where a large number of faulty conditions must be investigated under different operating conditions, including changes in angular velocity, voltage, and frequency of excitation; all of which are highlighted in the context of fault coverage. This model also serves as a promising tool for generating large datasets, which is advantageous for fault diagnosis. A resolver with a non-uniform air gap is chosen as a case study to challenge the suggested model, particularly in relation to eccentricity faults. We generalize the suggested model to account for the most common faulty conditions of resolvers: in-turn short circuits in signal and excitation windings, as well as static and dynamic eccentricity faults. The close agreement between the results of the suggested model and those from Time-Stepping Finite Element Analysis (TS-FEA), along with significant time savings in both healthy and faulty conditions, highlights the generality and proficiency of the suggested model. Finally, the case study is prototyped, and we verify the accuracy of the suggested model experimentally.

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arXiv2025

Model-Agnostic Meta-Learning for Fault Diagnosis of Induction Motors in Data-Scarce Environments with Varying Operating Conditions and Electric Drive Noise

Reliable mechanical fault detection with limited data is crucial for the effective operation of induction machines, particularly given the real-world challenges present in industrial datasets, such as significant imbalances between healthy and faulty samples and the scarcity of data representing faulty conditions. This research introduces an innovative meta-learning approach to address these issues, focusing on mechanical fault detection in induction motors across diverse operating conditions while mitigating the adverse effects of drive noise in scenarios with limited data. The process of identifying faults under varying operating conditions is framed as a few-shot classification challenge and approached through a model-agnostic meta-learning strategy. Specifically, this approach begins with training a meta-learner across multiple interconnected fault-diagnosis tasks conducted under different operating conditions. In this stage, cross-entropy is utilized to optimize parameters and develop a robust representation of the tasks. Subsequently, the parameters of the meta-learner are fine-tuned for new tasks, enabling rapid adaptation using only a small number of samples. This method achieves excellent accuracy in fault detection across various conditions, even when data availability is restricted. The findings indicate that the proposed model outperforms other sophisticated techniques, providing enhanced generalization and quicker adaptation. The accuracy of fault diagnosis reaches a minimum of 99%, underscoring the model's effectiveness for reliable fault identification.

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arXiv2024

A Multiphysics Analysis and Investigation of Soft Magnetics Effect on IPMSM: Case Study Dynamometer

Nowadays, Interior Permanent Magnet Synchronous Motors (IPMSMs) are taken into attention in the industry owing to their advantages. Moreover, in many cases, performing static tests is not enough, and investigating electric machines under dynamic conditions is necessary. Accordingly, by employing a dynamometer system, the dynamic behavior of the electric machine under test is investigated. Among the dynamometers, the best is the Alternating (AC) dynamometer because the basic dynamometers cannot take loads with high complexity. So, in the following study, two IPMSM with V-type and Delta-type rotor configurations are designed and suggested to employ in AC dynamometer. Any non-ideality in the electric machines of AC dynamometers, electrically and mechanically, causes errors in the measurement of the motor under test. Electrically and mechanically, the behavior of a system significantly depends on the used soft magnetics besides its physical and magnetic configuration. Accordingly, by performing a Multiphysics analysis and using the FEM tool to change the soft magnetics in the rotor and stator core, comparing the electric motors' behavior in the AC dynamometer is investigated under the same operating conditions electrically and mechanically. Finally, which soft magnetics is more satisfactory for the AC dynamometer can be seen.

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