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Related Concept Videos

Types Of Transformers01:16

Types Of Transformers

1.1K
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
1.1K
The Ideal Transformer01:26

The Ideal Transformer

909
In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
909
Three-Winding Transformers01:19

Three-Winding Transformers

314
Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
314
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

213
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
213
Transformers in Distribution System01:27

Transformers in Distribution System

162
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
162
Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

807
The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
807

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Generative Adversarial Network for Synthesizing Multivariate Time-Series Data in Electric Vehicle Driving Scenarios.

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Updated: Sep 16, 2025

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U-Net Inspired Transformer Architecture for Multivariate Time Series Synthesis.

Shyr-Long Jeng1

  • 1Department of Mechanical Engineering, Lunghwa University of Science and Technology, Taoyuan City 333326, Taiwan.

Sensors (Basel, Switzerland)
|July 12, 2025
PubMed
Summary

A new Multiscale Dual-Attention U-Net (TS-MSDA U-Net) model enhances long-term time series synthesis. It significantly improves electric vehicle data analysis and reconstructs high-resolution signals for power electronics.

Keywords:
CLLC converterattentionelectric vehiclehalf-bridgetime series synthesis

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Area of Science:

  • Artificial Intelligence
  • Machine Learning
  • Deep Learning

Background:

  • Accurate long-term time series synthesis is crucial for complex system modeling.
  • Existing models often struggle with capturing intricate temporal dependencies in multivariate data.

Purpose of the Study:

  • To introduce and evaluate the TS-MSDA U-Net model for high-fidelity multivariate time series synthesis.
  • To demonstrate the model's effectiveness in electric vehicle analytics and power electronics applications.

Main Methods:

  • Developed a U-Net architecture incorporating multiscale temporal feature extraction and dual-attention mechanisms.
  • Evaluated the model on real-world electric vehicle trip data and prototype resonant CLLC half-bridge converter signals.

Main Results:

  • Achieved mean absolute error below 1% for key electric vehicle parameters, a two-fold improvement over baseline.
  • Successfully reconstructed high-resolution signals from low-speed ADC data, improving resolution by a factor of 36.
  • The multiscale design significantly enhanced performance, while dual-attention offered modest gains.

Conclusions:

  • The TS-MSDA U-Net model demonstrates superior performance in long-term time series synthesis.
  • Transformer-inspired U-Net architectures are effective for high-fidelity modeling in diverse applications like EV analytics and power electronics.