Advancements on Real-Time Simulation for High Switching Frequency Power Electronics Applications (Invited Paper)

Osório, Caio Ruviaro Dantas; Miletic, Milos; Zelic, Jovan; Majstorovic, Dusan; Gagrica, Ognjen

doi:10.1109/ee53374.2021.9628306

Cited by 14 publications

(8 citation statements)

References 12 publications

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“…A viable solution to this problems is the use of hardware-inthe-loop (HIL) simulations. HIL allows real-time simulations, significantly accelerating optimization and test driven design processes, while also allowing the generation of automatic reports, for example [133]. Some research has been done regarding the use of HIL for the simulation SRMs [134]- [136], however, note that no effort has been put towards SRGs or the parameter optimization of the machine.…”

Section: B Hardware-in-the-loop Simulationmentioning

confidence: 99%

A Review on Switched Reluctance Generators in Wind Power Applications: Fundamentals, Control and Future Trends

et al. 2022

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With the ever growing environmental concerns, renewable energy sources emerge as a promise of clean and abundant energy, enabling long-term sustainable development. In this context, wind power gained significant interest due to its relative low cost and availability. Switched reluctance generators (SRGs) are suitable candidates for wind energy conversion systems, as they present a simple structure, robustness, a wide range of speed and are capable of operating in harsh environments. The machine, however, poses challenges such as high torque ripple, acoustic noise production and highly nonlinear behavior. Nonetheless, with the use of adequate control strategies, high dynamic performance SRG-based wind energy conversion systems can be achieved. As a result, this article presents a state of the art review of SRGs in wind power applications. First, the fundamentals of the SRG are presented. Next, two categories of firing angle control are reviewed: optimization and closed-loop control. Then, voltage and power control strategies are discussed, being divided in model-independent and model-based approaches. After that, a review on grid-tied SRGbased wind energy conversion systems is carried out. The most common filter topologies as well as the employed control strategies are detailed. Lastly, an outline of the discussed topics is presented and future trends as well as suggestions for future investigation are listed.

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Section: B Hardware-in-the-loop Simulationmentioning

confidence: 99%

A Review on Switched Reluctance Generators in Wind Power Applications: Fundamentals, Control and Future Trends

et al. 2022

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“…In short words, the higher time resolution is, the more accurate and reliable is the HIL model [7]. However, even reaching simulation steps limited to hundreds of nanoseconds cannot guarantee the sufficient precision of the simulation, as highlighted in [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…The main challenge in hardware in the HIL simulation of medium-to highfrequency converters is misdetection of the duty cycle when reading the control signals generated by the controller [8,10]. In HIL simulations, the input sampling frequency, disabling oversampling methods, is the same as the HIL model frequency.…”

Section: Introductionmentioning

confidence: 99%

“…However, they are suitable for high switching frequency models where multiple switching events often happen during one simulation step. For example, a dual active bridge converter is taken as a case study in [8] to demonstrate the validity of the average method proposed by Typhoon HIL company. Integration Oversampling Method (IOM) presented in [17] does not belong to the previous categories.…”

Section: Introductionmentioning

confidence: 99%

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Four-Period Integration Oversampling Method (4PIOM) for Hardware-in-the-Loop power converters with complementary switches

Zamiri

Sanchez

Castro

2023

Preprint

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This paper addresses aliasing oscillations encountered in hardware-in-the-loop (HIL) simulation caused by inaccurate duty cycle detection in high-frequency power electronic applications. Oversampling has been commonly used as a solution to detect switching events more accurately. Traditional oversampling methods use the extra information obtained by oversampling the inputs for further computations to enhance the precision of the simulation. However, these techniques increase the complexity of the model since they take into account several switch states during each simulation step. To mitigate these complexities, the Integration Oversampling Method (IOM) is introduced as a recent alternative with minimum impact on the model complexity. IOM provides a modified switching pattern that effectively prevents aliasing oscillations while maintaining a single switch-state for each simulation step. It can be implemented as an independent block between the controller and the HIL model, so it keeps the HIL model unchanged. This study highlights the limitations detected in applying IOM to the models with complementary switches, including possible undesired short circuits. To overcome these limitations, a novel oversampling method called 4PIOM is presented. 4PIOM further enhances the IOM algorithm by reducing the simulation step and sampling period. The validity of the new method is demonstrated by comparison with previous proposals and also with the same model without any oversampling. Both experimental and MATLAB simulation results prove its superior performance in attenuating the aliasing oscillations and improving the quality of the simulation.

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“…In that case, aliasing occurs when the control signal in the input of the model is read inaccurately provoking undesirable subharmonics in the output. While different approaches from academia and industry (such as reduction of the simulation step [15], parallel oversampling [16], integration oversampling [17], gate drive signal (GDS) oversamling [18,19]) can be applied to solve the problem, an automatic detection of the subharmonics has not previously been proposed. We present an effective CNN application to automatizing tracing of the oscillations in HIL models.…”

Section: Introductionmentioning

confidence: 99%

Convolutional neural network for subharmonics detection in Hardware-In-the-Loop

Yushkova,

Zambreno,

Sanchez

et al. 2023

Preprint

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Hardware-In-the-Loop (HIL) has become a popular technique for testing real-time complex systems.One of its possible applications is power converter modeling in order to test digital controllers.When a switching converter model is used, the output of the controller can be read incorrectly by the model due to the lack of synchronization of their clocks.Therefore, undesirable oscillations (subharmonics) can appear in the output due to the aliasing effects, which prevent the HIL model from its normal functionality.While there are various solutions present in academic and industrial research in order to address this arising problem, there is no automatic algorithm to detect it when a reference model is not available. In this paper, we implement a one-dimensional convolutional neural network which allows detecting the aliasing distortions.The 1D network was chosen due to the kind of the signal to be classified - an inductor current of the converter model, which is in effect a 1D time sequence.The proposed CNN architecture is shallow and consists of 27 layers only.Despite its simplicity, it shows remarkable performance of more than 99% for both validation and testing datasets, and for the post-training characteristics.Moreover, it makes the architecture potentially implementable in embedded systems, like a real-time HIL system, what can be a good objective for future research.

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Advancements on Real-Time Simulation for High Switching Frequency Power Electronics Applications (Invited Paper)

Cited by 14 publications

References 12 publications

A Review on Switched Reluctance Generators in Wind Power Applications: Fundamentals, Control and Future Trends

A Review on Switched Reluctance Generators in Wind Power Applications: Fundamentals, Control and Future Trends

Four-Period Integration Oversampling Method (4PIOM) for Hardware-in-the-Loop power converters with complementary switches

Convolutional neural network for subharmonics detection in Hardware-In-the-Loop

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