Metrological Characterization of EMI Receivers

The standard CISPR 16-1-1 defines the measuring receiver using a black-box approach and sets requirements for its accuracy and spectral properties. Traditionally, such test receivers were developed using a superheterodyne architecture. Recently, time-domain electromagnetic emission measurement systems have been built employing direct sampling instruments, mainly oscilloscopes, and relying on specific signal processing to emulate the performance of compliant instruments. In these cases, the short-time Fourier transform is used for spectral estimation, but the corresponding electromagnetic compatibility standards lack details for its correct use with respect to parameters such as windowing function, overlapping factor, and frequency interpolation. Moreover, it is unclear which combination of spectral estimation parameters is best fit for this purpose. Obtaining reliable, consistent and low uncertainty spectral estimates of electromagnetic emissions measured in time-domain needs appropriate configuration and tuning of the signal processing algorithms. This paper investigates the error in the calculated spectrum for various reference signals: multitone, chirp pulses and rectangular pulses. The analysis is carried out for each CISPR band from A to D, that is, between 9 kHz and 1 GHz. After 489.6 × 10 3 iterations, distributed in 1700 different digital implementations of the CISPR 16-1-1 measuring receiver, the simulations outcomes point to certain sets of parameters that showed satisfactory performance overall, being the Nutall, Kaiser, and Parzen windows with more than 75% of overlapping and using interpolation factor higher than 5, generally suitable. Calibration results are used to experimentally verify that a valid set of parameters is adequate to fulfil CISPR 16-1-1 requirements.INDEX TERMS CISPR-16-1-1, electromagnetic compatibility, measuring receiver, short-time Fourier Transform, standards, time-domain measurements.

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Communications and Data Science for the Success of Vehicle-to-Grid Technologies: Current State and Future Trends

Uribe-Pérez,

Gonzalez-Garrido,

Gallarreta

et al. 2024

Electronics

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Vehicle-to-grid (V2G) technology has emerged as a promising solution for enhancing the integration of electric vehicles (EVs) into the electric grid, offering benefits, such as distributed energy resource (DER) integration, grid stability support, and peak demand management, among others, as well as environmental advantages. This study provides a comprehensive review of V2G systems, with a specific focus on the role of the communication, as they have been identified as key enablers, as well as the challenges that V2G must face. It begins by introducing the fundamentals of V2G systems, including their architecture, operation, and a description of the benefits for different sectors. It then delves into the communication technologies and protocols in V2G systems, highlighting the key requirements in achieving reliable and efficient communication between EVs and the different agents involved. A comprehensive review of communication standards is described, as well as the main communication technologies, which are evaluated in terms of their suitability for V2G applications. Furthermore, the study discusses the challenges and environmental implications of V2G technology, emphasizing the importance of addressing strong and reliable communications to maximize its potential benefits. Finally, future research directions and potential solutions for overcoming challenges in V2G systems are outlined, offering useful insights for researchers, policymakers, and administrations as well as related industry stakeholders.

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Metrological Characterization of EMI Receivers

Cited by 3 publications

References 16 publications

Comparison of Measurement Methods for the Assessment of RMS Spectra in the 9-150 kHz Range

Comparison of Measurement Methods for the Assessment of RMS Spectra in the 9-150 kHz Range

Evaluation of Spectral Estimation Parameters for Direct Sampling FFT-Based Measuring Receivers

Communications and Data Science for the Success of Vehicle-to-Grid Technologies: Current State and Future Trends

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