Current Sensor Accuracy Enhancement by Harmonic Spectrum Analysis

Mateev, Valentin; Ralchev, Martin; Marinova, Iliana

doi:10.1109/icst46873.2019.9047692

Cited by 5 publications

(6 citation statements)

References 1 publication

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“…The calibration of the battery management system with a digital Finite Impulse Response filter in (Santoni et al, 2021) introduces harmonic distortions and makes it an inefficient choice for nonlinear impedance calibration. Moving window time difference Gaussian process regression method in (Mateev et al, 2019) and Multivariate adaptive regression splines (MARS) models in (Rahmatian et al, 2017) along with Decision tree regression model are somehow suitable for sensors having nonlinear responses. However, this literature's application domain mainly focuses on soft sensors and online measurement applications.…”

Section: It Has Higher Accuracy In Predictionmentioning

confidence: 99%

“…Similarly, two sets of auto-adjustable Successive Approximation Resistors (SARs) based on control logic are implemented to auto-adjust the precision, as discussed in (Fan et al, 2018). Apart from these, the idea of enhancing current sensor accuracy with harmonic component analysis is a significant arena of research in this domain (Mateev et al, 2019). These new domains are supported by Python's time series feature extraction library (Barandas et al, 2020) and feature dimensionality reduction measures, as presented in (Ikizoglu & Heydarov, 2020).…”

Section: Feature Extraction and Data Acquisitionmentioning

confidence: 99%

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Calibration and frequency estimation in sensors for electrical parameter measurement using regression and metaheuristic based models

2022

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Calibration is the backbone of any sensor and measurement philosophy. The conventional calibration techniques for electrical parameter measurement using nonlinear sensors are affected by the repeating analogue signals and lead to errors in measurement. This research paper investigates different regression-based mathematical models to calibrate the Hall sensor for measuring RMS and the fundamental frequency. The novelty of this research work lies in the feature-based input modelling to measure RMS current and frequency with an error of 3.37e-12% and 7.61e-9%, respectively. The conventional Fourier transform method is compared with six different bio-inspired metaheuristic algorithms to estimate the frequency components of the analogue signal received from the measurement setup. Apart from the conventional sine waveforms, this paper investigates sawtooth and square waveforms as the periodic signals for determining the frequency components. The results from the comparison study show that the Whale Optimization Algorithm exhibits 1.25% lesser error whilst predicting the features in measured frequency components. Apart from this, the paper identifies a unique combination of features that effectively measures the instantaneous electrical parameter with RMSE, NRMSE, and R 2 value of 158.8, 0.51, and 0.44, respectively. Experimentally it is found that the decision tree and random forest regression models calibrate the Hall sensor with 93% less error than their linear and polynomial counterparts.

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Section: It Has Higher Accuracy In Predictionmentioning

confidence: 99%

Section: Feature Extraction and Data Acquisitionmentioning

confidence: 99%

Calibration and frequency estimation in sensors for electrical parameter measurement using regression and metaheuristic based models

2022

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“…Substituting Equations (9) and (10) into (22) and (23), the final current prediction equation can be expressed as…”

Section: Then We Can Getmentioning

confidence: 99%

“…Ref. [10] proposed a data processing scheme based on the harmonic spectrum for Hall current sensors, which helps to improve the accuracy of the sensor. Aiming at the problem of the DC voltage deviation of the grid-connected converter, the Ref.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Current Control with Fixed Switching Frequency and Dead-Time Compensation for Single-Phase PWM Rectifier

et al. 2021

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The research object of this paper is single-phase PWM rectifier, the purpose is to reduce the total harmonic distortion (THD) of the grid-side current. A model predictive current control (MPCC) with fixed switching frequency and dead-time compensation is proposed. First, a combination of an effective vector and two zero vectors is used to fix the switching frequency, and a current prediction equation based on the effective vector’s optimal action time is derived. The optimal action time is resolved from the cost function. Furthermore, in order to perfect the established prediction model and suppress the current waveform distortion as a consequence of the dead-time effect, the dead-time’s influence on the switching vector’s action time is analyzed, and the current prediction equation is revised. According to the experimental results, the conclusion is that, firstly, compared with finite-control-set model predictive control, proportional-integral-based instantaneous current control (PI-ICC) scheme and model predictive direct power control (MP-DPC), the proposed MPCC has the lowest current THD. In addition, the proposed MPCC has a shorter execution time than MP-DPC and has fewer adjusted parameters than PI-ICC. In addition, the dead-time compensation scheme successfully suppresses the zero-current clamping effects, and reduce the current THD.

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“…These correction factors are applied to real measurements performed on-board DC locomotives in the framework of the European Project MyRailS [16]. The characterization of a current sensor experiencing chopped waveforms with a high slew rate and a high current variation as in the case of the braking rheostat is a challenging topic [17][18][19][20][21][22]. A methodology for laboratory generation of such waveforms and a reference system to accurately calibrate transducers exposed to such waveforms is described in [23,24], respectively.…”

Section: Introductionmentioning

confidence: 99%

Methodology for the Accurate Measurement of the Power Dissipated by Braking Rheostats

Giordano

Signorino

Gallo

et al. 2020

Sensors

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The energy efficiency of transportation is a crucial point for the rail and metro system today. The optimized recovery of the energy provided by the electrical braking can lead to savings of about 10% to 30%. Such figures can be reached by infrastructure measures which allow the recovery of the breaking energy that is not directly consumed by the rail system and dissipated in rheostat resistors. A methodology for the accurate estimate of such energy is valuable for a reliable evaluation of the cost–benefit ratio associated with the infrastructural investment. The energy can be estimated by measuring a braking current flowing in the rheostats. The varying duty-cycle associated with the high dynamic variation, from zero to thousands of amperes, makes the current measurement very challenging. Moreover, the digitization of such waveforms introduces systematic errors that affect the energy estimation. To overcome these issues, this paper proposes a technique to measure the power and energy dissipated by the rheostat of a DC operated train with high accuracy. By means of an accurate model of the electrical braking circuit (chopper and rheostat) and the frequency characterization of the current transducer, a correction coefficient as a function of the duty-cycle is estimated. The method is then applied to data recorded during a measurement campaign performed on-board a 1.5 kV train of Metro de Madrid during normal operation. Using the proposed technique, the estimation of the dissipated braking energy is improved by 20%.

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Current Sensor Accuracy Enhancement by Harmonic Spectrum Analysis

Cited by 5 publications

References 1 publication

Calibration and frequency estimation in sensors for electrical parameter measurement using regression and metaheuristic based models

Calibration and frequency estimation in sensors for electrical parameter measurement using regression and metaheuristic based models

Model Predictive Current Control with Fixed Switching Frequency and Dead-Time Compensation for Single-Phase PWM Rectifier

Methodology for the Accurate Measurement of the Power Dissipated by Braking Rheostats

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