RF-DC differences of coaxial thermal standards

Huang, De-Xiang; Chen, M.-L.; He, None Shui-Zhi

doi:10.1109/19.52507

Cited by 15 publications

(6 citation statements)

References 4 publications

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“…At SIRI, the RF-dc differences of TVC's have been determined by theoretical calculations and experimental analysis [8]. Standard TVC's ranging from 0. was used to make a nonlinear fit employing the leastsquares method.…”

Section: E Shaoxing Industry Research Institute (Siri)mentioning

confidence: 99%

Intercomparison of thermal converters at NIM, NIST, PTB, SIRI, and VSL from 10 to 100 MHz

Kinard¹,

Zhen

Hang³

et al. 1993

IEEE Trans. Instrum. Meas.

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Coaxial thermal voltage converters have been intercompared among NIM, NIST, PTB, SIRI, and VSL in the frequency range from 10 MHz to 100 MHz. The intercomparisons were made from 1988 through 1990. This paper briefly describes the highly varied methods and underlying principles on which RF-dc difference determinations are based in each laboratory, the transport standards used, and the results of the intercomparisons. The results from the participating laboratories are in very good agreement; therefore, we believe that the determinations of RF-dc difference in this frequency range are very well established.

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Section: E Shaoxing Industry Research Institute (Siri)mentioning

confidence: 99%

Intercomparison of thermal converters at NIM, NIST, PTB, SIRI, and VSL from 10 to 100 MHz

Kinard¹,

Zhen

Hang³

et al. 1993

IEEE Trans. Instrum. Meas.

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“…[27] Some grading devices feed the discharge energy back to the power grid, which can have an energy-saving effect; however, the noise is relatively high, which can easily cause harmonic pollution on the power grid side. [28] To avoid the problem that the discharge is not easy to handle and to save grading time significantly, the range of features extracted in this study is the voltage data before the discharge of the grading process, which is the voltage data for the first 25% of the grading process and the complete formation process. Some recent feature extraction methods, such as extracting features from discharge data [24] or high-voltage area data, [26,29] are not applicable in this study.…”

Section: Feature Extractionmentioning

confidence: 99%

Capacity Prediction Method of Lithium‐Ion Battery in Production Process Based on Improved Random Forest

Liu,

Tang,

Wang

et al. 2023

Energy Tech

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Measuring capacity in the grading process is an important step in battery production. The traditional capacity acquisition method requires considerable time and energy consumption; therefore, an accurate capacity estimation is crucial in reducing production costs. Herein, a capacity prediction method for lithium‐ion batteries based on improved random forest (RF) is proposed. This method extracts features from the voltage data of the entire formation process and the first 25% of the grading process, saving 56.7% of the energy consumption and 74.6% of the time in the grading process. The importance of these features is ranked by RF, the best feature subset is selected, and the RF algorithm with parameters optimized by the genetic algorithm is applied to establish a capacity prediction model. The results show that the proposed model can accurately predict the capacity, with root mean square error (RMSE) and mean absolute percentage error (MAPE) values of only 191.89 mAh and 0.13%, respectively. Compared with other regression algorithms, the model shows a lower RMSE and MAPE and a higher capacity prediction accuracy for low‐capacity cells.

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“…In general, for HVTC's without internal shields, the ac-dc difference contribution from the transmission line effect, 8T, can be expressed as [3]…”

Section: Ac-dc Differences Of Hvtc'smentioning

confidence: 99%

AC-DC difference characteristics of high-voltage thermal converters

Huang

Lipe

Kinard

et al. 1995

IEEE Trans. Instrum. Meas.

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RF-DC differences of coaxial thermal standards

Cited by 15 publications

References 4 publications

Intercomparison of thermal converters at NIM, NIST, PTB, SIRI, and VSL from 10 to 100 MHz

Intercomparison of thermal converters at NIM, NIST, PTB, SIRI, and VSL from 10 to 100 MHz

Capacity Prediction Method of Lithium‐Ion Battery in Production Process Based on Improved Random Forest

AC-DC difference characteristics of high-voltage thermal converters

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