12.6 Capacitor-current-sensor calibration technique and application in a 4-phase buck converter with load-transient optimization

Author(s):  
Szu-Yu Huang ◽  
Kuan-Yu Fang ◽  
Yi-Wei Huang ◽  
Shih-Hsiung Chien ◽  
Tai-Haur Kuo
2018 ◽  
Vol 54 (6) ◽  
pp. 379-381 ◽  
Author(s):  
Yong Zhou ◽  
Yanqi Zheng ◽  
Ka Nang Leung

2020 ◽  
Vol 48 (6) ◽  
pp. 953-964
Author(s):  
Yong Zhou ◽  
Xiaohui Lin ◽  
Jianxin Yang ◽  
Yanqi Zheng ◽  
Ka Nang Leung

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1923
Author(s):  
Shuang Zhao ◽  
Jun Liu ◽  
Yansong Li

At present, most sensor calibration methods are off-line calibration, which not only makes them time-consuming and laborious, but also causes considerable economic losses. Therefore, in this study, an online calibration method of current sensors is proposed to address the abovementioned issues. The principle and framework of online calibration are introduced. One of the calibration indexes is angular difference. In order to accurately verify it, data acquisition must be precisely synchronized. Therefore, a precise synchronous acquisition system based on GPS timing is proposed. The influence of ionosphere on the accuracy of GPS signal is analyzed and a new method for measuring the inherent delay of GPS receiver is proposed. The synchronous acquisition performance of the system is verified by inter-channel synchronization experiment, and the results show that the synchronization of the system is accurate. Lastly, we apply our online calibration method to the current sensor; the experimental results show that the angular difference and ratio difference meet the requirements of the national standard and the accuracy of the online calibration system can be achieved to 0.2 class, demonstrating the effectiveness of the proposed online calibration method.


2001 ◽  
Author(s):  
Li Cao ◽  
Chuck Hautamaki ◽  
Jia Zhou ◽  
Tae Song Kim ◽  
Sue Mantell

Abstract A calibration technique for measuring MEMS strain sensor performance is described. The sensor calibration technique entails developing a repeatable relationship (gage factor) between the change in sensor nominal resistance and the strain measured at the sensor. The calibration technique involves creating a “pseudo” strain sensor consisting of a strain gage mounted on a silicon wafer. Two identical test specimens are evaluated: the pseudo sensor mounted (with adhesive) on an aluminum specimen (or embedded in a specimen), and a MEMS strain sensor mounted on an aluminum specimen (or embedded in a specimen). The dimensions of the silicon wafer for both the pseudo sensor and MEMS sensor are identical. The specimens are loaded by tensile test. For the pseudo sensor specimen, a relationship is established between the strain applied to the specimen (far field strain) and the strain at the sensor (near field strain). Once the relationship between near field and far field strain is known, a relationship between near field strain and change in resistance of the uncalibrated MEMs sensor is established. This relationship between strain at the sensor and change in resistance is the gage factor. Two different MEMS strain sensor designs were fabricated by patterning polysilicon on a 500 micron thick silicon wafer: monofilament and membrane sensors. Gage factors for the MEMS sensors were determined following the calibration procedure. The results also lead to a conclusion that wafer geometry influences the strain transfer to the sensor.


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