An Efficiency Estimation Method for Inverter Fed Induction Motors

Author(s):  
Johnny W. Rengifo ◽  
Jose M. Aller
2013 ◽  
Vol 446-447 ◽  
pp. 698-703
Author(s):  
Hong Xia Yu ◽  
Chuang Li

In this paper, a new nonintrusive efficiency estimation method without using stray loss approximation value was presented, the efficiency of induction motor was computed using estimated value of speed and load torque by AEKF. In AEKF, the speed and load torque as the state of system are estimated, the noise covariance matrices are estimated adaptively while the state of induction motor system are estimated to overcome the defect that estimation results are affected by the selected noise covariance matrices in EKF, then the estimated speed and the load torque are used to achieve noninvasive efficiency estimation. Experimental results demonstrate that the efficiency estimation results of this method has higher accuracy and are not affected by initial value of noises covariance matrices.


2021 ◽  
Vol 26 (3-4) ◽  
pp. 291-301
Author(s):  
N.V. Stepanov ◽  

Operating quality of automated video control systems depends on optical specifications of video camera and peculiar features of video algorithm. Specified target function performance probability can serve as criterion of automated video control use efficiency. In this work, a new performance efficiency estimation method for automated equipment of target environment video control is suggested: to estimate the probability of target functions’ (object detection, capture, and auto tracking) performance. Theoretical prediction of target functions performance probability was built upon Johnson’s criterion and the use of optimal receiver model. The results of suggested method’s experimental verification have shown that target detection occurred when signal/noise ratio level was above 6. This level can be regarded as low value to ensure that object is detected with probability 0.9.


2018 ◽  
Vol 164 ◽  
pp. 650-660 ◽  
Author(s):  
Peng Liu ◽  
Yumin Su ◽  
Fushun Liu ◽  
Yebao Liu ◽  
Jianhua Zhang ◽  
...  

2020 ◽  
Vol 35 (8) ◽  
pp. 8429-8442 ◽  
Author(s):  
Chao Du ◽  
Zhonggang Yin ◽  
Jing Liu ◽  
Yanqing Zhang ◽  
Xiangdong Sun

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