Parameter Sensitivity and Measurement Error Propagation in Torque Estimation Algorithms for Induction Machines

Author(s):  
C. Bastiaensen
Author(s):  
Mohamed Omar Younsi ◽  
Olivier Ninet ◽  
Fabrice Morganti ◽  
Jean-Philippe Lecointe ◽  
Farid Zidat ◽  
...  

Purpose This paper aims to study the influence of supply voltage variations on the external magnetic field emitted by grid-powered induction machines (IMs). Design/methodology/approach Two models are developed in the paper to analyse, for different supply voltage values, the influence of the variations of the magnetizing voltage for which there is a link with the tangential component of the external flux. The first is an analytical model based on the IM single-phase-equivalent circuit with variable magnetizing reactance to take into account the saturation of the magnetic circuit. The second is a numerical finite element simulation to model the same phenomenon. Results of both models are analysed with experimental measures of the external flux. Findings The study shows that the amplitude of the external field strongly depends on supply voltage values. Research limitations/implications The investigation is mainly focused on the tangential component of the external magnetic field which is of high importance concerning the applicability of non-invasive methods of diagnosis, as electromagnetic torque estimation developed by the authors or internal fault determination. Originality/value The originality of the paper concerns the characterization of the external flux with the supply voltage for IMs. It is shown that the magnetic circuit radiates external flux differently with the load and with the supply voltage.


2020 ◽  
Vol 165 ◽  
pp. 04022
Author(s):  
Zhang Hongfeng

Based on the principle of trigonometric elevation measurement and the law of error propagation, the trigonometric elevation formula is derived in this paper. The factors that cause the trigonometric measurement error are analyzed accurately. It is considered that the use of a high-precision total station for the trigonometric elevation measurement under opposite conditions can reach the second-order level measurement accuracy.


2018 ◽  
Vol 11 (4) ◽  
pp. 1947-1969 ◽  
Author(s):  
Tae-Kwon Wee

Abstract. In the Global Positioning System (GPS) radio occultation (RO) technique, the inverse Abel transform of measured bending angle (Abel inversion, hereafter AI) is the standard means of deriving the refractivity. While concise and straightforward to apply, the AI accumulates and propagates the measurement error downward. The measurement error propagation is detrimental to the refractivity in lower altitudes. In particular, it builds up negative refractivity bias in the tropical lower troposphere. An alternative to AI is the numerical inversion of the forward Abel transform, which does not incur the integration of error-possessing measurement and thus precludes the error propagation. The variational regularization (VR) proposed in this study approximates the inversion of the forward Abel transform by an optimization problem in which the regularized solution describes the measurement as closely as possible within the measurement's considered accuracy. The optimization problem is then solved iteratively by means of the adjoint technique. VR is formulated with error covariance matrices, which permit a rigorous incorporation of prior information on measurement error characteristics and the solution's desired behavior into the regularization. VR holds the control variable in the measurement space to take advantage of the posterior height determination and to negate the measurement error due to the mismodeling of the refractional radius. The advantages of having the solution and the measurement in the same space are elaborated using a purposely corrupted synthetic sounding with a known true solution. The competency of VR relative to AI is validated with a large number of actual RO soundings. The comparison to nearby radiosonde observations shows that VR attains considerably smaller random and systematic errors compared to AI. A noteworthy finding is that in the heights and areas that the measurement bias is supposedly small, VR follows AI very closely in the mean refractivity deserting the first guess. In the lowest few kilometers that AI produces large negative refractivity bias, VR reduces the refractivity bias substantially with the aid of the background, which in this study is the operational forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF). It is concluded based on the results presented in this study that VR offers a definite advantage over AI in the quality of refractivity.


Author(s):  
Seungbum Park ◽  
Myoungho Sunwoo

Indicated torque estimation and load torque observation algorithms are presented and appear to be a feasible alternative to the use of the engine torque maps in a modern torque-based engine management system. The proposed method, which uses a cylinder pressure sensor, has advantages of simplicity from the elimination of the requirement for a complex indicated torque model. Moreover, the proposed algorithms are accurate and robust to the variations in the environmental factors that affect the torque production procedure. The indicated torque is estimated from the peak pressure and its location, and the load torque is observed on the basis of the estimated indicated torque. The proposed torque estimation algorithms may provide new ideas for many application areas such as engine diagnostics, torque-based engine control, traction control via engine control, and vehicle dynamics control.


Author(s):  
Ibrahim Mohd Alsofyani ◽  
Tole Sutikno ◽  
Yahya A. Alamri ◽  
Nik Rumzi Nik Idris ◽  
Norjulia Mohamad Nordin ◽  
...  

<span lang="EN-US">In this paper, two kinds of observers are proposed to investigate torque estimation. The first one is based on a voltage model represented with a low-pass filter (LPF); which is normally used as a replacement for a pure integrator to avoid integration drift problem due to dc offset or measurement error. The second estimator used is an extended Kalman filter (EKF) as a current model, which puts into account all noise problems. Both estimation algorithms are investigated during the steady and transient states, tested under light load, and then compared with the measured mechanical torque. In all conditions, the torque estimation error for EKF has remained within a narrow error band and yielded minimum torque ripples, which motivate the use of the EKF estimation algorithm in high performance control drives of IMs for achieving high dynamic performance. </span>


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