Impact of the motor magnetic model on direct flux vector control of interior PM motors

The stator-field-oriented, direct-flux vector control has been proven to be effective in terms of linear torque control and model independent performance at limited voltage and current (i.e. in flux weakening) for AC drives of various types. The performance of the direct-flux vector control relies on the accuracy of the flux estimation, as for any field oriented control. The knowledge of the motor magnetic model is critical for flux estimation when the operating at low speed. This paper addresses the effects of a limited knowledge of the motor model on the performance of the control at low speed, for an Interior Permanent Magnet motor drive. Experimental results are give

Reducing bias and quantifying uncertainty in watershed flux estimates: the R package loadflex

Many ecological insights into the function of rivers and watersheds emerge from quantifying the flux of solutes or suspended materials in rivers. Numerous methods for flux estimation have been described, and each has its strengths and weaknesses. Currently, the largest practical challenges in flux estimation are to select among these methods and to implement or apply whichever method is chosen. To ease this process of method selection and application, we have written an R software package called loadflex that implements several of the most popular methods for flux estimation, including regressions, interpolations, and the special case of interpolation known as the period-weighted approach. Our package also implements a lesser-known and empirically promising approach called the “composite method,” to which we have added an algorithm for estimating prediction uncertainty. Here we describe the structure and key features of loadflex, with a special emphasis on the rationale and details of our composite method implementation. We then demonstrate the use of loadflex by fitting four different models to nitrate data from the Lamprey River in southeastern New Hampshire, where two large floods in 2006–2007 are hypothesized to have driven a long-term shift in nitrate concentrations and fluxes from the watershed. The models each give believable estimates, and yet they yield different answers for whether and how the floods altered nitrate loads. In general, the best modeling approach for each new dataset will depend on the specific site and solute of interest, and researchers need to make an informed choice among the many possible models. Our package addresses this need by making it simple to apply and compare multiple load estimation models, ultimately allowing researchers to estimate riverine concentrations and fluxes with greater ease and accuracy

Self-Commissioning Algorithm for Inverter Non-Linearity Compensation in Sensorless Induction Motor Drives

In many sensorless field-oriented control schemes for induction motor (IM) drives, flux is estimated by means of measured motor currents and control reference voltages. In most cases, flux estimation is based on the integral of back-electromotive-force (EMF) voltages. Inverter nonlinear errors (dead-time and on-state voltage drops) introduce a distortion in the estimated voltage that reduces the accuracy of the flux estimation, particularly at low speed. In the literature, most of the compensation techniques of such errors require the offline identification of the inverter model and offline postprocessing. This paper presents a simple and accurate method for the identification of inverter parameters at the drive startup. The method is integrated into the control code of the IM drive, and it is based on the information contained in the feedback signal of the flux observer. The procedure applies, more in general, to all those sensorless ac drives where the flux is estimated using the back-EMF integration, not only for IM drives but also for permanent-magnet synchronous motor drives (surface-mounted permanent magnet and interior permanent magnet). A self-commissioning algorithm is presented and tested for the sensorless control of an IM drive, implemented on a fixed-point DSP. The feasibility and effectiveness of the method are demonstrated by experimental result

Isotropic Wavelets: a Powerful Tool to Extract Point Sources from CMB Maps

It is the aim of this paper to introduce the use of isotropic wavelets to detect and determine the flux of point sources appearing in CMB maps. The most suited wavelet to detect point sources filtered with a Gaussian beam is the Mexican Hat. An analytical expression of the wavelet coefficient obtained in the presence of a point source is provided and used in the detection and flux estimation methods presented. For illustration the method is applied to two simulations (assuming Planck Mission characteristics) dominated by CMB (100 GHz) and dust (857 GHz) as these will be the two signals dominating at low and high frequency respectively in the Planck channels. We are able to detect bright sources above 1.58 Jy at 857 GHz (82% of all sources) and above 0.36 Jy at 100 GHz (100% of all) with errors in the flux estimation below 25%. The main advantage of this method is that nothing has to be assumed about the underlying field, i.e. about the nature and properties of the signal plus noise present in the maps. This is not the case in the detection method presented by Tegmark and Oliveira-Costa 1998. Both methods are compared producing similar results.Comment: 6 pages. Accepted for publication in MNRA

Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land‐surface temperature observations

Equations based on surface renewal (SR) analysis to estimate the sensible heat flux (H) require as input the mean ramp amplitude and period observed in the ramp‐like pattern of the air temperature measured at high frequency. A SR‐based method to estimate sensible heat flux (HSR‐LST) requiring only low‐frequency measurements of the air temperature, horizontal mean wind speed, and land‐surface temperature as input was derived and tested under unstable conditions over a heterogeneous canopy (olive grove). HSR‐LST assumes that the mean ramp amplitude can be inferred from the difference between land‐surface temperature and mean air temperature through a linear relationship and that the ramp frequency is related to a wind shear scale characteristic of the canopy flow. The land‐surface temperature was retrieved by integrating in situ sensing measures of thermal infrared energy emitted by the surface. The performance of HSR‐LST was analyzed against flux tower measurements collected at two heights (close to and well above the canopy top). Crucial parameters involved in HSR‐LST, which define the above mentioned linear relationship, were explained using the canopy height and the land surface temperature observed at sunrise and sunset. Although the olive grove can behave as either an isothermal or anisothermal surface, HSR‐LST performed close to H measured using the eddy covariance and the Bowen ratio energy balance methods. Root mean square differences between HSR‐LST and measured H were of about 55 W m−2. Thus, by using multitemporal thermal acquisitions, HSR‐LST appears to bypass inconsistency between land surface temperature and the mean aerodynamic temperature. The one‐source bulk transfer formulation for estimating H performed reliable after calibration against the eddy covariance method. After calibration, the latter performed similar to the proposed SR‐LST method.This research was funded by project CGL2012‐37416‐C04‐01 and CGL2015‐65627‐C3‐1‐R (Ministerio de Ciencia y Innovación of Spain), CEI Iberus, 2014 (Proyecto financiado por el Ministerio de Educación en el marco del Programa Campus de Excelencia Internacional of Spain), and Ayuda para estancias en centros extranjeros (Ministerio de Educación, Cultura y Deporte of Spain)

Frequency-adaptive virtual flux estimation for grid synchronization under unbalanced conditions

This paper proposes a new and explicitly frequencyadaptive method for Virtual Flux estimation and voltage sensorless grid synchronization under unbalanced conditions. The proposed system is based on using Second Order Generalized Integrators, arranged to simultaneously fulfill the purposes of frequency-adaptive band-pass filtering, integration and quadrature signal generation. This results in a simple and efficient structure for combined Virtual Flux estimation and separation into positive and negative sequence components. The properties of the proposed Virtual Flux model is analyzed theoretically, first as an integrator for implementing generic Virtual Flux estimation, and then with respect to sequence separation. The dynamic performance of the proposed estimation method is tested by simulations for the case of an unbalanced voltage drop in the grid and for a step in grid frequency. The simulations verify the performance to be as expected, with similar dynamics as synchronization based on voltage measurements.Peer ReviewedPostprint (published version

On extended Kalman filters with augmented state vectors for the stator flux estimation in SPMSMs

The demand for highly dynamic electrical drives, characterized by high quality torque control, in a wide variety of applications has grown tremendously during the past decades. Direct torque control (DTC) for permanent magnet synchronous motors (PMSM) can provide this accurate and fast torque control. When applying DTC the change of the stator flux linkage vector is controlled, based on torque and flux errors. As such the estimation of the stator flux linkage is essential. In the literature several possible solutions for the estimation of the stator flux linkage are proposed. In order to overcome problems associated with the integration of the back-emf, the use of state observers has been advocated in the literature. Several types of state observers have been conceived and implemented for PMSMs, especially the Extended Kalman Filter (EKF) has received much attention. In most reported applications however the EKF is only used to estimate the speed and rotor position of the PMSM in order to realize field oriented current control in a rotor reference frame. Far fewer publications mention the use of an EKF to estimate the stator flux linkage vector in order to apply DTC. Still the performance of the EKF in the estimation of the stator flux linkage vector has not yet been thoroughly investigated. In this paper the performance of the EKF for stator flux linkage is studied and simulated. The possibilities to improve the estimation by augmenting the state vector and the consequences of these alterations are explored. Important practical aspects for FPGA implementation are discussed

Variance methods to estimate regional heat fluxes with aircraft measurements in the convective boundary layer

Turbulence data obtained by aircraft observations in the convective boundary layer (CBL) were analyzed to estimate the regional surface heat fluxes through application of the variance methods. Several heights within and above the CBL were flown repeatedly above the flux observation site in a homogeneous steppe region in Mongolia. The vertical profiles of the second moment about the mean, i.e., the variance, of temperature were found to follow in general the functional forms proposed in previous studies. These variance statistics were applied to the variance formulations to estimate surface sensible heat fluxes. First, the flux estimation was made with these equations and the constant parameters as proposed in previous studies. Then, the constants were re-calibrated with the current data set and used for flux estimation. In addition, a new simpler formulation was proposed and also calibrated with the current data set. Finally, additional variables, which represent the large scale atmospheric conditions namely baroclinity and advection, were considered for possible improvement of the flux estimation. The resulting rms difference of the estimated sensible heat flux and ground based measurements was reduced from about 40–100 W m−2 for the results obtained with the original constants and formulations, to 30 W m−2 or less for those obtained with locally calibrated constants and introduction of four additional variables. All formulations including the new simple equation performed equally well