Full-Load Range In-Situ Efficiency Estimation Method for Induction Motors Using Only A Direct Start-Up

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.

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Design Considerations for PPS Controlled Current-Fed DAB Converter to Achieve Full Load Range ZVS with Low Inductor RMS Current

2020 IEEE Energy Conversion Congress and Exposition (ECCE) ◽

10.1109/ecce44975.2020.9235334 ◽

2020 ◽

Author(s):

Jing Guo ◽

Hua Han ◽

Guo Xu ◽

Zhiqiang Cai ◽

Hui Wang ◽

...

Keyword(s):

Load Range ◽

Full Load ◽

Design Considerations

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Start-up Strategies for Anaerobic Ammonia Oxidation (Anammox) in In-Situ Nitrogen Removal from Polluted Groundwater in Rare Earth Mining Areas

Sustainability ◽

10.3390/su13084591 ◽

2021 ◽

Vol 13 (8) ◽

pp. 4591

Author(s):

Shuanglei Huang ◽

Daishe Wu

Keyword(s):

Rare Earth ◽

Low Temperature ◽

Removal Efficiency ◽

Nitrogen Removal ◽

Ex Situ ◽

High Concentration ◽

Low Concentration ◽

Start Up ◽

Anammox Activity

The tremendous input of ammonium and rare earth element (REE) ions released by the enormous consumption of (NH4)2SO4 in in situ leaching for ion-adsorption RE mining caused serious ground and surface water contamination. Anaerobic ammonium oxidation (anammox) was a sustainable in situ technology that can reduce this nitrogen pollution. In this research, in situ, semi in situ, and ex situ method of inoculation that included low-concentration (0.02 mg·L−1) and high-concentration (0.10 mg·L−1) lanthanum (La)(III) were adopted to explore effective start-up strategies for starting up anammox reactors seeded with activated sludge and anammox sludge. The reactors were refrigerated for 30 days at 4 °C to investigate the effects of La(III) during a period of low-temperature. The results showed that the in situ and semi in situ enrichment strategies with the addition of La(III) at a low-concentration La(III) addition (0.02 mg·L−1) reduced the length of time required to reactivate the sludge until it reached a state of stable anammox activity and high nitrogen removal efficiency by 60–71 days. The addition of La(III) promoted the formation of sludge floc with a compact structure that enabled it to resist the adverse effects of low temperature and so to maintain a high abundance of AnAOB and microbacterial community diversity of sludge during refrigeration period. The addition of La(III) at a high concentration caused the cellular percentage of AnAOB to decrease from 54.60 ± 6.19% to 17.35 ± 6.69% during the enrichment and reduced nitrogen removal efficiency to an unrecoverable level to post-refrigeration.

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Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data

Remote Sensing ◽

10.3390/rs13101865 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1865

Author(s):

Gabriel Calassou ◽

Pierre-Yves Foucher ◽

Jean-François Léon

Keyword(s):

Matched Filter ◽

Estimation Method ◽

Optimal Estimation ◽

Model Parameters ◽

Surface Reflectance ◽

Sequential Method ◽

Modal Radius ◽

Sentinel 2

Stack emissions from the industrial sector are a subject of concern for air quality. However, the characterization of the stack emission plume properties from in situ observations remains a challenging task. This paper focuses on the characterization of the aerosol properties of a steel plant stack plume through the use of hyperspectral (HS) airborne remote sensing imagery. We propose a new method, based on the combination of HS airborne acquisition and surface reflectance imagery derived from the Sentinel-2 Multi-Spectral Instrument (MSI). The proposed method detects the plume footprint and estimates the surface reflectance under the plume, the aerosol optical thickness (AOT), and the modal radius of the plume. Hyperspectral surface reflectances are estimated using the coupled non-negative matrix factorization (CNMF) method combining HS and MSI data. The CNMF reduces the error associated with estimating the surface reflectance below the plume, particularly for heterogeneous classes. The AOT and modal radius are retrieved using an optimal estimation method (OEM), based on the forward model and allowing for uncertainties in the observations and in the model parameters. The a priori state vector is provided by a sequential method using the root mean square error (RMSE) metric, which outperforms the previously used cluster tuned matched filter (CTMF). The OEM degrees of freedom are then analysed, in order to refine the mask plume and to enhance the quality of the retrieval. The retrieved mean radii of aerosol particles in the plume is 0.125 μμm, with an uncertainty of 0.05 μμm. These results are close to the ultra-fine mode (modal radius around 0.1 μμm) observed from in situ measurements within metallurgical plant plumes from previous studies. The retrieved AOT values vary between 0.07 (near the source point) and 0.01, with uncertainties of 0.005 for the darkest surfaces and above 0.010 for the brightest surfaces.

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