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Academic literature on the topic 'PM flux estimation'

Author: Grafiati
Published: 14 March 2023

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Journal articles on the topic "PM flux estimation"

1

Ding, Hongchang, Xiaobin Gong, and Yuchun Gong. "Estimation of Rotor Temperature of Permanent Magnet Synchronous Motor Based on Model Reference Fuzzy Adaptive Control." Mathematical Problems in Engineering 2020 (April 29, 2020): 1–11. http://dx.doi.org/10.1155/2020/4183706.

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For high-speed permanent magnet synchronous motor (PMSM), its efficiency is significantly affected by the performance of permanent magnets (PMs), and the phenomenon of demagnetization will occur with the increase of PM temperature. So, the temperature detection of PMs in rotor is very necessary for the safe operation of PMSM, and direct detection is difficult due to the rotation of rotor. Based on the relationship between permanent magnet flux linkage and its temperature, in this paper, a new temperature estimation method using model reference fuzzy adaptive control (MRFAC) is proposed to estimate PM temperature. In this method, the model reference adaptive system (MRAS) is built to estimate the permanent magnet flux linkage, and the fuzzy control method is introduced into MRAS, which is used to improve the accuracy and applicable speed range of parameters estimated by MRAS. Different permanent magnet flux linkages are estimated in MRFAC based on the variation of stator resistance, which corresponds to different working temperatures measured by thermal resistance, and the PM temperature will be obtained according to the estimated permanent magnet flux linkage. At last, the back electromotive force (BEMF) is measured on the experimental motor, and the flux linkage and PM temperature of the experimental motor are deduced according to the BEMF. Compared with the experimental results, the estimated PM temperature is very close to the actual test value, and the error is less than 5%, which verifies that the proposed method is suitable for the estimation of PM temperature.
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2

Cai, Xiaolei, Qixuan Wang, Yucheng Wang, and Li Zhang. "Research on a Variable-Leakage-Flux Permanent Magnet Motor Control System Based on an Adaptive Tracking Estimator." Energies 16, no. 2 (January 4, 2023): 587. http://dx.doi.org/10.3390/en16020587.

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Due to the characteristics of inductance parameter mismatch and back electromotive force harmonics caused by novel leakage flux branches and other non-ideal factors for the variable-leakage-flux permanent magnet (VLF-PM) motor, its control system suffers from a deteriorated performance of the rotor position estimation. To overcome the problems mentioned above, an adaptive tracking estimator of the rotor position is proposed in this paper for the VLF-PM motor control system. First, the proposed method simplifies the VLF-PM motor mathematical model and reduces the effect of inductance parameter variations according to the active flux concept. Then, robust and gradient descent algorithms are utilized to maintain the robustness of inductance parameter variations and eliminate the specific order harmonics owing to the novel leakage flux branches. Meanwhile, the accuracy and stability are enhanced. Furthermore, the position compensation based on the current adaptive tracking strategy is proposed to compensate the rotor position error caused by other non-ideal factors. Finally, the feasibility of the proposed estimated system is verified.
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Zhao, Wen Li, Guo Yu Qiu, Yu Jiu Xiong, Kyaw Tha Paw U, Pierre Gentine, and Bao Yu Chen. "Uncertainties Caused by Resistances in Evapotranspiration Estimation Using High-Density Eddy Covariance Measurements." Journal of Hydrometeorology 21, no. 6 (June 2020): 1349–65. http://dx.doi.org/10.1175/jhm-d-19-0191.1.

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AbstractQuantifying the uncertainties caused by resistance parameterizations is fundamental for understanding, improving, and developing terrestrial evapotranspiration (ET) models. Using high-density eddy covariance (EC) tower observations in a heterogeneous oasis in northwest China, this study evaluates the impacts of resistances on the estimation of latent heat flux (LE), the energy equivalent of ET, by comparing resistance parameterizations with different complexities under one- and two-source Penman–Monteith (PM) equations. The results showed that the mean absolute percent error (MAPE) for the LE estimates from the one- and two-source PM equations varied from 32% to 53%, and the uncertainties were caused mainly by the resistance parameterizations. Calibrating the parameters required in the resistance estimations could improve the performance of the PM equations; specifically, the MAPEs for the one-source PM equations were approximately 16%, whereas they were 38% for the two-source PM equations, emphasizing that multiple resistances result in increased uncertainties. The following conclusions were reached: 1) the empirical and biophysical parameters required in resistance estimations were responsible for the uncertainty; 2) increasingly complex resistance parameterizations resulted in greater uncertainties in LE estimates; and 3) models without resistance parameterizations exhibited reduced uncertainties in LE estimates.
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He, Jian, and Zhao-Hua Liu. "Estimation of Stator Resistance and Rotor Flux Linkage in SPMSM Using CLPSO with Opposition-Based-Learning Strategy." Journal of Control Science and Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/5781467.

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Electromagnetic parameters are important for controller design and condition monitoring of permanent magnet synchronous machine (PMSM) system. In this paper, an improved comprehensive learning particle swarm optimization (CLPSO) with opposition-based-learning (OBL) strategy is proposed for estimating stator resistance and rotor flux linkage in surface-mounted PMSM; the proposed method is referred to as CLPSO-OBL. In the CLPSO-OBL framework, an opposition-learning strategy is used for best particles reinforcement learning to improve the dynamic performance and global convergence ability of the CLPSO. The proposed parameter optimization not only retains the advantages of diversity in the CLPSO but also has inherited global exploration capability of the OBL. Then, the proposed method is applied to estimate the stator resistance and rotor flux linkage of surface-mounted PMSM. The experimental results show that the CLPSO-OBL has better performance in estimating winding resistance and PM flux compared to the existing peer PSOs. Furthermore, the proposed parameter estimation model and optimization method are simple and with good accuracy, fast convergence, and easy digital implementation.
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Liu, Kan, and Z. Q. Zhu. "Mechanical Parameter Estimation of Permanent-Magnet Synchronous Machines With Aiding From Estimation of Rotor PM Flux Linkage." IEEE Transactions on Industry Applications 51, no. 4 (July 2015): 3115–25. http://dx.doi.org/10.1109/tia.2015.2399615.

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6

Zhuang, Qifeng, Hao Wang, and Yuqi Xu. "Comparison of Remote Sensing based Multi-Source ET Models over Cropland in a Semi-Humid Region of China." Atmosphere 11, no. 4 (March 27, 2020): 325. http://dx.doi.org/10.3390/atmos11040325.

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The estimation of cropland evapotranspiration (ET) is essential for agriculture water management, drought monitoring, and yield forecast. Remote sensing-based multi-source ET models have been widely applied and validated in the semi-arid region of China. However, careful investigation of the models’ performances for different crop types (winter wheat and summer maize) over the semi-humid region is still necessary. This study used remote sensing data (Landsat 8 and ASTER) and compared three mainstream multi-source ET models: (i) the two-source energy balance model, i.e., TSEB; (ii) the Penman-Monteith based four-source model, i.e., 4s-PM; (iii) the Priestley Taylor-Jet Propulsion Laboratory ET algorithm, i.e., PT-JPL. The measurements of the eddy-covariance (EC) flux tower located in Guantao county of North China were used to validate the models. The results showed that the TSEB model performed the best in estimating latent heat flux (LE) of maize, with an RMSE of 75.0 W/m2 and an R2 of 0.9, and the 4s-PM model had the highest accuracy of LE estimation for wheat, with an RMSE of 61.0 W/m2 and an R2 of 0.91. The LE spatial distribution comparison indicated that the PT-JPL model had more capacity to exhibit crop ET heterogeneity. The major environmental factors affecting ET varied with crop types and crop growth stages. Without taking soil moisture into account, the 4s-PM and TSEB models overestimated LE under water deficit in the maturation stage of wheat. The plant moisture stress based on vegetation index in the PT-JPL model underestimated the evaporation in the maturation stage while the cropland was still wet.
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Chen, Jyun-You, Shih-Chin Yang, and Kai-Hsiang Tu. "Comparative Evaluation of a Permanent Magnet Machine Saliency-Based Drive with Sine-Wave and Square-Wave Voltage Injection." Energies 11, no. 9 (August 21, 2018): 2189. http://dx.doi.org/10.3390/en11092189.

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This paper improves a permanent magnet (PM) machine saliency-based drive performance based on the selection of a suitable injection signal. For the saliency-based position estimation, a persistently high-frequency (HF) voltage signal is injected to obtain a measurable spatial saliency feedback signal. The injection signal can be sine-wave or square-wave alternating current (AC) voltage manipulated by the inverter’s pulse width modulation (PWM). Due to the PWM dead-time effect, these HF voltage injection signals might be distorted, leading to secondary harmonics on the saliency signal. In addition, the flux saturation in machine rotors also results in other saliency harmonics. These nonlinear attributes cause position estimation errors on saliency-based drives. In this paper, two different voltage signals are analyzed to find a suited voltage which is less sensitive to these nonlinear attributes. Considering the inverter dead-time, a sine-wave voltage signal reduces its influence on the saliency signal. By contrast, the flux saturation causes the same amount of error on two injection signals. Analytical equations are developed to investigate position errors caused by the dead-time and flux saturation. An interior PM machine with the saliency ratio of 1.41 is tested for the experimental verification.
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Di Gerlando, Antonino, Giovanni Maria Foglia, Matteo Felice Iacchetti, and Roberto Perini. "Parasitic Currents in Structural Paths of YASA Axial Flux PM Machines: Estimation and Tests." IEEE Transactions on Energy Conversion 31, no. 2 (June 2016): 750–58. http://dx.doi.org/10.1109/tec.2016.2524549.

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9

Hille, Sander, Maria Akhmanova, Matouš Glanc, Alexander Johnson, and Jiří Friml. "Relative Contribution of PIN-Containing Secretory Vesicles and Plasma Membrane PINs to the Directed Auxin Transport: Theoretical Estimation." International Journal of Molecular Sciences 19, no. 11 (November 12, 2018): 3566. http://dx.doi.org/10.3390/ijms19113566.

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The intercellular transport of auxin is driven by PIN-formed (PIN) auxin efflux carriers. PINs are localized at the plasma membrane (PM) and on constitutively recycling endomembrane vesicles. Therefore, PINs can mediate auxin transport either by direct translocation across the PM or by pumping auxin into secretory vesicles (SVs), leading to its secretory release upon fusion with the PM. Which of these two mechanisms dominates is a matter of debate. Here, we addressed the issue with a mathematical modeling approach. We demonstrate that the efficiency of secretory transport depends on SV size, half-life of PINs on the PM, pH, exocytosis frequency and PIN density. 3D structured illumination microscopy (SIM) was used to determine PIN density on the PM. Combining this data with published values of the other parameters, we show that the transport activity of PINs in SVs would have to be at least 1000× greater than on the PM in order to produce a comparable macroscopic auxin transport. If both transport mechanisms operated simultaneously and PINs were equally active on SVs and PM, the contribution of secretion to the total auxin flux would be negligible. In conclusion, while secretory vesicle-mediated transport of auxin is an intriguing and theoretically possible model, it is unlikely to be a major mechanism of auxin transport in planta.
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10

Yi, Boyu, Longyun Kang, Kai Jiang, and Yujian Lin. "A Two-stage Kalman Filter for Sensorless Direct Torque Controlled PM Synchronous Motor Drive." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/768736.

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This paper presents an optimal two-stage extended Kalman filter (OTSEKF) for closed-loop flux, torque, and speed estimation of a permanent magnet synchronous motor (PMSM) to achieve sensorless DTC-SVPWM operation of drive system. The novel observer is obtained by using the same transformation as in a linear Kalman observer, which is proposed by C.-S. Hsieh and F.-C. Chen in 1999. The OTSEKF is an effective implementation of the extended Kalman filter (EKF) and provides a recursive optimum state estimation for PMSMs using terminal signals that may be polluted by noise. Compared to a conventional EKF, the OTSEKF reduces the number of arithmetic operations. Simulation and experimental results verify the effectiveness of the proposed OTSEKF observer for DTC of PMSMs.
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Book chapters on the topic "PM flux estimation"

1

Karan, Vijay Kumar, P. R. Thakura, and A. N. Thakur. "Adaptive Compensation Algorithm for Flux Estimation of PM BLDC Motor Drives." In Lecture Notes in Electrical Engineering, 795–801. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8234-4_64.

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Conference papers on the topic "PM flux estimation"

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Liu, Kan, and Z. Q. Zhu. "Mechanical parameter estimation of permanent magnet synchronous machines with aiding from estimation of rotor PM flux linkage." In 2014 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2014. http://dx.doi.org/10.1109/ecce.2014.6954066.

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Uddin, M., and Md Islam Chy. "On-Line Parameter Estimation Based Speed Control of PM AC Motor Drive in Flux Weakening Region." In Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting. IEEE, 2006. http://dx.doi.org/10.1109/ias.2006.256771.

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Zhu, Z. Q., X. Zhu, P. D. Sun, and D. Howe. "Estimation of Winding Resistance and PM Flux-Linkage in Brushless AC Machines by Reduced-Order Extended Kalman Filter." In 2007 IEEE International Conference on Networking, Sensing and Control. IEEE, 2007. http://dx.doi.org/10.1109/icnsc.2007.372872.

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4

Gaona, Daniel, Oliver Wallscheid, and Joachim Bocker. "Fusion of a lumped-parameter thermal network and speed-dependent flux observer for PM temperature estimation in synchronous machines." In 2017 IEEE Southern Power Electronics Conference (SPEC). IEEE, 2017. http://dx.doi.org/10.1109/spec.2017.8333640.

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