Research on Sensorless Control of Permanent Magnet Synchronous Motor Based on Novel Sliding Mode Observer

Yuan, Qingqing; Wu, Haodong; Qian, Jinyue; Zhang, Botao

doi:10.1109/apmrc.2018.8601057

Cited by 6 publications

(2 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yuan et al [11] and Wang et al [12] estimated rotor speed by sliding mode observer, which was simply computed and exhibits fast dynamic response. However, the buffeting problem affecting estimation accuracy could not be overcome.…”

Section: Introductionmentioning

confidence: 99%

Speed Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent-Magnet Machine Based on Model Reference Adaptive System

et al. 2020

View full text Add to dashboard Cite

A novel 6/13-pole hybrid excitation axial field flux-switching permanent magnet machine (HEAFFSPMM) exhibits strong fault tolerance capability, high efficiency, and large torque density. However, merely few research on speed sensorless control in HEAFFSPMM exists. The speed sensorless control methods based on model reference adaptive system (MRAS) are studied and compared for the machine to improve the stability and reliability of the system and consequently improve the application of machine in control system. Based on the field-oriented control strategy, the MRAS observer of speed is designed and built by applying stator currents, stator flux linkages, and simplified stator currents. The three speed sensorless control algorithms of MRAS are compared and analyzed by using MATLAB/Simulink simulation and dSPACE1104 experimental platform. Results show that the speed sensorless control algorithm based on simplified stator currents has good control performance and high control accuracy. INDEX TERMS Hybrid excitation, axial field flux-switching permanent magnet machine, simplified stator current, model reference adaptive system, and speed sensorless control. NOMENCLATURE u d , u q Stator voltage in d-q axis. u f Excitation voltage. i d , i q Stator current in d-q axis. i f Excitation current. L d , L q Stator inductance in d-q axis. L f Excitation inductance. R s Stator resistance. R f Excitation resistance. T e Electromagnetic torque. T eMAX Maximum value of torque. T eMIN Minimum value of torque. δ Torque ripple. ψ m Flux linkage produced by permanent magnets. ψ d , ψ q d, q-axis component of the stator flux. ω e Electric angular velocity. The associate editor coordinating the review of this manuscript and approving it for publication was Xiaodong Sun .

show abstract

Section: Introductionmentioning

confidence: 99%

Speed Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent-Magnet Machine Based on Model Reference Adaptive System

et al. 2020

View full text Add to dashboard Cite

show abstract

“…For PMSMs, the high-performance control requires accurate speed and rotor information, which can usually be obtained by mechanical sensors, e.g., rotary or photoelectric encoders [1]. However, with the considerations of cost, installation and harsh environments, these mechanical sensors are not suitable for all occasions, and it is necessary to design sensorless control [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Low Speed Sensorless Control Based on an Improved Sliding Mode Observation and the Inverter Nonlinearity Compensation for SPMSM

Yuan

Yang

et al. 2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

It is a difficult to accurately estimate the rotor position in a surface permanent magnet synchronous motor (SPMSM), especially for low speed conditions because the back electromotive force (EMF) is almost zero. In this paper, an improved sliding mode observer (SMO) with a continuous sliding mode switching function (which could reduce the chattering effect) is proposed to estimate the real-time rotor position at a low speed. Through the introduction of an intermediate variable H , the back EMF is extended at low speed, which could improve the estimation accuracy for the rotor position. In addition, the chattering phenomenon is reduced by redesigning the sliding switching function. On the other hand, inverter nonlinearity also results in torque ripple and deteriorates the drive performance because of the harmonic components in the three-phase stator current. Here, a generalized sliding discrete Fourier transform (GSDFT) strategy is studied to extract the harmonic components, which can then be compensated with the corresponding compensation voltage calculated from the motor mathematical model. With the proposed strategy, the estimation accuracy can be apparently restricted when the rotor speed is lower than 50 rpm, while the chattering effect is also improved. With the nonlinearity compensation, the total harmonic distortion obviously decreases, which can improve the rotor estimation and the torque performance. In addition, the GSDFT algorithm executes in approximately half the time of the SDFT compensation method. INDEX TERMS Surface permanent magnet synchronous motor (SPMSM), low speed, sliding mode observer (SMO), inverter nonlinearity compensation, generalized sliding discrete fourier transform (GSDFT).

show abstract

Position Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent Magnet Machine Based on Model Reference Adaptive System

Yang

Zhang

Liang

et al. 2019

2019 22nd International Conference on Electrical Machines and Systems (ICEMS)

View full text Add to dashboard Cite

Research on Sensorless Control of Permanent Magnet Synchronous Motor Based on Novel Sliding Mode Observer

Cited by 6 publications

References 1 publication

Speed Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent-Magnet Machine Based on Model Reference Adaptive System

Speed Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent-Magnet Machine Based on Model Reference Adaptive System

Low Speed Sensorless Control Based on an Improved Sliding Mode Observation and the Inverter Nonlinearity Compensation for SPMSM

Position Sensorless Control of Hybrid Excitation Axial Field Flux-Switching Permanent Magnet Machine Based on Model Reference Adaptive System

Contact Info

Product

Resources

About