Real-Time HIL Emulation for a Segmented-Rotor Switched Reluctance Motor Using a New Magnetic Equivalent Circuit

Sun, Xiaodong; Diao, Kaikai; Lei, Gang; Guo, Yueping; Zhu, Jun

doi:10.1109/tpel.2019.2933664

Cited by 77 publications

(26 citation statements)

References 32 publications

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“…dSPACE has advanced hardware processors, high-speed computing capabilities, and abundant I/O ports capable of completing system configuration, thereby generating and downloading code, debugging functions, and other functions [33], [34]. A dSPACE1104 experimental platform of speed sensorless control system for HEAFFSPMM is built to verify the effectiveness of the control method in the actual system.…”

Section: Experiments Analysismentioning

confidence: 99%

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

et al. 2020

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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 .

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Section: Experiments Analysismentioning

confidence: 99%

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

et al. 2020

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“…The design of the HEMA includes the following aspects: 1) The PM of the HEMA is axially arranged to obtain a gap flux density higher than that obtained in PM arranged in radial direction [21]- [23]. Moreover, this arrangement has a simpler structure and lower manufacturing cost than the Halbach magnetization.…”

Section: Structure Of Hemamentioning

confidence: 99%

“…However, Table only gives the design restrictions. Thus, the relationships among the main structural parameters of HEMA must be determined by the equivalent magnetic circuit method [23]. Figure 6 shows the equivalent magnetic circuit and the direction of the flux density, where R m is the magnetic reluctance of the PM, R p is the magnetic reluctance of the iron pole, R l is the magnetic reluctance of the external conductor tube, R s is the total magnetic reluctance of the internal cylinder of the actuator and hydraulic damper, F C is the magnetic motive force, g is the actual air gap, D m is the width of the PM, D Z is the total width of the field of coil and PM, and d is the thickness of the external conductor tube.…”

Section: Structural Parameter Optimization Of Hemamentioning

confidence: 99%

Optimal Design and Experimental Research on a New Hybrid Electromagnetic Actuator for Vehicles

et al. 2020

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In this study, a new hybrid electromagnetic actuator (HEMA) that integrates a cylindrical permanent magnet linear synchronous motor and a hydraulic damper is proposed and designed to solve the problem of poor reliability of a linear electromagnetic actuator. A modified skyhook control that matches the structure of the HEMA is adopted, and the performance parameters are optimized. Then, the relationships among structural parameters of the HEMA are analyzed using equivalent magnetic circuit method. On the basis of these relationships, multiple alternative groups of structural parameters are obtained. Moreover, finite element models are established in Ansoft Maxwell software. The structural parameters of the HEMA are optimized and determined to produce the peak electromagnetic thrust force that the linear motor requires. Finally, a prototype is developed on the basis of the optimized results for the bench test. Test results show that the linear motor tracks the desired force effectively. In contrast to the passive damper, the body acceleration and suspension working space of HEMA are decreased by 20.6% and 13.3%, respectively. The dynamic tire load is increased by 16%, which is in a reasonable range. And compared with LEMA, the body acceleration is increased by 2.73%, but the suspension working space and dynamic tire load are reduced by 1.1% and 38.1%. All the results above mentioned demonstrate that the HEMA can considerably improve the vehicle dynamic performance. INDEX TERMS Hybrid electromagnetic actuator, modified skyhook control strategy, optimal design, experimental research.

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“…Equation (2) shows that the electromagnetic torque is proportional to the product of d-axis current and q-axis current. The higher the current, the greater the torque.…”

Section: B Current Distribution In Whole Speed Rangementioning

confidence: 99%

Current Distribution Method of Induction Motor for Electric Vehicle in Whole Speed Range Based on Gaussian Process

Xie

Hong

et al. 2019

IEEE Access

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A current distribution method based on Gaussian process is proposed in this paper. This method can improve the accuracy of current distribution of induction motors for electric vehicles in whole speed range, and achieve high-performance output torque. First, a vector control system based on current distribution model is designed based on control requirement analysis of induction motor. Second, the mathematical model of output torque and current is established. And the current distribution law of the optimal electromagnetic torque under various operating conditions is qualitatively analyzed. Third, the experimental platform is built to obtain the discrete data of current distribution in whole speed range and the rotor time constants at different temperatures. Finally, the Gaussian process is introduced to establish the regression model based on current discrete data. The regression model distributes the current reasonably and accurately, which is embedded in the control system. Experimental results verify the effectiveness of the proposed method.

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Real-Time HIL Emulation for a Segmented-Rotor Switched Reluctance Motor Using a New Magnetic Equivalent Circuit

Cited by 77 publications

References 32 publications

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

Optimal Design and Experimental Research on a New Hybrid Electromagnetic Actuator for Vehicles

Current Distribution Method of Induction Motor for Electric Vehicle in Whole Speed Range Based on Gaussian Process

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