Torque Ripple Minimization and Control of a Permanent Magnet Synchronous Motor Using Multiobjective Extremum Seeking

Toloue, Shirin Fartash; Kamali, Seyed Hossein; Moallem, M.

doi:10.1109/tmech.2019.2929390

Cited by 25 publications

(7 citation statements)

References 28 publications

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“…The SVM with a better classification effect of small samples is used to diagnose the fault state of each phase, and the indirect classification method is used to construct a one-tomany SVM classifier, and 4 SVM sub-classifiers are set to correspond to these 4 operating states. The six-phase current EMD energy entropy value and the normalized average current are taken as the fault characteristic value as shown in equation (7). 2 shows the correspondence between 78 fault states and the output labels of the SVM classifier.…”

Section: Diagnose Fault States Based On Svmmentioning

confidence: 99%

“…In recent years, multi-phase PMSM has been widely used in aircraft, electric vehicles, marine motor propulsion systems, and other important industrial fields requiring high reliability by the advantage of its low-voltage components to achieve high power, small torque ripple, and high fault tolerance [1][2][3]. Therefore, the research on optimal control, fault-tolerant control, and fault diagnosis of multi-phase PMSM has become a popular direction in the field of motor control [4][5][6][7][8]. Since the six-phase PMSM can still operate normally after a phase loss, an open-circuit fault will generate more harmonics, and the current distortion will cause the magnetic potential to change, which will cause more severe torque ripple and make the motor unstable.…”

Section: Introductionmentioning

confidence: 99%

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Open-Circuit Fault Diagnosis of Six-Phase Permanent Magnet Synchronous Motor Drive System Based on Empirical Mode Decomposition Energy Entropy

Zhang

et al. 2021

IEEE Access

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This paper proposes a method to diagnose the open-circuit faulty phases and faulty points of the six-phase permanent magnet synchronous motor (PMSM) drive circuit. The current sensor is used to obtain the six-phase current signal, and the least mean square error (LMS) adaptive filtering algorithm is used to filter out the vibration and noise. Empirical Mode Decomposition (EMD) is performed on the filtered current signals, and the EMD energy entropy of each phase current signal is calculated. The change of energy entropy can simplify the double-bridge arm open-circuit fault to the single-bridge arm opencircuit fault, which reduces the number of fault characteristics. After the faulty phase is judged by the change of energy entropy, the fault diagnosis system can diagnose the specific faulty point according to the normalized average value of each phase current signal. Finally, the current data of normal state and fault state are used to train the support vector machine (SVM) and classify the fault state. Each type of fault can be accurately diagnosed by substituting experimental data into the SVM. Experimental results prove that the proposed method can accurately diagnose the open-circuit faults of the six-phase PMSM drive system. INDEX TERMS Six-phase permanent magnet synchronous motor, open-circuit fault, empirical mode decomposition, energy entropy, support vector machine.

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Section: Diagnose Fault States Based On Svmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Open-Circuit Fault Diagnosis of Six-Phase Permanent Magnet Synchronous Motor Drive System Based on Empirical Mode Decomposition Energy Entropy

Zhang

et al. 2021

IEEE Access

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“…Permanent magnet synchronous motors (PMSMs) are widely used for industrial and household applications due to their high power density, torque density, and efficiency [1][2][3][4][5]. Among them, as surface-mounted PMSMs (SPMSMs) generally have a smaller cogging torque, torque ripple, and vibration than interior permanent magnet synchronous motors (IPMSMs) do, they are widely used for robot applications that require precise control or as a motor for home appliances requiring low noise and vibration characteristics [6,7].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Effect of the Magnetization Distribution of Multi-Pole PM on SPMSM Performance Using Equivalent Magnetic Circuit Considering Dead Zone

et al. 2021

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In multi-pole permanent magnets (PMs) such a ring-type PMs, as multi-poles are magnetized in one segment, the ends of each pole are weakly magnetized, which is known as the dead zone. Thus, when analyzing characteristics of the motor with multi-pole PMs, accurate results can be obtained by considering the magnetization distribution. For this reason, this paper proposed an equivalent magnetic circuit (EMC) for external-rotor surface-mounted permanent magnet synchronous motors (SPMSMs) considering the dead zone to analyze the effects of the dead zone on the characteristics of the motor. As the magnetization in the dead zone gradually decreases toward the end of the pole, the magnetization distribution is assumed to have a trapezoidal shape. To describe the magnetization distribution, each pole was divided into several elements, and the equivalent residual magnetic flux density was applied to the elements of the dead zone. Finally, the validity of the proposed EMC was verified by comparing the back electro-motive force and air-gap magnetic flux density obtained by the EMC, finite-element analysis, and test.

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“…However, these results have not considered torque ripple and torque fluctuations in EV applications, which are difficult to obtain. The extremum seeking control (ESC), a model‐free optimisation approach, has been studied for the PMSMs in low‐speed machine control applications for handling torque ripple with implementation on dedicated hardware in [25]. However, this investigation has not studied the ESC control for BLDC motors handling load‐torque disturbances and torque ripple.…”

Section: Introductionmentioning

confidence: 99%

“…− e −(T ON (t)/τ) (25) where T ON denotes the power electronic switch's ON-time and τ = (L/R) is the motor time constant. The speed after the loadtorque fluctuations is…”

mentioning

confidence: 99%

Real‐time extremum seeking controller for brushless DC hub motors in electric vehicles

Ramaraj

Dharmaraj

Srinivasan

et al. 2020

IET Electric Power Applications

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This study presents an extremum seeking‐proportional–integral and derivative (ES‐PID) controller design for brushless direct current motors and its implementation in electric vehicles. The ES‐PID controller aims to simultaneously maintain a speed set‐point and reduce torque ripples in the presence of load‐torque disturbances. The proposed ES‐PID combines the simplicity of a PID controller with an extremum seeking approach, a model‐free optimisation approach, thereby resulting in an optimal controller that can be realised on simple hardware (with limited computing power and memory). In addition, a theoretical analysis of the proposed ES‐PID control scheme in terms of stability and convergence is also presented. Performance evaluation of the proposed ES‐PID controller using both simulations and hardware experiments are presented. The results clearly illustrate the ability of the controller to track speed set‐point and reduce torque ripples in the presence of load‐torque variations.

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Torque Ripple Minimization and Control of a Permanent Magnet Synchronous Motor Using Multiobjective Extremum Seeking

Cited by 25 publications

References 28 publications

Open-Circuit Fault Diagnosis of Six-Phase Permanent Magnet Synchronous Motor Drive System Based on Empirical Mode Decomposition Energy Entropy

Open-Circuit Fault Diagnosis of Six-Phase Permanent Magnet Synchronous Motor Drive System Based on Empirical Mode Decomposition Energy Entropy

Analysis of Effect of the Magnetization Distribution of Multi-Pole PM on SPMSM Performance Using Equivalent Magnetic Circuit Considering Dead Zone

Real‐time extremum seeking controller for brushless DC hub motors in electric vehicles

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