Analysis and Research on Mechanical Stress and Multiobjective Optimization of Synchronous Reluctance Motor

The mechanical strength of the synchronous reluctance motor(SynRM)has always been a great challenge.This paper presents an analysis method for assessing stress equivalence and magnetic bridge stress interaction,along with a multiobjective optimization approach.Considering the complex flux barrier structure and inevitable stress concentration at the bridge,the finite element model suitable for SynRM is established.Initially,a neural network structure with two inputs,one output,and three layers is established.Continuous functions are constructed to enhance accuracy.Additionally,the equivalent stress can be converted into a contour distribution of a three-dimensional stress graph.The contour line distribution illustrates the matching scheme for magnetic bridge lengths under equivalent stress.Moreover,the paper explores the analysis of magnetic bridge interaction stress.The optimization levels corresponding to the length of each magnetic bridge are defined,and each level is analyzed by the finite element method.The Taguchi method is used to determine the specific gravity of the stress source on each magnetic bridge.Based on this,a multiobjective optimization employing the Multiobjective Particle Swarm Optimization(MOPSO)technique is introduced.By taking the rotor magnetic bridge as the design parameter,ten optimization objectives including air-gap flux density,sinusoidal property,average torque,torque ripple,and mechanical stress are optimized.The relationship between the optimization objectives and the design parameters can be obtained based on the response surface method(RSM)to avoid too many experimental samples.The optimized model is compared with the initial model,and the optimized effect is verified.Finally,the temperature distribution of under rated working conditions is analyzed,providing support for addressing thermal stress as mentioned earlier.

Permanent Magnet Assisted Synchronous Reluctance Motor with Asymmetric Rotor for High Torque Performance

Permanent magnet assisted synchronous reluctance motor(PMA-SynRM)is a kind of high torque density energy conversion device widely used in modern industry.In this paper,based on the basic topology of PMA-SynRM,a novel PMA-SynRM of asymmetric rotor with position-biased magnet is proposed.The asymmetric rotor design with position-biased magnet realizes the concentration of magnetic field lines in the motor air gap to obtain higher electromagnetic torque,and makes both of magnetic and reluctance torque obtain the peak value at the same current phase angle.The asymmetric rotor configuration is theoretically illustrated by space vector diagram,and the feasibility of high torque performance of the motor is verified.Through the finite element simulation,the effect of the side barrier on output torque and the Mises stress under the rotor asymmetrical design are analyzed.Then the motor characteristics including airgap flux density,back EMF,magnetic torque,reluctance torque,torque ripple,losses,and efficiency are calculated for both the basic and proposed PMA-SynRMs.The results show that the proposed PMA-SynRM has higher torque and efficiency than the basic topology.Moreover,the torque ripple of the proposed PMA-SynRM is reduced by the method with harmonic current injection,and the torque characteristics in the whole current cycle are analyzed.Finally,the endurance to avoid PM demagnetization is confirmed based on the PM remanence calculation.

Passive adaptive control of chaos in synchronous reluctance motor

The performance of synchronous reluctance motor （SynRM） degrades due to chaos when its systemic parameters fall into a certain area. To control the undesirable chaos in SynRM, a passive control law is presented in this paper, which transforms the chaotic SynRM into an equivalent passive system. It is proved that the equivalent system can be asymptotically stabilized at the set equilibrium point, namely, chaos in SynRM can be controlled. Moreover, in order to eliminate the influence of undeterministic parameters, an adaptive law is introduced into the designed controller. Computer simulation results show that the proposed controller is very effective and robust against the uncertainties in systemic parameters. The present study may help to maintain the secure operation of industrial servo drive system.

Analysis of Permanent Magnet-assisted Synchronous Reluctance Motor Based on Equivalent Reluctance Network Model

In this paper,the equivalent reluctance network model(ERNM)is used to calculate the magnetic circuit of a permanent magnet-assisted synchronous reluctance motor(PMASynRM)and calculate no-load air-gap magnetic field and electromagnetic torque.Iteration method is used to solve the relative permeability of iron core.A novel reluctance network model based on actual distribution of the magnetic flux inside the motor is established.The magnetomotive force(MMF)generated by armature winding affects the relative permeability of iron core,which is considered in the calculation of ERNM to improve the accuracy when the motor is under load.ERNM can be used to measure air-gap flux density,no-load back electromotive force(EMF),the average value of motor torque,the armature winding voltage under load,and power factor.The method of calculating the motor performance is proposed.The results of calculation are consistent with finite element method(FEM)and the computational complexity is much less than that of the FEM.The results of ERNM has been verified,which will provide a simple method for motor design and analysis.

Torque Calculation of Five-Phase Synchronous Reluctance Motors With Shifted-Asymmetrical-Salient-Poles Under Saturation Condition

In traditional analytical method(AM),the magnetic saturation is always ignored to simplify the calculation process.However,synchronous reluctance motors(SynRMs)often operate around saturation point to achieve higher torque density.Therefore,a new AM is proposed,in which the saturation of stator iron has been considered.The key of the proposed method includes a saturation factor,and an iterative method is adopted to compute the saturation factor in the SynRM by increasing the air-gap length.Especially,the proposed AM can be applied to a SynRM even with shifted-asymmetrical-salient-poles.In the process of AM,the expression of stator magnetomotive force(MMF)is built firstly.Additionally,the air-gap density including slotting effect and salient-poles is calculated.Then,the rotor MMF under saturation of the stator iron is obtained.Therefore,the precision of the instantaneous torque can be improved significantly.Eventually,by the verification of finite elements method(FEM)and experiments,the torque performance of SynRMs with shifted asymmetrical rotor can be predicted accurately by the proposed AM.

Artificial Monitoring of Eccentric Synchronous Reluctance Motors Using Neural Networks

This paper proposes an artificial neural network for monitoring and detecting the eccentric error of synchronous reluctance motors.Firstly,a 15 kWsynchronous reluctance motor is introduced and took as a case study to investigate the effects of eccentric rotor.Then,the equivalent magnetic circuits of the studied motor are analyzed and developed,in cases of dynamic eccentric rotor and static eccentric rotor condition,respectively.After that,the analytical equations of the studied motor are derived,in terms of its air-gap flux density,electromagnetic torque,and electromagnetic force,followed by the electromagnetic finite element analyses.Then,the modal analyses of the stator and the whole motor are performed,respectively,to explore the natural frequency and the modal shape of the motor,by which the further vibrational analysis is possible to be conducted.The vibration level of the housing is furtherly studied to investigate its relationship with the rotor eccentricity,which is validated by the prototype test.Furthermore,an artificial neural network,which has 3 layers,is proposed.By taking the air-gap flux density,the electromagnetic force,and the vibrational level as inputs,and taking the eccentric distance as output,the proposed neural network is trained till the error smaller than 5%.Therefore,this neural network is obtaining the input parameters of the tested motor,based on which it is automatically monitoring and reporting the eccentric error to the upper-level control center.

Rotor Optimization for Synchronous Reluctance Motors

Rotor of Synchronous reluctance motor(SynRM)usually has multiple flux barrier structure for the purpose of higher electromagnetic torque and lower torque ripple.Two different strategies are used in this paper for rotor structure optimization and a compromised strategy for fully squeeze the potential of each related parameters is developed.Performance of resulted rotor structure is evaluated to verify the optimization procedure.

Position Sensorless Torque Estimation of Synchronous Reluctance Motors Based on Extended-Flux Model without Core-Loss Measurement

This paper proposes an extended-flux model with core-loss resistance of SynRMs （synchronous reluctance motors） and precise torque estimation without core-loss measurement and position encoder. The proposed torque estimation is useful for precise MTPA （maximum torque per ampere） control of position sensorless controlled SynRMs, which is achieved with the assistance of active and reactive powers.

Adaptive Gain Tuning Rule for Nonlinear Sliding-mode Speed Control of Encoderless Three-phase Permanent Magnet Assisted Synchronous Motor

In this paper, an adaptive gain tuning rule is designed for the nonlinear sliding mode speed control(NSMSC) in order to enhance the dynamic performance and the robustness of the permanent magnet assisted synchronous reluctance motor(PMa-Syn RM) with considering the parameter uncertainties. A nonlinear sliding surface whose parameters are altering with time is designed at first. The proposed NSMSC can minimize the settling time without any overshoot via utilizing a low damping ratio at starting along with a high damping ratio as the output approaches the target set-point. In addition, it eliminates the problem of the singularity with the upper bound of an uncertain term that is hard to be measured practically as well as ensures a rapid convergence in finite time, through employing a simple adaptation law. Moreover, for enhancing the system efficiency throughout the constant torque region, the control system utilizes the maximum torque per ampere technique. The nonlinear sliding surface stability is assured via employing Lyapunov stability theory. Furthermore, a simple sliding mode estimator is employed for estimating the system uncertainties. The stability analysis and the experimental results indicate the effectiveness along with feasibility of the proposed speed estimation and the NSMSC approach for a 1.1-k W PMa-Syn RM under different speed references, electrical and mechanical parameters disparities, and load disturbance conditions.

Encoderless Five-phase PMa-SynRM Drive System Based on Robust Torque-speed Estimator with Super-twisting Sliding Mode Control

In this paper,a robust torque speed estimator(RTSE)for linear parameter changing(LPC)system is proposed and designed for an encoderless five-phase permanent magnet assisted synchronous reluctance motor(5-phase PMa-SynRM).This estimator is utilized for estimating the rotor speed and the load torque as well as can solve the speed sensor fault problem,as the feedback speed information is obtained directly from the virtual sensor.In addition,this technique is able to enhance the 5-phase PMa-SynRM performance by estimating the load torque for the real time compensation.The stability analysis of the proposed estimator is performed via Schur complement along with Lyapunov analysis.Furthermore,for improving the 5-phase PMa-SynRM performance,five super-twisting sliding mode controllers(ST-SMCs)are employed with providing a robust response without the impacts of high chattering problem.A super-twisting sliding mode speed controller(ST-SMSC)is employed for controlling the PMa-SynRM rotor speed,and four super-twisting sliding mode current controllers(ST-SMCCs)are employed for controlling the 5-phase PMa-SynRM currents.The stability analysis and the experimental results indicate the effectiveness along with feasibility of the proposed RTSE and the ST-SMSC with ST-SMCCs approach for a 750-W 5-phase PMa-SynRM under load disturbance,parameters variations,single open-phase fault,and adjacent two-phase open circuit fault conditions.

High Performance Position Control System Based on SR-PM Motor

A position control system was developed using a synchronous reluctance permanent magnetic （SR-PM） motor with the field oriented control （FOC）. To get satisfactory control performance, a fuzzy adaptive proportion integration （PI） controller was used rather than a conventional PI controller for the position control. The controller tunes the PI parameters online with fuzzy logic, based on the error and the change of the error between the feedback and reference position. The superiority of the fuzzy PI controller compared to conventional controller is illustrated by simulations and experiments which confirm that the fuzzy PI con- troller effectively restrains overshoot of the position response, As a result, the servo system gives satisfactory steady state and dynamic performance.

Performance Comparison of Field-oriented Control,Direct Torque Control,and Model-predictive Control for SynRMs

Simulation studies of three synchronous reluctance motor(SynRM)control strategies are presented:field-oriented control(FOC),direct torque control(DTC),and finite-set model-predictive control(FS-MPC).FOC uses linear controllers and pulse-width modulation to control the fundamental components of the load voltages vectors.In contrast,DTC and FS-MPC are nonlinear strategies wherein the voltage vectors are directly generated in the absence of a modulator.Theoretical operating principles and control structures of these control strategies are presented.Moreover,a comparative analysis of the static and dynamic performance of the control strategies is conducted using Matlab/Simulink to identify their advantages and limitations.It is confirmed that each of the control strategies has merits and that all three of them satisfy the requirements of modern high-performance drives.