Performance Of Permanent Magnet Synchronous Motor Research Articles

Predicting Temperature of Permanent Magnet Synchronous Motor Based on Deep Neural Network

The heat loss and cooling modes of a permanent magnet synchronous motor (PMSM) directly affect the its temperature rise. The accurate evaluation and prediction of stator winding temperature is of great significance to the safety and reliability of PMSMs. In order to study the influencing factors of stator winding temperature and prevent motor insulation ageing, insulation burning, permanent magnet demagnetization and other faults caused by high stator winding temperature, we propose a computer model for PMSM temperature prediction. Ambient temperature, coolant temperature, direct-axis voltage, quadrature-axis voltage, motor speed, torque, direct-axis current, quadrature-axis current, permanent magnet surface temperature, stator yoke temperature, and stator tooth temperature are taken as the input, while the stator winding temperature is taken as the output. A deep neural network (DNN) model for PMSM temperature prediction was constructed. The experimental results showed the prediction error of the model (MAE) was 0.1515, the RMSE was 0.2368, the goodness of fit (R2) was 0.9439 and the goodness of fit between the predicted data and the measured data was high. Through comparative experiments, the prediction accuracy of the DNN model proposed in this paper was determined to be better than other models. This model can effectively predict the temperature change of stator winding, provide technical support to temperature early warning systems and ensure safe operation of PMSMs.

Minimization of ripples in stator current and torque of PMSM drive using advanced predictive current controller based on deadbeat control theory

An advanced predictive current controller (APCC) based on deadbeat (DB) control theory for permanent magnet synchronous motor (PMSM) drives is proposed in this paper, where the optimum voltage vector is computed offline by solving an optimization problem. The optimum voltage vector along with a zero-voltage vector (ZVV) is applied to the motor under steady state condition to minimize ripples in the stator current. To achieve a fast dynamic response during the transient state, the voltage vector having the largest magnitude is applied for the complete duration of the control cycle. The phase of the voltage-vector is synchronized to control the components of the stator-current in a DB manner. In previously reported control methods, the two best voltage vectors (BVVs) are selected through enumeration and two independent duty ratios are calculated. However, this increases the computation complexity and computational time. The proposed APCC employs a novel approach in calculating the stator current references of PMSM using maximum torque per ampere (MTPA) control. The effectiveness of the proposed APCC is investigated and compared with some recently reported predictive current controllers. The APCC improves the performance of PMSM drive under steady and transient operation with lower total harmonics distortion (THD) of the stator current and better torque dynamics.

Grey wolf optimizer algorithm based real time implementation of PIDDTC and FDTC of PMSM

Meta-heuristic optimization techniques are important tools to define the optimal solutions for many problems. In this paper, a new advanced artificial intelligence (AI) based direct torque control (DTC) speed drives are optimally designed and implemented in real time to achieve a high performance permanent-magnet synchronous-motor (PMSM) drive. Grey wolf (GW) algorithms are used with the standard PID-based DTC (PIDDTC) and with the DTC with fuzzy logic (FDTC) based speed controllers. DSPACE DS1202 is utilized in the real-time implementation. MATLAB SIMULINK is used to simulate the steady-state (S.S.) and dynamic responses. The overall system is tested at different operating conditions for both simulation and practical work and all results are presented. A comparison between experimental and simulation results is performed and also a comparison between different applied intelligent techniques is introduced.

Harmonic Torque Suppression Methods for Single-Phase Open-Circuit Fault-Tolerant Operation of PMSM Considering Third Harmonic BEMF

This article proposes a novel type of the 2nd and 4th harmonic torque suppression methods during conventional single-phase open-circuit fault-tolerant operation when considering the 3rd harmonic back-EMF of permanent magnet synchronous motor (PMSM). These suppression methods are based on injecting the 3rd harmonic currents into the two remaining healthy phases, which produces harmonic torque of opposite phase to cancel the original one. The suppression can have three different constraints: maintaining the average torque, eliminating the 2nd harmonic torque, and eliminating the 4th harmonic torque. They cannot be achieved simultaneously. Combining any two of them leads to a particular injection method. Three particular methods are developed and their performance are investigated by theoretical analysis and compared against the conventional one. The proposed fault tolerant control strategies are applicable to various fault-tolerant inverter topologies by using these novel phase current references, whereas the current tracking algorithms could be different. To ease validation, a four-leg inverter topology is selected to implement such injection methods to a three-phase star-connected 10-pole/9-slot PMSM. The experiments validate that tracking the proposed current references can effectively suppress the harmonic torque, which confirms the theoretical analysis.

Calculation and Analysis of the Electromagnetic Field and Temperature Field of the PMSM Based on Fault-Tolerant Control of Four-Leg Inverters

In the three-phase permanent magnet synchronous motor (PMSM) and its control system, the fault of the open or short circuit of the power semiconductor device, loss of the driving signal and the issue of the open circuit for cable connecting the PMSM and the inverter may often occur. This article proposes a fault-tolerant control strategy for the PMSM based on the four-leg inverter, which can maintain the stable operation of PMSM if there is a certain phase fault in the power semiconductor device, driving signal or stator winding. In the healthy mode, the 3D-SVM method is adopted to make four legs put into operation, and the neutral line current is used to compensate for the fault-tolerant operation of the PMSM in case of a certain phase fault. This article treats the PMSM, four-leg inverter and fault-tolerant control strategy as a system for simulation and analysis, which can obtain the variation rules of the internal magnetic field, loss and temperature field of the PMSM before and after fault tolerance. Furthermore, this article focuses on investigating whether the fault-tolerant operating condition will bring the potential negative impact of the PMSM thermal failure. Finally, the correctness of the analysis in this article is verified through experiments.

Design of a Fuzzy Logic-based MPPT Controller for a PV System Employing Sensorless Control of MRAS-based PMSM

The permanent magnet synchronous motors (PMSM) are widely employed in industrial, robotic, water pumping and HVAC applications due to their numerous benefits such as small size, high-energy efficiency, high performance, low inertia and the ability to operate in full load at low speeds. In case the PMSM drive system is supplied from photovoltaic (PV) modules, it can be a perfect match for water pumping or HVAC applications. In such a system, in order to extract full energy from PV modules, a maximum power point tracking (MPPT) algorithm must be employed. This article presents a PV system-fed PMSM drive system with sensorless speed control. The proposed system consists of two main parts. The first part deals with MPPT algorithm based on fuzzy logic controller and the second part deals with PMSM drive system with a sensorless speed estimator by using Model Reference Adaptive System (MRAS) approach to eliminate the use of an encoder. The operation of PMSM is accomplished by using the vector control method to obtain a similar dynamic of the DC motor. The overall system is modelled in Matlab/Simulink environment and simulation results are collected under various operating conditions.

Estimation of Rotor Temperature of Permanent Magnet Synchronous Motor Based on Model Reference Fuzzy Adaptive Control

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.

Novel modelling method based on winding sub‐element of direct‐drive permanent magnet synchronous motor

Owing to its many benefits, including convenient and short computing time, the analytical model (AM) is widely used in the performance analyse of the permanent magnet synchronous motor (PMSM). The existing analytical models based on phase winding cannot sufficiently speculate about the contribution of the coil to the performances of direct-drive PMSM (DDPMSM) with series coils and multiple branches. Hence, in this work, a novel AM for the DDPMSM is proposed. This model, which is based on the winding sub-element, can analyse the influence of coil on motor performance. First, the structure and key parameters of the DDPMSM are reported. Second, an inductance matrix, which considers the spatial disposition of coils and the characteristics of large self-inductance and small mutual inductance, is constructed. Then, the influence of the coil on motor performance is analysed based on the proposed AM. Finally, the results of AM, finite-element model and experiment are compared. The results validate the correctness of the proposed AM. Furthermore, the proposed AM can speculate about the contribution of a coil in the DDPMSM performances with satisfactory accuracy.

Design optimisation of submersible permanent magnet synchronous motor by combined DOE and Taguchi approach

This study presents an optimisation procedure for a submersible permanent magnet synchronous motor (PMSM) to achieve the maximum efficiency and minimum cogging torque simultaneously. Numerous geometric parameters can be used to define submersible PMSM. To identify the most significant parameters for optimisation, the fractional factorial design out of design of experiment (DOE) is employed for the screening activity, considering the interaction effects into account. The manufacturing process of the motor causes dimension tolerances, shape and position tolerances, installation errors and deviations of material properties. To ensure a good robustness for the performance of the submersible PMSM, Taguchi's robust design method is employed. The screened significant parameters are taken as the control factors. The noise factors include inner diameter of stator, the air-gap length, the remanence of the magnets and the dimension tolerances of magnets. Numerical results demonstrate that this method is an effective optimisation design procedure to improve the performance of submersible PMSM, which is finally proved by the prototype test.

Parameters Compensation of Permanent Magnet Synchronous Motor in Flux-Weakening Region for Rail Transit

This article proposes a dual-parameters compensation control method to improve the torque accuracy of permanent magnet synchronous motor (PMSM) in flux-weakening region for rail transit. For the sake of the feature that six-step operation is the essential operation of rail transit and switching frequency is very low, the proposed method works on the single q-axis current regulator-variable voltage angle (SQCR-VVA) flux-weakening control strategy for PMSM operation. Based on SQCR-VVA flux-weakening control, impact of inaccurate parameters is analyzed in seven different conditions, and inaccurate parameters (d-axis inductance, q-axis inductance and permanent magnet flux linkage) result in the errors on d-axis current response and d-axis feed forward voltage. In order to eliminate the impact of the three parameters at the same time, dual compensation regulators are applied to the proposed method. Error of q-axis inductance is identified by the d-axis voltage regulator. The whole impact of inaccurate d-axis inductance and permanent magnet flux linkage is eliminated by the d-axis current regulator. The proposed method is subsequently tested on PMSM and shows quite good performance on the improvement of torque accuracy.

Simulation of PMSM Operating at Different Speeds and Optimization of PI Controller Parameters

This study aims to contribute to design and development studies by investigating current, speed and torque responses of permanent magnet synchronous motor (PMSM) with different loads and powers without any experimental study. For this reason, firstly, PMSM was simulated using Matlab/Simulink package program. The simulation results were then tested using a 0.25 kW PMSM coded MCS06C41, a motor driver coded EVS9322-ESV004, and the Global Drive Control interface program produced by Lenze. In addition, the model was tested on another PMSM (1.1 kW) to determine the validity of the model. Since the driver used during the experiment was designed according to field-oriented vector control, the field-oriented vector control was also preferred in the simulation. The PI controller parameters in driver simulation were optimized by using the Signal Constraint Block in Simulink Response Optimization toolbox of Matlab.

A Modified Model Predictive Current Control of Permanent Magnet Synchronous Motor Drive

Model predictive current control (MPCC) is widely used and more popular control method for a permanent magnet synchronous motor (PMSM) drive. It is less complex and simple to understand as compared with other predictive control methods. MPCC involves the evaluation of a simpler cost function for selecting an optimal voltage vector (VV), which is based on the minimization of error between reference and sensed currents. For a two-level inverter with limited number of VV, MPCC gives poor steady-state performance as a single VV is applied over one sampling interval. In this article, for improving the steady-state performance of PMSM, an improved MPCC is proposed. In this proposed MPCC method, an active VV along with a zero VV is applied similar to the duty cycle control (DCC); however, the timings of active VV and zero VV are selected to decrease the q-axis current ripples. The method introduced in this article is based on the calculation of q-axis current slopes to calculate optimal timing for different VVs. The method introduced in this article is compared with conventional MPCC (C-MPCC) and MPCC with DCC. Simulation and experimentation is carried out for comparison and to confirm the effectiveness of introduced MPCC.

Simplified Predictive Torque Control for Surface-Mounted PMSM Based on Equivalent Transformation and Partition Method

Predictive torque control (PTC) is one of the most widely discussed strategies for high performance permanent magnet synchronous motor (PMSM) drive system because of its fast dynamic response and good stability. However, the complex prediction and optimization process requires a large amount of computation. Until now, few studies have carried out any systematic research on the simplification of the PTC. In this paper, a stepwise simplification method for the PTC strategy is proposed. Firstly, by using the equivalent transformation, the prediction process is simplified without affecting the control performance of the PTC. On this basis, the cost function is further simplified with additional presuppositions, and the optimization process is replaced by honeycomb-structured space partitioning for optimal voltage vector searching. Therefore, the computation burden caused by the multiple calculations in traditional PTC is greatly reduced. In addition, this paper provides the implementation details of the proposed control strategy. Moreover, the comparison between the traditional PTC and two simplified PTC is carried out in the evaluation of the transient performance, steady-state errors, control characteristics, computation burden, and compatibility with additional constraints. The experimental results prove the feasibility and effectiveness of the simplified algorithms, and this is beneficial to the future application of PTC strategy in the low-cost motor drive system. Moreover, the simplified PTC algorithm can achieve higher switching frequency, thereby improving the performance of torque and stator flux in the motor drive system with the application of new generation SiC power device.

Velocity Control for Ripple Reduction in Permanent Magnet Synchronous Motors With Low Performance Current Sensing

In this study, a velocity control method is proposed for minimizing velocity ripples in permanent-magnet synchronous motors with low-performance current sensing. The proposed method involves the use of desired currents, peak estimation, and a proposed tracking controller. The desired currents are used to achieve velocity control with only the current sensing. Peak estimation is performed to estimate the peak of the measured distorted current that occurs due to low-performance sensing. The proposed tracking controller is developed based on a proportional-integral controller using the estimated peak obtained from the measured currents. The proposed method aids in reducing velocity ripples and improving velocity tracking performance of permanent-magnet synchronous motors. The primary contribution of this method is the improvement of velocity-control performance with low-performance current sensing. The stability of the closed loop is proven by employing the input-to-state stable property. To verify the effectiveness of the proposed method, we performed simulations and experiments with different three cases.

Research on Startup Process for Sensorless Control of PMSMs Based on I-F Method Combined With an Adaptive Compensator

Speed control of permanent magnet synchronous motors (PMSMs) without position sensors is preferable in some applications due to cost and mounting space concerns. For applications in which the operating speed is relatively stable, the dynamic performance and efficiency demands of PMSMs are not severe during the startup process. Under such circumstances, a sensorless controller based on back electromotive force (EMF) estimation combined with a simple startup strategy is a suitable solution. In this paper, an I-f (current-frequency) startup method and a sliding mode observer are adopted to develop a sensorless control system, and the startup process which employs the I-f method is analysed in detail. Based on the analysis, this paper proposes a simple and robust startup strategy with an adaptive compensator to realize the smooth transition from I-f control to EMF-based control. The proposed strategy allows quick startup from standstill under different load conditions without initial position estimation. Furthermore, the strategy does not introduce any additional control coefficients, and none of the original control coefficients need to be adjusted. The strategy is suitable for both surface and interior PMSMs, and a test bench based on an interior PMSM is built to validate its properties. The experimental results show that the motor can smoothly accelerate from standstill to its rated speed in less than 2 s in both loaded and non-loaded situations, and the transition between the two sensorless control methods does not cause any large speed or current fluctuations.

Reliable Fuzzy H∞ Control for Permanent Magnet Synchronous Motor Against Stochastic Actuator Faults

This article examines the issue of reliable fuzzy H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control with permanent magnet synchronous motor (PMSM) and stochastic actuator faults. The principle target of modeling the reliable control for PMSM is to improve the performance of PMSM in terms of speed of response, tracking accuracy, and robustness. In contrast to work found in the literature, the proposed dynamic model of a PMSM the load torque variation acts as disturbances, speed control strategy is developed based on the Takagi-Sugeno (T-S) fuzzy model and stochastic actuator faults are considered which is more practical and challenging. In such a manner, first, the nonlinear PMSM model is altered into corresponding linear submodels through the sufficient T-S fuzzy membership rules. Then, based on the obtained dynamic model, reliable H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control is designed for the considered PMSM. By executing an appropriate Lyapunov-Krasovskii (L-K) functional together with linear matrix inequality (LMI) optimization procedure, Wirtinger-based integral inequality approach, and arrangement of the delay-dependent adequate condition is determined which ensures that the closed-loop PMSM is robust asymptotic stable. Based on the acquired condition, the controller gains are derived by solving a set of LMIs. At last, the simulation results are depicted to validate the efficiency of our presented control method.

Optimal Design of PMSM Based on Automated Finite Element Analysis and Metamodeling

To obtain accurate optimal design results in electric machines, the finite element analysis (FEA) technique should be used; however, it is time-consuming. In addition, when the design of experiments (DOE) is conducted in the optimal design process, mechanical design, analysis, and post process must be performed for each design point, which requires a significant amount of design cost and time. This study proposes an automated DOE procedure through linkage between an FEA program and optimal design program to perform DOE easily and accurately. Parametric modeling was developed for the FEA model for automation, the files required for automation were generated using the macro function, and the interface between the FEA and optimal design program was established. Shape optimization was performed on permanent magnet synchronous motors (PMSMs) for small electric vehicles to maximize torque while maintaining efficiency, torque ripple, and total harmonic distortion of the back EMF using the built-in automation program. Fifty FEAs were performed for the experimental points selected by optimal Latin hypercube design and their results were analyzed by screening. Eleven metamodels were created for each output variable using the DOE results and root mean squared error tests were conducted to evaluate the predictive performance of the metamodels. The optimization design based on metamodels was conducted using the hybrid metaheuristic algorithm to determine the global optimum. The optimum design results showed that the average torque was improved by 2.5% in comparison to the initial model, while satisfying all constraints. Finally, the optimal design results were verified by FEA. Consequently, it was found that the proposed optimal design method can be useful for improving the performance of PMSM as well as reducing design cost and time.

Sensorless control of PMSM with fuzzy model reference adaptive system

&lt;p&gt;To improve the performance of permanent-magnet synchronous motor (PMSM) drives powered by the voltage inverter with PWM control, a sensorless control scheme based on a Model Reference Adaptive System (MRAS) a fuzzy logic controller (FLC) based in with fuzzy supervisor structure. The major drawbacks of the conventional MRAS, namely chattering phenomena, high-order harmonics andexternal noise, are discussed. These drawbacks affect the estimated speed accuracy of the MRAS and reduce the control reliability of the system. To eliminate these drawbacks, an FLC is designed and integrated into the MRAS to adjust the observer gain to reduce the chattering in closed loop speed and closed loop current/torque. Comparative simulations using the proposed Fuzzy-MRAS and the conventional MRAS are performed to validate the effectiveness of the proposed FLC structure. Performance simulations of the overall proposed Fuzzy-MRAS based sensorless control scheme are performed to verify the robustness and control reliability of the system. The results show that the proposed Fuzzy MRAS has satisfactory performances with reduction of total harmonic distortion generated in the phase currents.&lt;/p&gt;

An adaptive dynamic programming method for torque ripple minimization of PMSM

<p style='text-indent:20px;'>The imperfect sinusoidal flux distribution, cogging torque, and current measurement errors can cause periodic torque ripple in the permanent magnet synchronous motor (PMSM). These ripples are reflected in the periodic oscillation of the motor speed and torque, causing vibration at low speeds and noise at high speeds. As a high-precision tracking application, ripple degrades the application performance of PMSM. In this paper, an adaptive dynamic programming (ADP) scheme is proposed to reduce the periodic torque ripples. An optimal controller is designed by iterative control algorithm using robust adaptive dynamic programming theory and strategic iterative technique. ADP is combined with the existing Proportional-Integral (PI) current controller and generates compensated reference current iteratively from cycle to cycle so as to minimize the mean square torque error. As a result, an optimization problem is constructed and an optimal controller is obtained. The simulation results show that the robust adaptive dynamic programming achieves lower torque ripple and shorter dynamic adjustment time during steady-state operation, thus meeting the requirements of steady speed state and the dynamic performance of the regulation system.

Study of winding inter turn short circuit effect on permanent magnet synchronous motor performance

Single phase winding’s inter turn short circuit is a common fault in permanent magnet synchronous motor, the short circuit will cause the change of the motor performance to various degrees. In this paper, a 70 kW permanent magnet motor is taken as an example, and ANSYS Maxwell software is used to establish the model of permanent magnet synchronous motor. The inter turn short circuit fault is simulated by reducing the number of turns of the coil. With the help of the software’s powerful electromagnetic field analysis ability and post-processing function, the fault influence on stator winding phase current, electromotive force, torque fluctuation and iron loss, copper loss effect are studied; the current signal is extracted to analyze the relationship between the changes and it is concluded that the amplitude of the third harmonic (150 Hz) of the current increases with the increase of the number of inter-turn short circuit of the A-phase stator. The result can provide the basis for early stage fault diagnosis of the inter turn short circuit.