Torque Of Permanent Magnet Synchronous Motor Research Articles

Direct torque control for PMSM based on the RBFNN surrogate model of electromagnetic torque and stator flux linkage

Direct Torque Control (DTC) is widely used in motion control of motors. Classical DTC utilizes the Park transformation(dq-model) or observer to estimate the stator fluxlinkage and electromagnetic torque. However, the dq-model and observer lack descriptions of the cogging torque and magnetic saturation in permanent magnet synchronous motors (PMSM). This paper proposes a novel method based on the surrogate model to estimate stator fluxlinkage and torque for PMSM DTC. First, a finite element model (FEM) was established based on the parameters of PMSM. Using the FEM and Latin hypercube sampling (LHS), a surrogate model for estimating the stator fluxlinkage and torque of PMSM was constructed. The stator fluxlinkage and torque surrogate model, active flux observer, and dq current model under different control methods are constructed, respectively. The servo control parameters were tuned using the extended symmetric optimum algorithm, and simulation and experiments were conducted. Finally, electromechanical coupling models with a ball screw feed system were built based on various control and feedback methods. Simulation and experiment results indicate that the surrogate model reduces torque ripple, stator fluxlinkage offset, and feed system tracking error.

Direct torque control of electric vehicle drives using hybrid techniques

Permanent magnet synchronous motors (PMSM) have the capability of delivering a high torque-to-current ratio, better efficiency and low noise. Because of the above-mentioned factors, PMSMs are commonly employed in variable speed drives, especially in electric vehicle (EV) applications. Without the usage of electromechanical devices, the conventional direct torque control (DTC) can control the speed and torque of PMSM. DTC is highly efficient, fast-tracking and provides smooth torque while limiting its ripple during transient periods. There are many benefits to using a DTC-controlled PMSM drive, including quick and reliable torque reaction, high-performance control speed, and enhanced performance. This research examines the use of the DTC approach to enhance the speed and torque behavior of PMSM. The jellyfish search optimizer (JSO) is used to adjust the DTC's responsiveness and tailor the controller's best gains. In order to train the adaptive neuro-fuzzy inference system (ANFIS) controller, JSO data are utilized. The simulation outcomes demonstrate that the proposed JSO-ANFIS controller achieves a minimal torque ripple of 0.26 Nm and preserves the speed with a harmonic error of 1.21% while contrasted to existing methods.

Adaptive Identification of Nonlinear Friction and Load Torque for PMSM Drives via a Parallel-Observer-Based Network With Model Compensation

Acquiring accurate knowledge of nonlinear friction and load torque is of great interest for optimizing the control behavior of permanent-magnet synchronous motor (PMSM) drives. In this work, a friction-and-load adaptive identification scheme based on a parallel-observer-based network with model compensation (POBN-MC) is presented. The developed network possesses a parallel structure consisting of the designed two novel observers, which involve a gain-adaptation super-twisting load torque observer and a variable-learning-rate Adaline inertia observer. A non-empirical friction model is proposed to capture friction, forming the model compensation part that is exploited for correcting the torque input of the network. With a two-step mechanism derived from the POBN-MC, the proposed scheme attains the online adaptive identification of the friction and load torque in a manner that integrates both accuracy and simplicity. In the first step, an explicit mapping relationship between the nonlinear friction torque and the rotor speed is determined with the speed response triggered by the natural deceleration. The second step accomplishes the online observation with regard to friction-and-load information matching the real-time operating conditions. Sufficient theoretical analyses, as well as the validations of numerous simulations and experiments, are presented to support the suggested scheme.

A Low-Complexity Modulated Model Predictive Torque and Flux Control Strategy for PMSM Drives Without Weighting Factor

This article proposes a modulated model predictive torque and flux control (M2PTFC) method with low complexity for a two-level voltage source inverter (2L-VSI)-fed permanent magnet synchronous motor (PMSM). The proposed strategy aims to reduce the computation burden and simplify the control implementation of the conventional M2PTFC scheme by reducing the number of candidate voltage vectors at every control sample to the minimum (i.e., only two candidates) and eliminating the weighting factor of the cost function and its corresponding tuning procedures. For these purposes, the proposed method devotes different control objectives to the duty modulation and the cost function evaluation processes while executing them sequentially. First, aiming at torque ripple reduction, a duty modulation strategy is proposed based on the analysis of torque deviations produced by different voltage vectors, which ensures proper selection of the two candidates and restricts active voltage vectors (AVVs) that cause high deviations. Then, these candidates are evaluated based on a cost function assigned to achieve the stator flux control objective. The effectiveness of the proposed control scheme is verified through comparative assessment with the conventional M2PTFC and two existing simplified methods by means of simulation and experimental results.

An efficient Feed-forward compensation mechanism for NFC-based PMSM system using different observers for Load-torque estimation

Permanent magnet synchronous motor (PMSM) offers high torque and efficiency and is used in most industrial applications. This manuscript uses a feed-forward compensation mechanism to design an efficient neuro-fuzzy logic controller (NFC) based surface-mounted PMSM system. The different load-observers like Discrete Luenberger Observer (DLO), Kalman filter observer (KFO), and discrete Kalman filter observer (DKFO) are used as a feed-forward compensation method to compensate the dq stator current and also estimate performance metrics. The NFC is used as a speed controller, and two PI controllers are used for the current control mechanism. The noise is added at the actual load torque and speed of PMSM and compensated using load observers. In this work, two different design scenarios are considered to analyze the performance metrics like load torque, speed, and position. The work also explores the average error that occurred at load torque, speed, and position during estimation. The NFC-based PMSM system improves the performance and utilizes less error over the PI/FLC-based PMSM using different observers.

Influence of Inverter Open Circuit Fault on Multiple Physical Quantities in the PMSM

The fault of the drive system mainly occurs in the power transistor of the inverter. Compared with the short-circuit fault, open-circuit fault is not easy to perceive and accurately detect, and it will not cause instantaneously devastating damage to the system. In the case of the open-circuit fault, the motor will be in limp operation mode. At present, most of the research results are focused on fault detection methods, and have not analyzed the situation of multiple physical quantities in the limp mode. In this article, the system hybrid logic dynamic model in different combinations of open-circuit faults under vector control mode is established, and the transient characterization of the current is presented. Furthermore, the system-level analysis model of inverter and motor coupling for fault analysis is proposed, and the change rule of electrical parameters, magnetic field, speed, torque, and loss of PMSM under four fault modes is comprehensively studied. Based on the theory of transient temperature field and fluid dynamics, the three-dimensional global temperature analysis model with electromagnetic-temperature bidirectional coupling is established, and the thermal evolution law and limit temperature rise of permanent magnet synchronous motor (PMSM) are revealed. A lot of experiments are done to verify the analysis correctness, combining with the theoretical research results, the fault conditions, and working range of the motor that can maintain the limp operation are given.

PMSM Torque Ripple Minimization Based on Novel Low Carrier Ratio PWM Technique

Harmonic injection is commonly used in permanent magnet synchronous motor torque ripple minimization (TRM) of electric vehicle. Traditional inverter switching frequency limits TRM application at high speed due to harmonic modulation accuracy and inverter loss. To achieve TRM in the whole speed range and reduce inverter loss, a novel online calculated low carrier ratio pulsewidth modulation (LCRPWM) is proposed in this article. The carrier ratio determining regular according to the injected harmonics is established first. The relationship between injected harmonics and LCRPWM switching angle is revealed and a set of nonlinear equations is established. Thus, the problem is transformed from solving nonlinear equations into optimization by establishing a cost function. The analytical solutions of nonlinear equations are obtained, which avoids iterative operation and plunging into local minimum. Therefore, the switch angle solution method is suitable for online calculation. The LCRPWM is verified in simulation compared with the traditional regularly sampled space vector PWM, which achieves better results in voltage harmonic injection and flux tracking at a much lower switching frequency. At last, the LCRPWM is used in a test bench experiment that shows good TRM effects. The influence of sideband harmonics on torque ripple is analyzed.

Dynamic Response and Synchronizing Characteristic for the Dual-Motor Driving System in Non-Inertial System

As one of the typical propulsion systems of the new-energy vehicles (NEVs), the dual-motor driving system (DMDS) is installed and fixed on the bodywork and moves together with the bodywork in space, that is, the DMDS works in non-inertial systems. The previous researches on the DMDS are based on the assumption that the bodywork is stationary. In fact, since the DMDS moves with the bodywork, besides its own excitation forces, it is inevitably affected by the additional inertial terms (AITs) caused by the change in the operating state of the NEVs. In order to investigate the dynamic response and synchronizing characteristic of the DMDS under different motion forms of NEVs, the dynamic model of the DMDS in a non-inertial system is established, considering the permanent magnet synchronous motors (PMSMs), time-varying meshing stiffness and transmission error of gears. Subsequently, the expressions of the AITs are deduced under different non-inertial conditions. The translational motion and circular motion of the vehicle are selected to analyze the dynamic response and synchronizing characteristics of the DMDS in a non-inertial system. The results show that the acceleration has a significant influence on the displacement response of gears, torque and speed of PMSMs, but the torque synchronization and speed synchronization between PMSMs are minimally influenced by both the acceleration and the AITs. Meanwhile, the AITs that affect the displacement response are analyzed and quantified.

Model Predictive Direct Torque Control and Fuzzy Logic Energy Management for Multi Power Source Electric Vehicles.

This paper proposes a novel Fuzzy-MPDTC control applied to a fuel cell battery electric vehicle whose traction is ensured using a permanent magnet synchronous motor (PMSM). On the traction side, model predictive direct torque control (MPDTC) is used to control PMSM torque, and guarantee minimum torque and current ripples while ensuring satisfactory speed tracking. On the sources side, an energy management strategy (EMS) based on fuzzy logic is proposed, it aims to distribute power over energy sources rationally and satisfy the load power demand. To assess these techniques, a driving cycle under different operating modes, namely cruising, acceleration, idling and regenerative braking is proposed. Real-time simulation is developed using the RT LAB platform and the obtained results match those obtained in numerical simulation using MATLAB/Simulink. The results show a good performance of the whole system, where the proposed MPDTC minimized the torque and flux ripples with 54.54% and 77%, respectively, compared to the conventional DTC and reduced the THD of the PMSM current with 53.37%. Furthermore, the proposed EMS based on fuzzy logic shows good performance and keeps the battery SOC within safe limits under the proposed speed profile and international NYCC driving cycle. These aforementioned results confirm the robustness and effectiveness of the proposed control techniques.

Fault-tolerant control via four-leg inverter of a full-electric propulsion system for lightweight fixed-wing UAVs

The work deals with the development and the performance characterization of a novel control strategy for the detection, isolation and accommodation of coil faults in a three-phase Permanent Magnet Synchronous Motor (PMSM), used to drive the propeller of a modern lightweight fixed-wing UAV. The health-monitoring algorithms on motor currents (used to detect the open-circuit fault and to activate the control reconfiguration) are based on a slope method, associated to the evaluation of the current phasor trajectory in the Clarke plane. Actually, when an open-circuit fault occurs in PMSM driven by a standard three-leg converter, the typical circular trajectory of the current phasor in the Clarke plane collapses into a linear track and relevant torque ripples are generated. On the other hand, if the PMSM is driven by a four-leg converter, a control reconfiguration can be applied: the fourth leg of the power bridge is in stand-by when the system operates without faults, but it is enabled to regulate the current flowing at the central point of the Y connection of the 3-phase PMSM. The performances of the fault-tolerant algorithms are assessed via detailed nonlinear simulation of the propulsion system (including propeller loads, electrical faults, mechanical transmission compliance, digital signal processing and sensors errors). The results demonstrate that the health-monitoring algorithms and the fault-tolerant control strategies permit to obtain extremely small detection and isolation latencies, and negligible performance degradation in terms PMSM torque.

Multi-material topology optimization of permanent magnet synchronous motors

This paper presents a multi-material topology optimization for the design of permanent magnet synchronous motors (PMSMs). Specifically, structural shapes of permanent magnet (PM) and iron core in a PMSM rotor are simultaneously designed together with the orientation of PM magnetization. For a co-design of PM and iron core, relative permeability and residual magnetic flux density are interpolated by the three-field density approach based on the Helmholtz filtering and regularized Heaviside step function. Here, the Helmholtz filtering aims to attain smooth border in design results, and the Heaviside function enables us to acquire a clear border (i.e. zero-one design) without intermediate densities. The optimization goal is set as maximizing the average torque of PMSMs. The average torque is calculated by Maxwell stress tensor (MST) method considering a maximum torque per ampere (MTPA) control. To validate the effectiveness of the proposed multi-material topology optimization approach, a PMSM rotor with 4 poles and 12 slots is designed. In addition, design results at various settings of input current amplitude and PM strength are compared and discussed. When the input current is stronger than the PM strength, rotor PM and iron core are designed for utilizing both PM and reluctance torque components like V-shape interior PMSMs. On the other hand, in the case of stronger PM strength, PM is designed near the air-gap, which utilizes only PM torque component like surface PMSMs.

Optimization of cogging torque in permanent magnet motors based on parameter sensitivity and Kriging model

The weakening of cogging torque in permanent-magnet synchronous motors brings about the problem of low efficiency optimization. To solve this problem, an optimization-simulation scheme for the response surface model based on the parameter sensitivity screening is proposed. A surface-mounted motor having 12 poles and 48 slots is used to obtain the law of the influence on cogging torque caused by multiple electromagnetic parameters. Additionally, the Spearman correlation is used to analyze significant factors that affect the cogging torque. The sample is collected by an OSF optimal space filling design. A Kriging model is applied to construct the relationship between the cogging torque and significant factors, and to modify the model accuracy. The multi-island genetic algorithm is used to find an optimal solution to the cogging torque. The results show that the result of the finite element analysis after optimization only has an error of 1.5% compared with the predicted value of the pseudo model, which is 62% lower than the initial value. Therefore, the sharp reduction in cogging torque in the motor verifies the effectiveness of the optimization scheme.

Research on a PMSM control strategy for electric vehicles

This paper proposes a novel state estimation based permanent magnet synchronous motor (PMSM) control method for electric vehicle (EV) driving. Firstly, a state feedback decoupling control with disturbance feed-forward (SFDCDF) is described. As motor angular speed and rotary angle are key information for the proposed control algorithm and park’s transformation, a novel observer based angular speed estimator (OBASE) is proposed for angular speed estimation. Moreover, an extended Kalman filter (EKF) based rotary angle estimator (EBRAE) is used for rotary angle estimation with information of the estimated angular speed. The convergence of angular speed estimation is proven through Lyapunov stability theory. Simulation results also indicate that the proposed algorithms can control PMSM torque, current, and angular speed to accurately follow reference values without severe fluctuation. In addition, in order to provide SFDCDF with load torque information, the OBASE is slightly modified to work as a vehicle load estimator (VLE) so PMSM responds more rapidly and speed fluctuates more slightly when the load suddenly changes. Then a series of hardware in the loop (HIL) simulations are carried out. Results indicate that the proposed control strategy can precisely estimate PMSM’s angular speed and rotor angle. Also, it can improve the driving performance of PMSM used on EVs.

A Low Complexity Two Step Predictive Torque and Flux Control Scheme for PMSM Drive

Nowadays, finite control set model predictive control techniques are widely used for variable speed Permanent Magnet Synchronous Motor (PMSM) drive applications due to its simple, intuitive algorithm and easy inclusion of motor objectives. In conventional predictive torque control (PTC) method, both torque and flux are controlled by a cost function optimization, where it introduces weighting factors. The selection and tuning of weighting factors is difficult since it affects torque and flux performance of PMSM drive. In this article, a two-step PTC for PMSM drive is proposed, where the flux control objective is replaced with the reactive torque component. Therefore, optimal torque and flux controlling of PMSM is achieved with similar units for both control objectives. Hence, it eliminates weighting factor tuning problem and reduces the average torque and flux ripples over a two sample instants. Additionally, the reduced voltage vector strategy is proposed, so that increased computational efficiency is achieved. To validate the proposed methodology, simulations and experimental tests are conducted for three phase PMSM drive. The obtained simulation and experimental results justify an improved torque and flux response with reduced computational burden when compared to existing PTC methods.

Analysis of Instability in Torque Control of Sensorless PMSM Drives in Flux Weakening Region

This article analyzes the effect of angle estimation error on the sensorless torque control of the permanent-magnet synchronous motor (PMSM). The actual torque of PMSM may differ from the torque reference due to the angle error in sensorless control. Furthermore, this torque discrepancy can cause instability to the control system, especially in the flux weakening region. The instability is highly dependent on the gain setting of the controller and observer in the control loop. To mitigate the adverse effect of the angle error, a torque feedforward method considering the transient angle error is proposed. With the proposed torque feedforward method, the gain margin of the control loop can be enhanced without modifying the gain of the control system. The proposed method is verified through the simulation and experimental results.

A harmonic injection method for improving NVH performance of permanent magnet synchronous motor

A harmonic injection method is proposed for reduce permanent magnet synchronous motor torque ripple and noise, which is based on harmonic model of PMSM. The effectiveness of the method is verified by simulation and experiment. It is proved that this method can significantly improve NVH performance of the motor.

Rapid Torque Rising of PMSM by Directly Chasing Rotating Flux Linkage Vector

The principle of permanent magnet synchronous motor (PMSM) torque control could be seen as driving the stator flux linkage vector to chase a rotating reference by the voltage vectors. An increase in the magnitude of the stator flux linkage vector limits the ability of the voltage vector to vary the torque angle and the torque. In most control strategies, simultaneously increasing that magnitude and the torque angle slows down the PMSM torque response. In this article, a new method to quicken the PMSM torque rising is proposed. The key idea is to predict an almost static flux linkage vector as the target and find a shortcut consisting of the voltage vector sequence during torque tracking to catch up with the rotating reference rapidly. Then, the torque rising can be accelerated by first shortening the stator flux linkage vector to quickly rotate it and then lengthening it. A set of comparative experimental results are presented to confirm the validity of this method.

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.

An Improved Model Predictive Current Control for PMSM Drives Based on Current Track Circle

Model predictive current control (MPCC) is a high-performance control strategy for permanent-magnet synchronous motor (PMSM) drives, with the features of quick response and simple computation. However, the conventional MPCC results in high torque and current ripples. This article proposes an improved MPCC scheme for PMSM drives. In the proposed scheme, the back electromotive force is estimated from the previous stator voltage and current, and it is used to predict the stator current for the next period. To further improve the steady state and dynamic performance, the proposed MPCC selects the optimal voltage vector based on a current track circle instead of a cost function. Compared with the calculation of cost function, the prediction of the current track circle is simple and quick. The proposed MPCC is compared with conventional MPCC and a duty-circle based MPCC by simulation and experiment in the aspect of converter output voltage and sensitivity analysis. Results prove the superiority of the proposed MPCC and its effectiveness in reducing the torque and current ripples of PMSM drives.

Multivariable sliding‐mode extremum seeking PI tuning for current control of a PMSM

High-performance current control is critical for obtaining smooth output torque in permanent-magnet synchronous motors (PMSMs). To this end, a new proportional–integral (PI) tuning method based on multivariable sliding-mode extremum seeking is proposed in this study and applied for current control of a PMSM. In the proposed method, a sliding-mode extremum seeking optimiser varies the PI gains by minimising a cost function based on the feedback error term. The resulting PI controller can achieve fast and accurate tracking response, high disturbance rejection, and low sensitivity to PMSM parameter variations. The stability of the proposed control strategy is investigated through a Lyapunov analysis and its performance is evaluated through experimental studies. The results indicate that the proposed controller can offer improved performance in terms of accuracy, parametric variations, and load torque disturbances when compared with a conventional PI and a recently proposed PI controller using the gradient-based extremum seeking tuning method.