Model Of Permanent Magnet Synchronous Machine Research Articles

Enhanced Remora Optimization with Deep Learning Model for Intelligent PMSM Drives Temperature Prediction in Electric Vehicles

One of the widespread electric motors for electric vehicles (EVs) is permanent magnet synchronous machine (PMSM) drives. It is because of the power density and high energy of the PMSM with moderate assembly cost. The widely adopted PMSM as the motor of choice for EVs, together with variety of applications urges stringent monitoring of temperature to ignore high temperatures. Temperature monitoring of the PMSM is highly complex to accomplish because of complex measurement device for internal components of the PMSM. Temperature values beyond a certain range might result in additional maintenance costs together with major operational problems in PMSM. The latest developments in artificial intelligence (AI) and deep learning (DL) methods pave a way for accurate temperature prediction in PMSM drivers. With this motivation, this article introduces an enhanced remora optimization algorithm with stacked bidirectional long short-term memory (EROA-SBiLSTM) approach for temperature prediction of the PMSM drives. The presented EROA-SBiLSTM technique mainly focuses on effectual temperature prediction using DL and hyperparameter tuning schemes. To accomplish this, the EROA-SBiLSTM technique applies Pearson correlation coefficient analysis for observing the correlation among various features, and the p-value is utilized for determining the relevant level. Next, the SBiLSTM model is used to predict the level of temperature that exists in the PMSM drivers. Finally, the EROA based hyperparameter tuning process is carried out to adjust the SBiLSTM parameters optimally. The experimental outcome of the EROA-SBiLSTM technique is tested using electric motor temperature dataset from the Kaggle dataset. The comprehensive study specifies the betterment of the EROA-SBiLSTM technique.

Arbitrary Current Harmonic Decomposition and Regulation for Permanent Magnet Synchronous Machines

This paper contributes a novel solution for the regulation of arbitrary current harmonics in a permanent magnet synchronous machine (PMSM) system by introducing a virtual three-phase system. The inverter nonlinearity, back-EMF harmonics, and the asymmetry among phases, are considered to derive a comprehensive electrical model of PMSMs. Compared to the conventional harmonic analysis, the derived model indicates that more new current harmonics can exist in the PMSM system. To regulate the current harmonics with arbitrary orders, a virtual three-phase system is established. By properly shifting the spatial and time phase angles between the virtual three-phase system and the original physical three-phase system, the selected current harmonics can be decomposed from the phase current. A simple proportional-integral regulator with adjustable phase compensation angle is designed based on the proposed model to regulate the decomposed current harmonics in the corresponding harmonic synchronous reference frame. The implementation details and experimental results are provided to illustrate the feasibility and correctness of the proposed control strategy.

Efficient Nonlinear Multi-Parameter Decoupled Estimation of PMSM Drives Based on Multi-State Voltage and Torque Measurements

Accurate and fast parameter estimation is essential for efficient operation and control of permanent magnet synchronous machine (PMSM). In this paper, a novel multi-parameter decoupling estimation method based on multi-state measurement is proposed to analyze and estimate the important parameters including winding resistance, permanent magnetic flux linkage, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d-q$</tex-math></inline-formula> axis inductances. An improved PMSM model containing inverter distorted voltage and nonlinear inductance considering magnetic saturation is established at first, then the model is decoupled to reduce the cross influences among the parameters and improve the computation efficiency through model dimension reduction according to the proposed decoupling method, and finally each parameter is estimated from multi-state voltage and torque measurement with improved efficiency and accuracy. This decoupling method separates the resistance and the inductance based on electromagnetic torque and reluctance torque, which is the crucial part of the estimation method proposed in this paper. Experiment on a PMSM driving system and comparison with existing methods are conducted to show that the proposed estimation method can improve the accuracy of estimation and calculation efficiency.

Fault tolerant control of a permanent magnet synchronous machine using multiple constraints Takagi-Sugeno approach

Introduction. Fault diagnosis, and fault tolerant control issues are becoming very important to ensure a good supervision of systems and guarantee the safety of human operators and equipments even if system complexity increases. Problem. In fact, the presence of faults in actuators, sensors and processes can lead to system performance degradation, system breakdown, economic loss, and even disastrous situations. Furthermore, Actuator saturation or control input saturation is probably the most usual nonlinearity encountered in control engineering because of the physical impossibility of applying unlimited control signals and/or safety constraints. Purpose. This article is dedicated to the problem of fault tolerant control for constrained nonlinear systems described by a Takagi-Sugeno model. One of the interests of this type of models is the possibility of extend some tools and methods from linear system case to the nonlinear one. The novelty of the work consists in developing a fault tolerant control algorithm for a nonlinear Permanent Magnet Synchronous Machine model using an observer based state-feedback control technique in order to enhance fault and state estimation despite actuator saturation and system disturbances. Methods. Indeed a sensor fault detection observer based residual generator is synthesized with a guaranteed L2 performance to attenuate the external disturbances effect from one side and to maximize the residual sensitivity to faults from the other side. Based on Lyapunov function, design conditions are formulated in terms of Linear Matrix Inequalities to ensure stability of the global system. Practical value. A detailed study concerning nonlinear permanent magnet synchronous machine model, which is consolidated by simulation results, is conducted to show the used algorithm’s effectiveness guarantying fault estimation and reconfiguration of the control law to maintain stable performance even in the presence of actuator faults, external perturbation and the phenomenon of actuator saturation.

Mitigation of high-resistance connection in surface-mounted PMSM drive system based on model predictive current control

High-resistance connection fault can result in the increasing of power loss and the rise of heat, so the electric machine drive system possibly can be damaged. Therefore, to reduce the copper loss caused by high-resistance connection in surface mounted permanent magnet synchronous machine drive system, a method to minimize the copper loss based on the model predictive current control is shown in this paper. First, the permanent magnet synchronous machine model is deduced under high-resistance connection fault condition. Then, the direct axis current is deduced to minimize the copper loss. Next, the predictive model of permanent magnet synchronous machine is deduced under fault condition, and the cost function is defined to select the optimal voltage vector. Finally, the proposed model predictive current control strategy is realized to minimize the copper loss. And the effectiveness of this method is verified through the simulation and experiment. According to the results of the simulation and experiment, the proposed model predictive current control method has the same performance as the traditional model predictive current control method, as well as can reduce the copper loss effectively.

Design, modelling and analysis of a hybrid-magnet variable-flux PMSM with variable series-parallel magnetic circuit

Variable-flux permanent magnet synchronous machines (PMSMs) which use low-coercive-force permanent magnets have gained a lot of attention as a perspective alternative in the variable-speed driving application for their advantages of operating with improved efficiency in higher speed through adjusting the variable-flux PMSMs’ magnetization states. A hybrid-magnet variable-flux machine which has the variable series-parallel magnetic circuit is investigated. Magnetization state and magnetic circuit type of this variable-flux PMSM are adjustable. This machine’s equivalent magnetic circuit (EMC) model at different magnetization states is established and evaluated. This model can precisely represent the complicated and changeable magnetic circuit in variable-flux PMSMs and provide an effective way for the operating principle and performance analysis. The electromagnetic performances are investigated in detail. The magnetization state variation’s range is wide. Magnetizing/demagnetizing current is small. By fully using reluctance torque, variable-flux PMSM’s torque ability improves greatly. The ratio of high efficiency area in total torque-speed operating area increases obviously. The efficiency during high speed operation also increases. This machine has advantages and overcomes limitations of variable-flux machine which has series magnetic circuit or parallel magnetic circuit.

Characteristic analysis of conventional pole and consequent pole IPMSM for electric vehicle application

On December 12, 2020, President Xi Jinping announced at the Climate Ambition Summit that China will increase its nationally determined contribution, adopt more powerful policies and measures, and strive to reach the peak of carbon dioxide emissions by 2030, and strive to achieve carbon neutrality by 2060. As far as the automotive industry is concerned, replacing traditional fuel vehicles with electric vehicles is an important starting point for achieving carbon peak and carbon neutral goals. Inspired by the triangular permanent magnets of 2008 Lexus LS600H and 2012 Nissan LEAF, a 48-slot 8-pole conventional pole triangular interior permanent magnet synchronous machine (IPMSM) model and a 48-slot 8-pole consequent pole triangular interior permanent magnet synchronous machine model are created separately in this paper. The consequent pole IPMSM uses magnetic iron core instead of a part of the permanent magnet to reduce the amount of permanent magnets to make the processing process cleaner and lower carbon. The magnetic line of force of consequent pole IPMSM can be concentrated by the magnetic iron core to form a magnetic pole in order to reduce the dosage of the permanent magnet. Firstly, the finite element analysis (FEA) is used to optimize air gap flux density and confirm geometrical parameter of conventional pole IPMSM, then the FEA is used to confirm the geometrical parameter of consequent pole IPMSM machine by optimizing the output torque Tavg and torque ripple Tripple so that the Tavg of consequent pole IPMSM are similar to that of conventional pole IPMSM and Tripple of consequent pole IPMSM is lower than that of conventional pole IPMSM. The following analysis contents include no-load air gap magnetic density, back-EMF, cogging torque, torque ripple, loss and efficiency, flux-weakening performance. Finally, the following conclusion could be drawn that although Tavg of consequent pole IPMSM is slightly reduced compared to the conventional pole IPMSM, it uses fewer permanent magnets to meet output requirements and has better flux-weakening performance.

A Class of Linear–Nonlinear Switching Active Disturbance Rejection Speed and Current Controllers for PMSM

This article investigates a class of linear-nonlinear switching active disturbance rejection control (ADRC) to design speed controllers and current controllers for permanent magnet synchronous machine (PMSM) in servo systems, which aims at enhancing the ability of disturbance rejection of speed and current controllers for PMSM. First, the mathematical model of PMSM is introduced. Next, the design of a class of linear-nonlinear switching ADRCs is introduced in details. Then, the stability of linear-nonlinear switching extended state observers (ESOs) is proved by multiple Lyapunov functions. Lastly, the effectiveness of the speed and current controllers based on the linear-nonlinear active disturbance rejection technique is validated by experiments results of a 5.5-kW PMSM platform. Specially, the experiment results of the speed controllers illustrate that the amplitude of speed change of the proposed ADRCs is smaller than that of the linear ADRC (LADRC) when the step load torque disturbance occurs. The proposed ADRCs can overcome the overshoot of speed response caused by improper parameter setting of LADRC. The experiment results of the current controllers show that the proposed LNSADRC type 2 has greater robustness than the other ADRC controllers when b <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">02</sub> is not estimated accurately.

Two-dimensional steady-state thermal analytical model of permanent-magnet synchronous machines operating in generator mode

PurposeThermal analysis of electrical machines is usually performed by using numerical methods or lumped parameter thermal networks depending on the desired accuracy. The analytical prediction of temperature distribution based on the formal resolution of thermal partial differential equations (PDEs) by the harmonic modeling technique (or the Fourier method) is uncommon in electrical machines. Therefore, this paper aims to present a two-dimensional (2D) analytical model of steady-state temperature distribution for permanent-magnet (PM) synchronous machines (PMSM) operating in generator mode.Design/methodology/approachThe proposed model is based on the multi-layer models with the convolution theorem (i.e. Cauchy’s product theorem) by using complex Fourier’s series and the separation of variables method. This technique takes into the different thermal conductivities of the machine parts. The heat sources are determined by calculating the different power losses in the PMSM with the finite-element method (FEM).FindingsTo validate the proposed analytical model, the analytical results are compared with those obtained by thermal FEM. The comparisons show good results of the proposed model.Originality/valueA new 2D analytical model based on the PDE in steady-state for full prediction of temperature distribution in the PMSM takes into account the heat transfer by conduction, convection and radiation.

Compensating the performance of permanent magnet synchronous machines for fully electric vehicle using LPV control

The state-of-the-art robust H∞ linear parameter-varying controller is designed for wide speed operating range for non-linear mathematical model of permanent magnet synchronous machines (PMSM) in d-q reference frame for fully electric vehicle. This study propose polytopic approach using rotor speed as scheduling variable to reformulate mathematical model of PMSM into linear parameter varying (LPV) form. The weights were optimized for sensitivity and complementary sensitivity function. The simulation results illustrate fast tracking and enhanced performance of the proposed control technique over wide range of rotor speed. Moreover, as part of this work, the results of H∞ linear parameter varying controller is validated by comparing it with linear quadratic integrator and proportional integral derivative (PID) control techniques to show the effectiveness of the proposed control technique.

A novel method of model predictive control on permanent magnet synchronous machine with Laguerre functions

This paper aims to speed up the response and alleviate the computing load of model predictive control (MPC) of permanent magnet synchronous machine (PMSM). For this purpose, the Laguerre functions were extended to MPC, creating novel linear controller (LMPC) for the PMSM model. Firstly, the differences of control variables between adjacent sampling periods were regarded as a unit impulse response of a stable system, which can be approximated by a few terms of Laguerre polynomials. In this way, the difference of control variables can converge to zero quickly through parameter adjustment. Then, the current and voltage constraints in the form of Laguerre functions were applied on PMSM to improve the current response to sudden changes of speed or load. Furthermore, the torque load was applied to the state space model of PMSM to optimize the response to external load. Simulation results show that the proposed LMPC controller can effectively reduce the computing complexity that restricts the application of MPC on PMSM.

A Survey on Fault Diagnosis and Fault Tolerant Methodologies for Permanent Magnet Synchronous Machines

This paper presents a comprehensive survey of fault diagnosis and fault tolerant approaches for permanent magnet synchronous machines (PMSM). PMSMs are prominent in the pervading usage of electric motors, for their high efficiency, great robustness, reliability and low torque inertia. In spite of their extensive appliance, they can be quite non-resilient and inadequate in operation when faults appear in motor drive apparatus such as inverters, stator windings, sensors, etc. These may lead to insulation failure, torque fluctuations, overcurrent or even system collapse. On that account, fault diagnosis and fault tolerant methods are equipped to enhance the stability and robustness in PMSMs. Progressive methodologies of PMSM fault diagnosis and tolerance are classified, discussed, reviewed and compared in this paper, beginning with mathematical modeling of PMSM and then scrutinizing various fault conditions in PMSMs. Finally, the scope of research on the topic is highlighted. The contribution of this review is to emphasize optimistic schemes and to assist researchers with the latest trends in this field for future directions.

Interturn short‐circuit fault diagnosis in PMSM with partitioned stator windings

A new signal-based strategy for stator winding interturn short-circuit fault detection and isolation in permanent magnet synchronous machines (PMSM) is proposed. The strategy is based on an analysis of the midpoint voltage of the phase windings. A PMSM model with partitioned stator windings including an interturn short-circuit fault is presented. Unlike the motor current signature analysis methods, the midpoint voltage measurement allows detecting an incipient stator fault even under external disturbances without false alarms. For PMSM generators used in variable-speed wind turbines, the random changes of wind produce fluctuations in the rotor speed. In this situation, conventional fault detection methods used for the steady-state condition may produce errors in the fault diagnosis. However, the proposed strategy is capable of rejecting the effects of the non-stationary speed conditions by resampling the voltage signals at fixed increments of the rotor angular position. Several experimental results in time and frequency-domain are presented for different speed conditions using a PMSM with modified stator winding.

Field Prediction and Validation of a Slotless Segmented-Halbach Permanent Magnet Synchronous Machine for More Electric Aircraft

High-performance propulsion motors for more electric aircraft (MEA) are highly appreciated in transportation electrification. For the widely adopted permanent magnet synchronous machines (PMSMs) for MEA propulsion, the segmented Halbach magnetization has distinct merit that it contributes to sinusoidal air-gap magnetic fields for smooth operation. However, it is hard to fast predict the field distribution and machine performance due to the model complexity. Based on the subdomain method, this article first proposes an exact analytical model for slotless PMSM with the segmented Halbach PMs. Then, the model is applied in the fast computation of the magnetic field and performance prediction. Subsequently, the analytical results are compared with the finite element method (FEM), including the flux density, flux linkage, induced voltage, and steady-state torque at different loads. Also, the computation burden and prediction error are included to validate the model’s rapidity and accuracy. Finally, by prototype fabrication and unique field measurement methods, the flux density distribution is originally validated.

Sensorless Control of Permanent Magnet Synchronous Machine with Magnetic Saliency Tracking Based on Voltage Signal Injection

This paper presents a sensorless control method of a permanent magnet synchronous machine (PMSM) with magnetic saliency estimation. This is based on a high-frequency injection (HFI) technique applied on the modified PMSM model in the γδ reference frame. Except for sensorless control, an emphasis is placed on the magnetic saliency estimation to indicate a practical approach in tracking PMSM inductance variations. The magnetic saliency is determined using calculations embedded in the speed and position algorithm through current measurements. A notable characteristic of the modified PMSM model is that the corresponding rotor flux integrates both permanent magnet and saliency term fluxes. In applying a HFI technique for sensorless control, the structure of the PMSM flux model is formatted accordingly. A novel inductance matrix is derived that is completely compatible with the HFI methodology, since its elements include terms of angle error differential and average inductances. In addition, a sliding mode observer (SMO) is designed to estimate the speed and angle of rotor flux based on equivalent control applying a smooth function of the angle error instead of a sign one to reduce the chattering phenomenon. The control strategy is principally based on the adequacy of the proposed modified model and on the appropriateness of the SMO structure to successfully track the rotor flux position with the required stability and accuracy. Simulation results demonstrate the performance of the PMSM sensorless control verifying the effectiveness of the proposed algorithm to detect PMSM saliency, speed and position in steady state and transient modes successfully.

Simulation Study on On-Line MTPA/MTPV Trajectory Tracking in PMSMs with Power Management

This paper proposes an on-line maximum torque per ampere (MTPA)/maximum torque per voltage (MTPV) trajectory tracking method in permanent magnet synchronous machines (PMSMs) with power management. The on-line MTPA/MTPV machine current trajectory tracking algorithm is developed from PMSM model. Maximum source current and machine current are regulated to enhance hardware protection during machine current trajectory tracking. The maximum source current management is achieved by iterating within the current trajectory tracking algorithm over continuous torque command modifications based on power flow analysis, and the maximum machine current management is achieved by torque command limiting based on current angle modulation. Different from the existing techniques in literature, the proposed method has an unique feature of providing on-line regulation of source current, while maintaining on-line MTPA/MTPV trajectory tracking in PMSMs. It also provides machine and inverter overcurrent regulation to enhance their protection. In addition, the proposed method is flexible to tune and does not require off-line calibration. The effectiveness of the proposed method is confirmed by simulation results in MATLAB.

Nonparametric Predictive Current Control for PMSM

Conventional finite-control set model predictive current control predicts the motor behavior for every switching state and selects the voltage vector that can minimize the cost functions as an optimum voltage vector. To get rid of the model parameter dependency, a finite-control set nonparametric predictive current control (NPCC) was proposed before, which can predict future current behavior using the measured data instead of initial model parameters. However, one of the main issues that are limiting the current and torque ripple performance is a stagnant current update mechanism. To overcome this issue, this article proposes a novel current update mechanism that based on two most recent current variations to reconstruct the permanent magnet synchronous machine model. The proposed nonparametric predictive current control based on the current update mechanism can effectively reduce the torque ripple and enhance current performance in contrast to NPCC. Experiment results are demonstrated to verify the effectiveness of the proposed method under different operating conditions.

Behavior Study of Permanent Magnet Synchronous Machines Based on a New Normalized Model

Permanent magnet synchronous machines (PMSMs) are widely used in many applications. The performance of the PMSM is highly dependent on the motor parameters. Many research studies have been done to evaluate the PMSM performances in terms of maximum torque capability, power capability, and field-weakening capability. This paper proposes a new normalized PMSM model and uses two parameters, characteristic current and saliency ratio, to uniquely define the motor characteristic. Based on this normalized model, the full map motor behaviors, including torque capability, power capability, torque/power-speed characteristics, and power factor behaviors, are studied parametrically. A new unitless metric, i.e., copper loss factor, is introduced to evaluate the copper loss variation of PMSMs. The saturation effect on the motor behavior is studied based on the 2004 Prius traction motor, which confirms that the field-weakening characteristic can be well predicted using the linearized model. A new design flow for traction PMSMs, which requires wide-speed operation, is proposed based on the full map motor behavior study, and a prototype machine is designed accordingly. The behavior study and the effectiveness of the traction motor design flow are validated experimentally by the prototype.

Inter-Turn Short-Circuit Fault Detection Approach for Permanent Magnet Synchronous Machines Through Stray Magnetic Field Sensing

Fast online detection of inter-turn short-circuit faults for permanent magnet synchronous machines (PMSMs) is a challenging task. Previous attempts based on phase currents or back EMF monitoring lack the capability to accurately locate the inter-turn short-circuit faults in stator windings. This paper proposed a new approach to online inter-turn short-circuit fault detection for PMSMs by means of sensing the external stray magnetic field outside the motor stator yoke. The stray magnetic field provides the information about the phase currents as well as the status of stator windings and thus, the location of inter-turn short-circuit fault can be detected accordingly. In this paper, the inter-turn short-circuit model and the stray magnetic flux model for PMSMs were theoretically analyzed. Both FEM simulations and experiments have been presented to validate the effectiveness of the proposed approach. A sensor array composed of 24 sensitive tunneling magnetoresistive (TMR) sensor units was employed to measure the stray magnetic field distribution outside the PMSM stator yoke. The experimental results show that both the location and severity of the inter-turn short-circuit fault in PMSMs were effectively detected using the proposed approach.

Multiple Reference Frame-Based Extended Concentrated Wound PMSM Model Considering PM Flux Linkage and Inductance Harmonics

Permanent magnet (PM) synchronous machines (PMSMs) with concentrated windings (CW) exhibit high content of space harmonics leading to non–sinusoidal distribution of PM flux linkage and phase inductances in addition to the non-sinusoidal wave shape of the induced electromotive force. The ideal single reference frame-based PMSM model considers these parameters to be sinusoidal and does not include the effect of harmonics. Hence, computation of electromagnetic torque using ideal model can lead to deviation from the actual waveform. In this paper, a novel analytical model for electromagnetic torque has been derived using multiple reference frames (MRF) incorporating non-sinusoidal aspects of CW PMSM. Initially, the PM flux linkage and inductances in abc frame are extended by incorporating higher order harmonics. Then, the extended model is transformed into dq –axis using MRF rotating at speeds of dominant harmonics in PM flux linkages and inductances, the fundamental being the electrical rotor frequency. Based on this MRF model, a comprehensive electromagnetic torque model for the CW PMSM is derived. Simulation and experiments are conducted on a CW PMSM to validate the proposed model under different operating conditions.