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The purpose of this paper is to include thermal analysis in the design process of permanent magnet synchronous motor (PMSM). The additional objective is a comparison of PMSM with induction motor (IM) in terms of thermal phenomena.

Numerical investigation using commercial software MotorSolve was performed. Parameterized models of PMSM and IM were used. Calculations of motor parameters and temperature distribution were made using Finite Element Method.

The results of the calculations show that thermal calculations should be included in the design process because the maximum permissible operating temperature of permanent magnets should not be exceeded. A comparative analysis of PMSM and IM shows that the PMSM has better parameters than the IM which was used as a base of the PMSM construction.

Computational models should be verified experimentally on a physical model or by using more complex numerical models. In the case of IM thermal calculations, a method of air speed calculation should be proposed. Air speed is a parameter that is necessary in thermal analysis of IM, but during the design process it is unknown.

This paper presents modelling methodology of 3D transient thermal field coupled with electromagnetic field applied in a three-phase IM at rated load conditions. This paper presents a design strategy which includes thermal analysis of the designed PMSM. Moreover, the paper shows a comparison between PMSM and IM indicating advantages of PMSM over IM.

Voltage source inverter-fed permanent magnet synchronous motors (VSI-PMSMs) are widely used in industrial actuation and mechatronic systems in water pumping stations, as well as in the traction of transportation systems (such as electric vehicles and electric trains or ships with electric propulsion). The dynamic model of VSI-PMSMs is multivariable and exhibits complicated nonlinear dynamics. The inverters’ currents, which are generated through a pulsewidth modulation process, are used to control the stator currents of the PMSM, which in turn control the rotational speed of this electric machine. So far, several nonlinear control schemes for VSI-PMSMs have been developed, having as primary objectives the precise tracking of setpoints by the system’s state variables and robustness to parametric changes or external perturbations. However, little has been done for the solution of the associated nonlinear optimal control problem. The purpose of this study/paper is to provide a novel nonlinear optimal control method for VSI-fed three-phase PMSMs.

The present article proposes a nonlinear optimal control approach for VSI-PMSMs. The nonlinear dynamic model of VSI-PMSMs undergoes approximate linearization around a temporary operating point, which is recomputed at each iteration of the control method. This temporary operating point is defined by the present value of the voltage source inverter-fed PMSM state vector and by the last sampled value of the motor’s control input vector. The linearization relies on Taylor series expansion and the calculation of the system’s Jacobian matrices. For the approximately linearized model of the voltage source inverter-fed PMSM, an H-infinity feedback controller is designed. For the computation of the controller’s feedback gains, an algebraic Riccati equation is iteratively solved at each time-step of the control method. The global asymptotic stability properties of the control method are proven through Lyapunov analysis. Finally, to implement state estimation-based control for this system, the H-infinity Kalman filter is proposed as a state observer. The proposed control method achieves fast and accurate tracking of the reference setpoints of the VSI-fed PMSM under moderate variations of the control inputs.

The proposed H-infinity controller provides the solution to the optimal control problem for the VSI-PMSM system under model uncertainty and external perturbations. Actually, this controller represents a min–max differential game taking place between the control inputs, which try to minimize a cost function that contains a quadratic term of the state vector’s tracking error, the model uncertainty, and exogenous disturbance terms, which try to maximize this cost function. To select the feedback gains of the stabilizing feedback controller, an algebraic Riccati equation is repetitively solved at each time-step of the control algorithm. To analyze the stability properties of the control scheme, the Lyapunov method is used. It is proven that the VSI-PMSM loop has the H-infinity tracking performance property, which signifies robustness against model uncertainty and disturbances. Moreover, under moderate conditions, the global asymptotic stability properties of this control scheme are proven. The proposed control method achieves fast tracking of reference setpoints by the VSI-PMSM state variables, while keeping also moderate the variations of the control inputs. The latter property indicates that energy consumption by the VSI-PMSM control loop can be minimized.

The proposed nonlinear optimal control method for the VSI-PMSM system exhibits several advantages: Comparing to global linearization-based control methods, such as Lie algebra-based control or differential flatness theory-based control, the nonlinear optimal control scheme avoids complicated state variable transformations (diffeomorphisms). Besides, its control inputs are applied directly to the initial nonlinear model of the VSI-PMSM system, and thus inverse transformations and the related singularity problems are also avoided. Compared with backstepping control, the nonlinear optimal control scheme does not require the state-space description of the controlled system to be found in the triangular (backstepping integral) form. Compared with sliding-mode control, there is no need to define in an often intuitive manner the sliding surfaces of the controlled system. Finally, compared with local model-based control, the article’s nonlinear optimal control method avoids linearization around multiple operating points and does not need the solution of multiple Riccati equations or LMIs. As a result of this, the nonlinear optimal control method requires less computational effort.

Voltage source inverter-fed permanent magnet synchronous motors (VSI-PMSMs) are widely used in industrial actuation and mechatronic systems in water pumping stations, as well as in the traction of transportation systems (such as electric vehicles and electric trains or ships with electric propulsion), The solution of the associated nonlinear control problem enables reliable and precise functioning of VSI-fd PMSMs. This in turn has a positive impact in all related industrial applications and in tasks of electric traction and propulsion where VSI-fed PMSMs are used. It is particularly important for electric transportation systems and for the wide use of electric vehicles as expected by green policies which aim at deploying electromotion and at achieving the Net Zero objective.

Unlike past approaches, in the new nonlinear optimal control method, linearization is performed around a temporary operating point, which is defined by the present value of the system’s state vector and by the last sampled value of the control input vector and not at points that belong to the desirable trajectory (setpoints). Besides, the Riccati equation, which is used for computing the feedback gains of the controller, is new, as is the global stability proof for this control method. Comparing with nonlinear model predictive control, which is a popular approach for treating the optimal control problem in industry, the new nonlinear optimal (H-infinity) control scheme is of proven global stability, and the convergence of its iterative search for the optimum does not depend on initial conditions and trials with multiple sets of controller parameters. It is also noteworthy that the nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state-dependent Riccati equations (SDRE). The SDRE approaches can be applied only to dynamical systems that can be transformed to the linear parameter varying form. Besides, the nonlinear optimal control method performs better than nonlinear optimal control schemes which use approximation of the solution of the Hamilton–Jacobi–Bellman equation by Galerkin series expansions.

Electromagnetic noise of permanent magnet synchronous motor (PMSM) seriously affects the sound quality of electric vehicles (EVs). This paper aims to present a comprehensive process for the electromagnetic noise analysis and optimization of a water-cooled PMSM.

First, the noises of an eight-pole 48-slot PMSM in at speeds up to 10,000 rpm are measured. Furthermore, an electromagnetic-structural-acoustic model of the PMSM is established for multi-field coupling simulations of electromagnetic noises. Finally, the electromagnetic noise of the PMSM is optimized by using the multi-objective genetic algorithm, where a multi-objective function related to the slot width of PMSM stator is defined for radial electromagnetic force (REF) optimization.

The experimental results show that main electromagnetic noises are the 8n-order (n = 1, 2, 3, …) and 12-order noises. The simulated results show that the REFs are mainly generated by the 8n-order (n = 1, 2, 3, 4, 5, 6) vibrations, especially those of the 8th, 16th, 24th and 32th orders. The 12-order noise is a mechanical noise, which might be caused by the bearings and other structures of the PMSM. Comparing the simulated results before and after optimization, both the REFs and electromagnetic noises are effectively reduced, which suggests that an appropriate design of stator slot is important for reducing electromagnetic noise of the PMSM.

In view of applications, the methods proposed in this paper can be applied to other types of PMSM for generation mechanism analysis of electromagnetic noise, optimal design of PMSM and thereby noise improvement of EVs.

The purpose of this paper is to present a two-loop approach for velocity control of a permanent magnet synchronous motor (PMSM) under mechanical uncertainties.

The inner loop calculates the two-axis stator reference voltages through a feedback linearization method. The outer loop employs an RST control structure to compute the q-axis stator reference current. To increase the robustness of the proposed method, the RST controller parameters are adapted through a fractional order model reference adaptive system (FO-MRAS). The fractional order gradient and Lyapunov methods are utilized as adaptation mechanisms.

The effect of the fractional order derivative in the load disturbance rejection, transient response speed and the robustness is verified through computer simulations. The simulation results show the effectiveness of the proposed method against the external torque and mechanical parameters uncertainties.

The proposed FO-MRAS based on Lyapunov adaptation mechanism is proposed for the first time. Moreover, application of the FO-MRAS for velocity control of PMSM is presented for the first time.

This paper is aimed at investigating the potential advantages of flux‐switching machines (FSM) compared to permanent magnet synchronous machines (PMSM), particularly for the applications of electric vehicle traction.

A 12‐slot 14‐pole PMSM designed for an in‐wheel traction application is chosen for the comparison. With the same volume constraint, three 12/14 FSM structures are created. Both the PMSM and the three FSM structures are modeled using the software Flux. Based on these models, finite element analyses (FEA) are performed, and the results are compared in terms of open‐circuit back electromotive force (EMF), electrical loading capability, and thermal conditions.

Within the same volume constraint, a 12/14 FSMs can achieve the maximum torque higher than the one of 12/14 PMSM. This conclusion is drawn based on the observed facts that at the same rotor speed, a larger open‐circuit back EMF is induced in the FSM, while a larger electrical loading is also allowed in this machine, compared to the PMSM. In addition, the risk of demagnetization during the process of field weakening proves to be lower in FSMs than PMSMs. This advantage suggests a potentially wide constant power speed range (CPSR) of FSMs, which is especially beneficial in automotive applications.

This research can be continued with investigating the field weakening capability and iron losses of FSMs.

This paper proposed two optional structures of FSMs to reduce the amount of permanent magnets. It also highlighted the effectiveness of FSMs in cooling these magnets.

This paper mainly aims to deal with the problems of uncertainties including modelling errors, unknown dynamics and disturbances caused by load mutation in control of permanent magnet synchronous motor (PMSM).

This paper proposes an enhanced speed sensorless vector control method based on an active disturbance rejection controller (ADRC) for a PMSM. First, a state space model of the PMSM is obtained for the field orientation control strategy. Second, a sliding mode observer (SMO) based on back electromotive force (EMF) is introduced to replace the encode to estimate the rotor flux position angle and speed. Third, an infinite impulse response (IIR) filter is introduced to eliminate high frequency noise mixed in the output of the sliding mode observer. In addition, a speed control method based on an extended state observer (ESO) is proposed to estimate and compensate for the total disturbances. Finally, an experimental set-up is built to verify the effectiveness and superiority of the proposed ADRC-based control method.

The comparative experimental results show that the proposed speed sensorless control method with the IIR filter can achieve excellent robustness and speed tracking performance for PMSM system.

An enhanced sensorless control method based on active disturbance rejection controller is designed to realize high precision control of the PMSM; the IIR filter is used to attenuate the chattering problem of traditional SMO; this method simplifies the system and saves the total cost due to the speed sensorless technology.

The use of sensorless can reduce costs and be more beneficial to actual industrial application.

The proposed enhanced speed sensorless vector control method based on an ADRC with the IIR filter enriches the control method of PMSM. It can ameliorate system robustness and achieve excellent speed tracking performance.

For vector control of permanent magnet synchronous motor (PMSM) requires motor speed and rotor position estimation. The precision of the open-loop techniques of the stator flux and speed for vector control PMSM drive drops as mechanical speed decreases. The stator resistance and estimated stator flux values crisscross have a huge effect on the transient and steady-state performance of the drive at lower speed. The framework turns out to be increasingly strong against parameter crisscross and signal noises by using adaptive observers for estimation of speed and flux.

This paper presents a comparison of two-speed observers for the vector control PMSM drive: the sliding mode observer (SMO) and the model reference adaptive system (MRAS). A comprehensive analysis of SMO and MRAS respects dynamic, steady-state performance and robustness, affectability, stability and computational complexity has been introduced. The abstract of the advantages and disadvantages of both observer and their comparative analysis have also been discussed.

Dynamic performance steady-state performance and robustness, affectability and stability.

This paper presents a sensorless scheme, namely, MRAS and SMO for control of PMSM drive. These sensorless techniques have been tested for a PMSM motor drive and the motor performance was compared for both techniques. Matlab/Simulink based simulation results conclude that the adaptive methods improve dynamic response, reduces torque ripples and extended speed range.

This paper aims to present a cascaded pseudo derivative feedback (PDF) plus pseudo derivative feedback plus pseudo derivative feedforward (PDFF) controller for a permanent magnet synchronous motor (PMSM) to improve the transient response of the system.

Proportional integral (PI) plus PI controller and the proposed PDF plus PDFF controller are designed, stability analysis is performed using the extended root locus method, and the effect of the damping coefficient is also extensively studied to validate the robustness of the proposed controller.

When compared to a cascaded PI plus PI controller, the proposed control approach has a much shorter settling time for the entire system and a 50% reduction in overshoot in stator current under extensive variations in speed with load disturbance.

The proposed controller is programmed into an FPGA Altera Cyclone II and applied to a 1.5 kW laboratory prototype PMSM drive. The effectiveness of the proposed methods has been demonstrated experimentally throughout a wide variable speed range, from 0 to 157 rad/s at different load conditions.

The purpose of this study is to propose an analytical model with consideration of the permeability of soft-magnetic materials, which can predict the magnetic field distribution more accurately and facilitate the initial design and parameter optimization of the machine.

This paper proposes an analytical model of stator yokeless radial flux dual rotor permanent magnet synchronous machine (SYRFDR-PMSM) with the consideration of magnetic saturation of soft-magnetic material. The analytical model of SYRFDR-PMSM is divided into seven regions along the radial direction according to the different excitation source and magnetic medium, and the iron permeability in each region is considered based on the Maxwell–Fourier method and Cauchy’s product theorem. The magnetic vector potential of each region is obtained by the Laplace’s or Poisson’s equation, and the magnetic field solution is determined using the boundary conditions of adjacent regions.

The inner and outer air-gap flux density, flux linkage, output torque, etc., of SYRFDR-PMSM are predicted by analytical model, resulting in good agreement with that of finite element model. Additionally, the SYRFDR-PMSM prototype is manufactured and the correctness of analytical model is further verified by experiments on no-load back electromotive force and current–torque curve. Reasonable design of the slot opening width and pole arc coefficient can improve the average output torque and reduce output torque ripple.

The analytical model proposed in this paper assumes that the permeability of soft-magnetic material is a fixed value. However, the actual iron’s permeability varies nonlinearly; thus, the prediction results of the analytical model will have some deviations from the actual machine.

The main contribution of this paper is to propose an accurate magnetic field analytical model of SYRFDR-PMSM. It takes into account the permeability of soft-magnetic material and slot opening, which can quickly and accurately predict the electromagnetic performance of SYRFDR-PMSM. It can provide assistance for the initial design and optimization of SYRFDR-PMSM.

To eliminate the angle deviation of magnetic encoder, this paper aims to propose a compensation method based on permanent magnet synchronous motor (PMSM) sensorless control. The paper also describes the experiments performed to verify the validity of this proposed method.

The proposed method uses PMSM sensorless control method to get high precision virtual angle value, and then get the deviation value between virtual position and magnetic angle which is used as compensation table. Oversampling linear interpolation tabulation method has been proposed to eliminate the noise signals. Finally, a magnetic encoder with precision (repeatability) 0.09° and unidirectional motion precision 0.03 is realized. The control system with an encoder running at 14,000 and 0.01 r/min showing high motion resolution is also realized.

Higher value of current in PMSM leads to a magnetic encoder with higher precision. When using oversampling linear interpolation to tabulate the compensation table, it is understood that more oversampling does not lead to a better result. Finally, validated by experiments, using eight intervals to calculate the mean value of angle deviation leads to the best result.

The angle deviation compensation method proposed in this paper has a great practical implication and a good commercial application. The method proposed in this paper could be effectively used to self-correct the magnetic encoder using arctangent method and also correct any rotary encoder sensor.

This paper originally proposes an adaptive correction method for a rotary encoder based on PMSM sensorless control. To eliminate the noise signals in an angle compensation table, over-sampling linear interpolation tabulation method has been proposed which also guarantees the precision of the compensation table.