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One of the main obstacles to the robust optimization for permanent magnet machines is the high computational burden, which is mainly caused by the robustness evaluation process considering the manufacturing uncertainties. In this paper, a sequential sampling Kriging model is adopted to estimate the design robustness, and the problem of high-dimensional variables for the surrogate model due to uncertainties is avoided through adopting the worst-case based approach. To further reduce the number of finite element analyses (FEA) required for constructing a metamodel, a multi-points sequential sampling process with a two-step optimization oriented surrogate model updating algorithm is proposed. Compared with the FEA directly based robust optimization in previous work, similar Pareto Fronts are achieved by adopting the meta-model proposed algorithm but the overall run time reduced by 75%. In the end, an optimization problem for a 1.2 kW motor is considered by applying the proposed algorithm, and two prototypes with deliberately designed tolerances, imitating the worst-case scenarios in the real world, are manufactured. The worst-case torque ripple is reduced from 7.6% to 4.8% after optimizing, and this verifies the efficacy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous motor (PMSM) possesses the advantages of low power loss, high power density and high torque density and, hence, has achieved broad applications in both industrial drives and home appliances. With the increasing demands for high power density, the PMSM often operates at high speed and high frequency, leading to high power loss and temperature rise. Consequently, proper consideration of power loss, including the core loss, has attracted much attention for the modelling, designing, controlling and optimizing of PMSMs. However, the widely used equivalent circuit model, capable of providing good analysis results with fast calculation, often ignores the core loss, which may lead to unsatisfactory motor performance. This paper aims to investigate the development of equivalent circuit models, with predictable core loss for PMSMs, and proposes novel equivalent circuit models, which improve the core loss prediction accuracy in the load conditions. Some thoughts about the further improvement of the models are proposed and discussed. [ABSTRACT FROM AUTHOR]

To improve the torque accuracy for open-end winding permanent magnet synchronous motor (OEW-PMSM) with common dc bus, it is necessary to eliminate the zero-sequence torque (ZST) caused by zero-sequence current (ZSC) and the third back electromotive force. But the third flux linkage mismatch can enlarge ZSC which causes torque ripple. To deal with the above problem, firstly, a q-axis current injection method combined with deadbeat predictive current control (DPCC) is adopted to inject an extra current into the reference q-axis current. The extra torque generated by this injected current can compensate for ZST. Secondly, to ensure the accuracy of the q-axis injected current, a parameter identification method based on recursive least square (RLS) algorithm with forgetting factor is presented to identify the third flux linkage accurately. The identification value can reduce ZSC and torque ripple under different working conditions. And the accurate q-axis injected current can be obtained to counteract ZST and output accurate torque. Finally, three methods are comparatively analyzed in this paper, namely the traditional DPCC method, the DPCC method with q-axis current injection and the proposed DPCC method based on RLS with forgetting factor. The simulation and experimental results verify the effectiveness of the proposed DPCC method. [ABSTRACT FROM AUTHOR]

This article discusses a method to consider the effects of the manufacturing uncertainties on the additional cogging torque harmonics. With this method, the sensitivity analysis can be incorporated into the design stage instead of just checking it afterwards. With the authors’ previous work of the worst-uncertain-combination-analysis (WUCA) method, several design parameters and their effects on the additional cogging torque harmonics under uncertainties are discussed. It is demonstrated that a design with inherent robustness can be obtained through the proper selection of pole-arc coefficient and slot-opening width. In addition, a sensitivity index is proposed to estimate the effects of parameter uncertainties on torque harmonics. Some suggestions on improving the design robustness are consequently provided from the aspects of tolerances control and parameter design. The deductions are verified through finite element analysis (FEA) on different pole/slot configurations. [ABSTRACT FROM AUTHOR]

To improve the performance of open-winding permanent magnet synchronous motors (OW-PMSMs) with a common dc bus, a novel control method that can simultaneously eliminate parameter mismatch in the d-axis, q-axis, and zero-sequence loop (ZSL) is proposed. First, the parameter mismatches are analyzed. Second, an extended state observer (ESO), which can predict the current in the next instant and the disturbance caused by parameter mismatch, is established. By combining the ESO and the deadbeat predictive current control (DPCC) in the d-axis and q-axis, replacing the sampled current in the DPCC with the predictive current in the ESO, and considering predictive disturbance as a voltage reference feedforward compensation, one-step delay and the disturbance caused by parameter mismatch are addressed. Then, in the ZSL, the predicted zero-sequence disturbance is considered as a compensation for the reference zero-sequence voltage (ZSV). The ZSV is obtained using the zero-voltage vector redistribution strategy in alternate subhexagonal center pulsewidth modulation strategy. The proposed method enhances the robustness of OW-PMSM, against parameter mismatch in the d-axis, q-axis, or ZSL. To verify the effectiveness of the proposed method, simulation and experimental results obtained using the traditional DPCC method and the ESO+DPCC method are presented herein. [ABSTRACT FROM AUTHOR]

Finite-set model predictive current control (FS-MPCC) has been employed for machine drives owing to the good dynamic performance. Sensitivity to parameter variation is one of the main barriers to its widespread application. To overcome this barrier, this article proposes an improved FS-MPCC for surfaced permanent magnet synchronous machines (SPMSMs). The contribution of this article is developing a novel current update mechanism, where the variation of resistance, rotor flux linkage, and inductance is considered, in which a modified coordinate system that contains a stationary and rotary axis frame is introduced. In this case, the predicted parameter can be obtained more accurately based on this mechanism, which can suppress the disturbances caused by model parameter mismatch. In addition, SPMSM parameter mismatch effect on FS-MPCC performance is analyzed in this article, which testifies that resistance mismatch influence on current prediction error can be neglected in practical system. The proposed FS-MPCC is validated and compared with different state-of-the-art methods. Improvement of the proposed control strategy is validated by means of experimental results on a 2-kW test rig. [ABSTRACT FROM AUTHOR]

One of the main obstacles to applying the robust optimization for the permanent magnet motors is the high computational burden, which is mainly caused by the robustness evaluation considering the manufacturing uncertainties. In this article, efforts are made to speed up the process of robust optimization, from the aspects of reducing the computational cost, and avoiding the computing resources being wasted. Firstly, several widely used methods, aiming to identify the worst-case performance under uncertainties, are examined, and compared. And the efficient worst-uncertain-combination-analysis (WUCA) method is consequently adopted to significantly reduce the computational cost of robustness evaluation. From another aspect, the parameter rounding (PR) operation is inevitable due to the constraint of manufacturing accuracy, but its adverse effects on the optimization are often ignored. It is found that parts of the computing resources might be wasted during the optimization. A new PR during the calculation (PRDC) method is proposed, and incorporated into the process of robust optimization. Compared with the conventional one, similar results can be achieved with the computational time reduced by approximately $\text{11}\%$ in the PRDC modified robust optimization. [ABSTRACT FROM AUTHOR]

Model predictive current control (MPCC) can predict future motor behavior according to a motor model. In practice, however, motor parameters will vary at run time, and the parameter mismatch disturbances caused by the variation in motor parameters will deteriorate the MPCC performance. To suppress the parameter mismatch disturbances effectively, this paper proposes a modified MPCC with a current variation update mechanism. In contrast with the traditional current prediction equation that contains crude model parameters, the modified current prediction equation contains only measured information, taking advantage of the proposed current variation update mechanism, which can update the modified prediction equation within each sampling period. A simulation established by MATLAB software indicates that the proposed method can effectively suppress the parameter mismatch disturbances. Experiments are carried out to verify the correctness of the proposed method. [ABSTRACT FROM AUTHOR]

Soft magnetic composite (SMC) materials and SMC electromagnetic devices have attracted strong research interest in the past decades. However, SMC devices have large core loss that needs to be put into consideration even at the design stage. Effective and accurate prediction of the core loss becomes crucial for the design and optimization of high-performance motors with these materials. Equivalent circuit model is a widely used method for machine analysis, due to the advantages in the fast calculation with a clear physical mechanism. This paper presents an equivalent circuit model to predict the core loss of a claw-pole permanent magnet motor with SMC stator core. All the parameters including the equivalent core-loss resistance in the equivalent circuit model are identified based on the finite-element method to achieve high accuracy, and the effectiveness of the parameters identification methods is experimentally verified. The proposed equivalent circuit model can predict the core loss and motor’s performance efficiently both under no-load and loading conditions. [ABSTRACT FROM AUTHOR]

This paper presents a computationally efficient loss prediction procedure and thermal analysis of surface-mounted brushless AC permanent magnet (PM) machine considering the UDDS driving duty cycle by using a lumped parameters’ thermal model. The accurate prediction of loss and its variation with load are essential for thermal analysis. Employing finite element analysis (FEA) to determine loss at every load point would be computationally intensive. Here, the finite element analysis and/or experiment based computationally efficient winding copper and iron loss and permanent magnet (PM) power loss models are employed to calculate the electromagnetic loss at every operation point, respectively. Then, the lumped parameter thermal method is used to analyse the thermal behaviour of the driving PM machine. Experiments have been carried out to measure the temperature distribution in a motor prototype. The calculation and experiment results are compared and discussed. [ABSTRACT FROM AUTHOR]

This paper describes a computationally efficient approach for mapping rotor power loss in permanent magnet (PM) machines. The PM loss mapping methodology discussed here utilizes a small number of time-step finite-element analyses (FEAs) to determine the parameters of a functional representation of loss variation with speed (frequency) and stator current and is intended for a rapid evaluation of machine performance over the entire torque–speed envelope. The research focus is placed on field-oriented-controlled brushless AC PM machines with surface-mounted PM rotor construction, although the method could be adapted for other rotor formats. The loss mapping procedure accounts for the axial segmentation of the PM array through the use of an equivalent electrical resistivity of the segmented PM array, which is obtained from three-dimensional (3-D) FEA. The PM loss can be accurately mapped across the full operational envelope, including the field-weakened mode, through a single 3-D and four two-dimensional time-step FEAs. The proposed methodology is validated on an 18-slot 16-pole surface-mounted brushless AC PM machine design. The loss mapping procedure results closely agree with the computationally demanding alternative of direct 3-D finite-element prediction of the PM power loss undertaken at each of the machine's operating points. [ABSTRACT FROM PUBLISHER]

To improve the suppression ability of uncertain disturbance of the sliding mode control driving system of the surface-mounted permanent magnet synchronous motor (SPMSM) and to reduce the chattering of the control output, a robust sliding mode control strategy with an improved power reaching law (IPRL) is proposed in this paper. Compared with the traditional fast power reaching law (FPRL), the IPRL incorporates the sum of the power terms of the system state variables into the conventional power terms, and uses hyperbolic tangent saturation function to replace the piecewise function, which can effectively suppress the sliding mode chattering and improve the convergence speed of the system state to the sliding mode surface. Furthermore, the robust sliding mode speed controller and sliding mode current controller of the SPMSM are designed separately with the IPRL, and detailed simulation verification is carried out to reveal the effectiveness of the IPRL. Simulation and experimental results show that compared with the FPRL, the proposed IPRL can reduce the inherent chattering phenomenon in sliding mode control, and the IPRL-based speed and current control strategy can effectively improve the dynamic performance and robustness of the system. [ABSTRACT FROM AUTHOR]

The typical motor has poor heat dissipation conditions that are limited by the installation space and working environment, and the high operation temperature increase has been a bottleneck to improve the power density and torque density. The inner rotor motor is considered to be the research object, and an oil-cooling structure for end winding and stator core is proposed. The heat inside the motor is mainly carried away through the lubricating oil in the form of heat conduction and convection heat transfer. The 3d motor model was built using the ANSYS software. The temperature field of the motor was simulated to analyze the temperature distribution inside the motor under rated and peak working conditions. The low-speed high-torque test and one-hour temperature-rise test of the motor prototype were performed on a bench built in the laboratory. The comparison between the test results with water-cooled motor shows that the temperature-rise rate of oil-cooled motor with the same electromagnetic structure is slower than that of water-jacketed cooled motor, and the temperature difference between the front and back of the motor decreases by 18 °C in half an hour. The oil-cooled method has a good cooling effect on the stator core and works for longer time under rated conditions. [ABSTRACT FROM AUTHOR]