Optimal Stator Research Articles

Improvement on Electromagnetic Performance of Axial–Radial Flux Type Permanent Magnet Machines by Optimal Stator Slot Number

To achieve the objective of high torque, a high utilization rate of PMs, and flexible flux regulation capability of the permanent magnet (PM) machine, an axial–radial flux type permanent magnet (ARFTPM) machine was studied in this paper. The working principle of the ARFTPM machine is analyzed by illustrating the flux paths. Then, the influence of stator slot number on the flux regulation capability and torque is studied. A full comparison of the main parameters and electromagnetic performances of the ARFTPM machine with different stator slot numbers is presented, including winding coefficient, back electromotive force (EMF), cogging torque, average torque, and torque-angle characteristics. The optimal stator slot number was obtained. Finally, the 12-slot/10-pole prototype machine is manufactured and tested to validate the simulation data and theoretical analysis.

Performance improvement of a three phase induction squired-cage motor by winding topology configuration

The aim of this paper is to determine the optimal stator winding topology configuration for a 75 kW three-phase squirrel cage motor that provides the highest efficiency, power factor, and optimal starting parameters. The induction motor is simulated using Cedrat FLUX2D finite element software, which enables accurate modeling of its performance. Initially, the motor operation is simulated using the originally manufactured winding topology. Then, several alternative winding topology configurations are tested through numerical simulations. The performance results for each configuration are compared with those obtained from the original winding topology to identify the best option. The simulation results show that the shortened pitch concentric winding, combining both single and double layers, is the winding topology that offers the highest performance for the motor under study, significantly enhancing the overall efficiency of the system. These findings highlight the potential of optimized winding configurations in improving motor performance and energy efficiency.

Thermal Power and the Structural Parameters of a Wind Turbine Permanent Magnet Eddy Current Heater

Permanent magnet eddy current heating as a new type of wind energy utilization method, which is energy-saving, is zero-emission, and involves no pollution and a high utilization of wind energy, has attracted more and more attention. This paper deals with the simulation and optimal design of a permanent magnet eddy current heater (PMECH) driven by wind. Solid steel, closed-slot, and open-slot PMECH are proposed, and corresponding 2D finite element method (FEM) models are established. Using the skin depth concept, numerical analyses are conducted on the influence of the number, size, and position of copper strips on the thermal power of closed-slot and open-slot PMECHs, and the thermal power growth compared to solid steel PMECH. The results showed that there is an optimal value for stator wall thickness. When the air-gap length is 0.5 mm and the rotation speed is 200 and 1000 rpm, the optimal stator wall thickness is 16 and 9 mm, respectively. Compared to the influence of conductivity on thermal power, the influence of permeability is more significant. Compared with solid steel PMECH, both closed-slot and open-slot PMECH in a low-speed region can effectively improve thermal power, and the open slot has more obvious advantages. The maximum values of the thermal power growth (TPG) and thermal power growth rate (TPGR) of the closed-slot PMECH are 1.57 kW and 120.15%, respectively. The maximums of TPG and TPGR of the open-slot PMECH are 2.58 kW and 175.08%, respectively. The experimental results prove the validity of the analytical calculation.

Effect of pre-swirl stator angles on broadband noise considering hydrodynamic performance of pump-jet propeller

A pump-jet propeller is composed of a rotor, stator, and duct. A pre-swirl stator is employed to optimize flow into the rotor. The hydrodynamic and noise performances of pump-jet propellers vary with the stator angles. In this study, the hydrodynamic performance of a full-scale submarine and pump-jet propeller is assessed by conducting computational fluid dynamics simulations based on the Reynolds-averaged Navier–Stokes equation. Additionally, broadband noise, blade-passing frequency noise, and a significant factor, that is, underwater radiated noise are predicted using Lighthill’s equation, Green’s function, and wall pressure spectrum. Unsteady forces were extracted from the flow field to obtain the blade-passing frequency noise. Broadband noise could not be calculated directly from the flow field owing to the absence of small eddies, and wall pressure spectrum was used to obtain high-frequency broadband noise. The overall noise, including broadband noise and blade-passing frequency noise, was evaluated. The optimal stator angle for the rotor at the self-propulsion point was determined considering the propulsion efficiency and noise level of the pump-jet propeller.

Torque Capacity Improvement of Flux-Switching PM Machines Based on Directional Stator Permeance Design

As one type of flux modulation machines, flux-switching permanent magnet (FSPM) machines present high sensitivity to airgap structures. Therefore, both stator/rotor teeth and slot/pole combinations have significant influences on machine performance. However, the relationships between the optimal stator structure and maximum torque capability of the FSPM machine are barely investigated. Therefore, this paper is devoted to proposing a directional stator permeance design approach to achieve the maximum torque of the FSPM machines under a given rotor, and reveal the corresponding stator structure. First, the relations between torque and air-gap permeance are presented based on a constructed torque contribution equation, where amplitudes and phase angles of the stator permeance harmonics are determined. Then, main permeance harmonics are directionally optimized to enlarge positive torque, while negative contributions are inversed to be positive. Especially, two FSPMs with 6-slot/19-pole and 6-slot/13-pole are chosen as design examples, and their optimal design processes and torque performances have been deeply analyzed, which verifies the effectiveness of the proposed design approach.

Online Estimation of Three-Phase Induction Motor Parameters Using an Extended Kalman Filter for Energy Saving

In this paper, the online estimation of three-phase induction motor parameters using an extended Kalman filter for energy saving is proposed. The optimal value of the stator current on the d-axis is calculated to obtain the minimum power loss. Accurate motor parameters are required to calculate the optimal stator current value for energy saving. Hence, to estimate motor parameters in real time, an online estimator known as the extended Kalman filter is applied. The energy consumption results for the motor using the proposed approach (estimated parameters with extended Kalman filter) are compared with those obtained using the conventional approach and energy saving (fixed parameters without parameter estimation) approach. As revealed by the comparison results from implementation in a laboratory, the proposed approach can provide minimum power losses for the three-phase induction motor drive, and the maximum energy-saving percentage is 60.18% compared with using the conventional drive approach.

Optimal voltage angle for maximum torque per voltage control of induction machine in deep field‐weakening region

AbstractThis paper investigates the optimal stator voltage angle in a rotor flux‐oriented system of an induction machine drive, aiming to maximise machine torque while operating in a deep field weakening region. Here, torque maximisation leads to maximum torque per voltage control, as only voltage constraints are relevant in this region due to high back‐electromotive force. Previous studies have predominantly focused on field‐weakening operation and torque maximisation, assuming a constant synchronous speed. However, for a given rotor speed, the variation in thedqvoltage components impacts the slip speed, thereby influencing the synchronous speed. Therefore, this paper proposes enhanced analytical expressions to address this limitation. It is shown that after a linearisation around a suitable operating point, a closed‐form algebraic equation for calculating the speed and parameter‐dependent optimal voltage angle for torque maximisation can be obtained. The theoretical analysis is supported by numerical and experimental results. The presented linearised expression is proven to be an effective tool for the analytical calculation of the optimal voltage angle, making it suitable for real‐time control applications. It is shown that the proposed approach achieves higher drive torque and efficiency than the conventional voltage component distribution.

Switched Reluctance Motor Design and Optimization

In the field of electric vehicle engineering, Switched Reluctance Motors (SRMs) are progressively drawing the attention of developers for their streamlined structural design, superior torque output, economical cost-benefit, and excellent energy efficiency ratios. This paper takes a four-phase 8/6-pole switched reluctance motor as an example, with a rated power of 7.5Kw and a rated speed of 1500r/min. According to the basic design requirements of the SRM, the SRM parameter design flow is designed, and a Matlab calculation program is written for the preliminary calculation of the SRM parameters, and the detailed design of its motor structural parameters is carried out. After that, the stator and rotor pole arc coefficients of the SRM are parametrically analyzed using Maxwell2D tool according to the design experience, and the optimal stator and rotor pole arc coefficients are selected. The simulation results show that the design optimization scheme can effectively reduce the SRM torque pulsation.

Loss model based controller of fuzzy DTC driven induction motor for electric vehicles using optimal stator flux

Adoption of electric vehicles (EVs) is playing a major role in achieving green energy; however, this suffers from energy density range anxiety. Induction motors (IM) are designed to operate most efficiently under rated conditions. However, for EV applications, it operates at partial load at a constant speed, which reduces its efficiency when operated with nominal flux. In the long run, a lot of battery energy is consumed, which increases the running cost of the vehicle. This paper presents an energy efficient motor drive for EV applications with the objective of reducing battery energy consumption by an optimal reference flux. The optimal value of the stator flux reduces the difference between constant and variable losses, which improves the efficiency and driving range of the vehicle. The optimal flux selection strategies used in the current literature are mostly based on a search control approach, which has convergence issues, is highly complex, and is difficult to implement. In this paper, the Teamwork optimization algorithm (TOA) is used for optimal flux selection under a dynamic driving scenario. The method is examined with realistic EV data under various operating conditions and validated using standard drive cycles. The analysis of efficiency, energy savings, and power input confirms the superiority of the proposed method over other existing methods.

Computationally Efficient Predictive Current Control With Finite Set Extension Using Derivative Projection for IM Drives

This article proposes a computationally efficient predictive current control (PCC) combined with an extension of a finite set using current derivative projection, to solve the challenges experienced by finite control set PCC (FCS-PCC), that is, unsatisfied steady-state performance and high computational burden. Since only one switching sequence is utilized in the entire sampling period, FCS-PCC is inevitably penalized by the high torque and current deviations. More specifically, FCS-PCC suffers from the high computational burden caused by the exhaustive search in the optimization stage. To tackle the aforementioned issues, a reformulated objective function using current derivative projection with least-squares (LSs) optimization in PCC is presented in this work. First, PCC is geometrically described as a quadratic programming (QP) problem. To minimize the deviation between the selected and desired current derivative, the objective function is rearranged as the quadratic Euclidean norm of the derivative deviation. The exhaustive search in the optimization stage is avoided by a preselection principle. Based on the above, the optimal stator current derivatives in the consecutive sampling intervals combined with their duty cycles are optimized by the LS method. The effectiveness of the proposed method is verified by the experimental results based on a 2.2-kW IM drive platform.

Teamwork optimization based DTC for enhanced performance of IM based electric vehicle

The tailpipe emissions caused by vehicles using internal combustion engines are a significant source of air pollution. To reduce the health hazards caused by air pollution, advanced countries are now adopting the use of electric vehicles (EVs). Due to the advancement of electric vehicles, research and development efforts are being made to improve the performance of EV motors. With a nominal reference stator flux, the classical induction motor drive generates significant flux, torque ripple, and current harmonics. In this work, a teamwork optimization algorithm (TOA)-based optimal stator flux strategy is suggested for torque ripple reduction applied in a classical direct torque-controlled induction motor drive. The suggested algorithm's responsiveness is investigated under various steady-state and dynamic operating conditions. The proposed DTC-IM drive's simulation results are compared to those of the classical and fuzzy DTC-IM drives. The proposed system has been evaluated and found to reduce torque ripple, flux ripple, current harmonics, and total energy consumption by the motor. Further, a comparative simulation study of the above methods at different standard drive cycles is presented. Experimental verification of the proposed algorithm using OPAL-RT is presented. The results represent the superiority of the proposed algorithm compared to the classical DTC and fuzzy DTC IM drives. The torque ripple reduction approach described in this study can also be applied to all induction motors, not only those for electric vehicles or hybrid electric vehicles (HEVs).

Torque Quality Improvement in Induction Motor for Electric Vehicle Application Based on Teamwork Optimization

The tailpipe emission caused by the vehicles using internal combustion engines is a significant source of air pollution. To reduce the health hazards caused by air pollution, advanced countries are now adopting the use of Electric Vehicles (EVs). Due to the advancement of electric vehicles, research and development efforts are being made to improve the performance of EV motors. With a nominal reference stator flux, the classical induction motor drive generates significant flux, torque ripple, and current harmonics. In this work, a Teamwork Optimization Algorithm (TOA)-based optimal stator flux strategy is suggested for torque ripple reduction applied in a Classical Direct Torque Controlled Induction Motor (CDTC-IM) drive. The suggested algorithm's responsiveness is investigated under various steady-state and dynamic operating conditions. The proposed Direct Torque Controlled Induction Motor (DTC-IM) drive's simulation results are compared to those of the CDTC-IM and Fuzzy Direct Torque Controlled Induction Motor (FDTC-IM) drives. The proposed system has been evaluated and shown to have reduced torque ripple, flux ripple, current harmonics, and total energy consumption by the motor. Further, a comparative simulation study of the above methods at different standard drive cycles is presented. Experimental verification of the proposed algorithm using OPAL-RT is presented. The results represent the superiority of the proposed algorithm compared to the CDTC- and FDTC-IM drive. The torque ripple reduction approach described in this study can also be applied to all types of induction motors, not only those for electric vehicles or Hybrid Electric Vehicles (HEVs).

Derived Functions for MATLAB Non-linear Solvers – an optimal Stator Slot Design Stopgap

In the three-phase squirrel cage induction motor (SCIM), like other rotating electromechanical machines, the active length of the stator windings lies in the slots. The proper dimensioning of the slots is therefore critical to the design of both the windings and the stator core, so as to attain a high performing machine. The preliminary stage of the SCIM design, if well done, facilitates the refinement and optimization stages; serving as a good take-off point for that final state of the art design. The aim of this article isn’t to come up with a novel optimization method for the SCIM, but to provide another way of obtaining an initial stator slot design template, from where proper design refinement/optimization techniques could obtain very good starting values and be facilitated. Therefore, an attempt is being made here to derive relevant design functions that could be fed into the algorithms of various non-linear solvers such as the Genetic Algorithm (GA), to output the main stator slot dimensions for the SCIM. The final designed SCIM obtained from implementing the derived equations, when compared with the appropriate reference datasheets, showed only minor deviations from the expected performance indices – an outcome deemed satisfactory for a preliminary design attempt. These initial dimensions may in practice be subjected to the appropriate refinement. Depending on the target performance requirement of the motor.

Optimal stator adjustment with minimal sensor requirements for variable stator progressing cavity pumps

The classical progressing cavity pump design features constant rotor and stator geometries. Pump efficiency decreases over time due to mechanical wear of the pump components. Variable stator progressing cavity pumps can compensate for mechanical wear up to a certain extent with manual adjustments of the stator geometry. Thus, progressing cavity pump designs with variable stator replace an increasing number of classical pumps. The optimal adjustment of the variable stator is crucial for efficient pump operation. Currently the optimal in-situ stator adjustment requires expensive flow rate measurements and expert knowledge. Consequently many variable stator progressing cavity pumps operate with suboptimal stator configurations. This contribution proposes a novel procedure for adjusting the variable stator of a progressing cavity pump. The procedure only relies on easy-to-acquire process variables and can be implemented on low-cost embedded hardware. A laboratory test setup is used to validate the proposed approach.

Optimal Stator and Rotor Slots Design of Induction Motors for Electric Vehicles Using Opposition-Based Jellyfish Search Optimization

This study presents a hybrid optimization technique to optimize stator and rotor slots of induction motor (IM) design for electric vehicle (EV) applications. The existing meta-heuristic optimization techniques for the IM design, such as genetic algorithm (GA) and particle swarm optimization (PSO), suffer premature convergence, exploration and exploitation imbalance, and computational burden. Therefore, this study proposes a new hybrid optimization technique called opposition-based jellyfish search optimization (OBJSO). This technique adopts opposition-based learning (OBL) into a jellyfish search optimization (JSO). Apart from that, a multi-objective formulation is derived to maximize the main performance indicators of EVs, including efficiency, breakdown torque, and power factor. The proposed OBJSO is used to solve the optimal design of stator and rotor slots based on the formulated multi-objective. The performance is compared with conventional optimization techniques, such as GA, PSO, and JSO. OBJSO outperforms three other optimization techniques in terms of average fitness by 2.2% (GA), 1.3% (PSO), and 0.17% (JSO). Furthermore, the convergence rate of OBJSO is improved tremendously, where up to 13.6% reduction in average can be achieved compared with JSO. In conclusion, the proposed technique can be used to help engineers in the automotive industry design a high-performance IM for EVs as an alternative to the existing motor.

Optimization of Stator Slot Parameters for Electromagnetic Vibration Reduction of Permanent Magnet Synchronous Motors

Slight electromagnetic vibration is one of the crucial indicators that must be considered in the motor design stage. Considering the influence of complex stator slot structure and inevitable saturation at slot opening, a permeance calculation model suitable for the motor with any pole-slot combination is introduced, and the electromagnetic force waves of the motor are calculated quickly and accurately. Considering the orthogonality of stator material and the influence of enclosure and windings, the natural frequencies of the entire stator are analyzed, and the vibration accelerations are calculated by the multiphysics model including control, electromagnetic, structural, and vibration models, the accuracy of the calculation results is verified by the prototype test. Furthermore, the components of electromagnetic force waves that have great impact on electromagnetic vibration are summarized, a weakening method of electromagnetic vibration based on the optimization of the stator slot parameters is proposed, and the optimal stator slot parameters are obtained by the simplified model and the accurate model combining deep neural network (DNN) and immune clone algorithm (ICA), respectively. For the 6-pole 36-slot motor, the vibration accelerations near the six-order natural frequency are greatly reduced by optimizing the stator slot parameters based on the accurate model combining DNN and ICA, and the maximum vibration accelerations are reduced by 34.1% at no load and 36.8% at rated load.

Numerical Investigation of the Effect of Hub Gaps on the 3D Flows Inside the Stator of a Highly Loaded Axial Compressor Stage

Both the compressor performance and the 3D flows inside the stator passage are significantly impacted by the stator hub gap. The interplay between leakage flow and corner separation within a cantilevered stator of a highly loaded, low-speed axial compressor with a succession of stator hub gaps was examined numerically in this paper. Firstly, the simulated results were compared with the measured results, including the compressor characteristics, the 3D flow structures, and the flow fields at the stator outlet. The results revealed that the used CFD solver, as well as the corresponding setup, can reproduce the flow not only in terms of the trend along with the stator hub gap, but also in terms of the specific scale of the 3D flow structure. Hence, it is feasible enough to be applied in the present investigation. Secondly, the flow mechanisms of the interplay between the corner separation and the leakage flow with different stator hub gaps were analyzed. It was found that the velocity of the leakage flow is the key parameter that dominates the flow structures as well as the compressor performance. Additionally, a simple metric was proposed to be used to choose the optimum stator hub gap. By comparing our results with those from published research, this metric was proven to be feasible. Finally, it is also discussed how the stator hub gap affected the stator inlet flow and rotor performance. It is demonstrated that the stator passage flow blockage can affect the upstream flow field. As a result, the performance of the rotor tends to vary in the opposite direction to that of the stator.

Loss minimisation of induction motor-driven electric vehicle using teamwork optimisation

Electric vehicles (EVs) are a feasible alternative to traditional automobiles because of their silent operation and low emissions. Energy optimisation in EVs powered by induction motor (IM) drive is essential for lowering battery current. A loss model-based controller (LMC) is a popular approach that quickly converges to an optimum solution. Some LMC approximations, such as ignoring leakage inductances and iron loss, adversely influence IM drive performance in loss reduction. This work proposes an improved LMC in conjunction with direct torque control (DTC) to address the issue. Here, a parameter-free optimisation algorithm known as the teamwork optimisation algorithm (TOA) is used to select the optimum stator flux for improving IM efficiency. The algorithm is validated using realistic EV data and tested with standard drive cycles. The results demonstrate the improvement in efficiency and the reduction in torque ripple.

Calculation of Rotor Harmonic Losses in Multiphase Induction Machines

The topic of this paper is the determination of rotor harmonic losses in multiphase machines. Specifically, harmonic losses occur in the rotor winding and core due to higher-order spatial harmonics of the flux density. This phenomenon influences machine parameters and overall performance and increases temperature rise in parts of the rotor. The flux density distribution is determined by the stator magnetomotive force harmonic content, which is directly related to the winding distribution. A cage-rotor asymmetrical six-phase induction machine is selected for this case study. An analysis of different stator winding topologies and their influence on harmonic losses is presented. A finite element-based method for calculating the contribution of individual stator magnetomotive force harmonics to the rotor losses is developed and described in the paper. The analysis includes scenarios with different phase current waveforms to emphasize the issues specific to the asymmetrical six-phase machine. It is found that the magnetomotive force components generated by non-torque-producing current components contribute significantly to harmonic losses. The obtained results can represent a foundation for optimal stator winding topology selection. This work is intended to motivate the development of new and the modification of existing models to properly include rotor harmonic losses during the design, performance prediction, and control of multiphase machines.

Influence of Supersonic Nozzle Design Parameters on the Unsteady Stator–Rotor Interaction in Radial-Inflow Turbines for Organic Rankine Cycles

Abstract The use of radial-inflow turbine (RIT) for organic Rankine cycle (ORC) plant sizes below 100 kW is promising, although the application remains challenging. In fact, the single-stage arrangement imposed by economic constraints and hence the large expansion ratio, together with the large molecular weight, which characterizes organic fluids, usually result in highly supersonic flows, so making the use of transonic stators often mandatory. Particularly, the influence of RIT stator design parameters on losses and the level of unsteadiness seen by the subsequent rotor is still scarcely addressed in published literature. The present work investigates the effect of the convergent–divergent stators design parameters and the resulting downstream flow field non-uniformity on the unsteady stator–rotor interaction and loss generation in ORC RIT. To this end, two stator and rotor configurations which differ by the stator design parameters (i.e., discharge metal angle and number of vanes) have been tested by means of three-dimensional (3D) unsteady CFD calculations accounting for real-gas properties. The results show that larger stator–rotor interaction is present for the case featuring higher vane count and lower outlet metal, which also features the largest fluctuations of power output and pressure force on blade, together with a substantially lower average total-to-static efficiency, as a result of a larger stator downstream pitchwise non-uniformity. Ultimately, the results indicate that only aiming for optimal stator efficiency during the stator design phase might lead to highly suboptimal configurations from the whole turbine stage point of view.