Synchronous Machine Research Articles

Trajectory control strategy for multi-tool synchronous electrochemical machining of blisk channels

The blisk is a core component of an aero-engine, and electrochemical machining (ECM) is the primary method for its manufacture. Among several ECM methods for blisks, multi-tool synchronous machining is the most efficient and advantageous for machining channels. The allowance distribution of the blank after blisk channel machining directly influences the blade profile accuracy. This paper proposes a trajectory control strategy to homogenize the allowance distribution of the blisk channel in multi-tool ECM. The strategy includes the design of the three-dimensional space motion of the tool and blisk, as well as the regulated feed speed. The structural characteristics of the blisk channel and the principle of ECM allow for designing and optimizing the multi-dimensional trajectory. The electric field simulations elucidate the influence law of the three-axis feed speed on the side gap. An algorithm is adopted to iteratively optimize the speeds for different positions to realize multi-dimensional motion control and allowance homogenization. The proposed trajectory control strategy is applied to ECM experiments for the blisk channel. Compared with the constant feed speed mode, the regulated speed strategy reduces the maximum allowance difference between the convex (CV) profiles by 36.18% and that between the concave (CC) profiles by 37.73%. Subsequently, the one-time ECM of eight blisk channels was successfully realized. The average time for a single channel was 12.5 min, significantly improving the machining efficiency. In conclusion, the proposed method is effective and can be extended for synchronously machining various blisk types with twisted channels.

Analysis of adaptive parameter tuning control strategy of VSG

Abstract The traditional virtual synchronous inverter employs constant inertia and damping control, resulting in poor reliability when the system faces disturbances. Consequently, this paper proposes a synchronous virtual machine network control strategy based on adaptive technology. Firstly, the traditional principle is analyzed, followed by an examination of the effects of varying inertia and damping levels on the power grid. Leveraging the power angle characteristic and frequency oscillation characteristic of synchronous generators, an inertia and damping adaptive control strategy is devised. Subsequently, the effectiveness of the strategy is validated through simulation curves generated by a Simlink model.

Designing an Electromagnetic Shield to Protect Rotor Components in Superconducting Synchronous Machines

Designing an Electromagnetic Shield to Protect Rotor Components in Superconducting Synchronous Machines

Optimization of electromagnetic layout for E-machine in electric vehicles: Achieving high performance, efficiency and NVH

The development of electric vehicles (EVs) presents the challenge of optimising electric machines to enhance efficiency, compactness, noise, vibration, harshness (NVH), and affordability, while reducing the dependence on heavy rare-earth materials to reduce the CO2 footprint of electric powertrains. This paper introduces a comprehensive optimization approach for the electromagnetic design of permanent magnet synchronous machines (PMSMs), employing a combination of Design of Experiment (DoE) and Robust Neural Networks (RNN). The optimization framework is utilised to comprehensively address the multiple objectives of an electric machine, including efficiency, noise, vibration, harshness (NVH), and cost. The integration of Artificial Intelligence (AI)-driven modelling has resulted in significant performance improvements, achieving up to 96% total efficiency over the entire load cycle with substantial NVH reductions of up to 20 dB, while reducing the magnet rare earth materials by 35% compared to the baseline. Furthermore, this methodology reduces the simulation time by up to 90%, demonstrating the potential of combining neural network optimization with conventional finite element simulation techniques. The validation of the AI-driven optimization approach with the measurement of the baseline and optimised electric machines for efficiency and vibration is demonstrated for correlation.

An enhanced proportional resonance controller design for the PMSM based electric vehicle drive system

Permanent magnet synchronous machine (PMSM) has proven to be a more economical traction drive system for electric vehicle (EV) applications owing to increased efficiency and high-power density. However, the drive system requires more efficient control schemes to deliver better dynamic performance irrespective of dynamic changes in the motor speed, machine parameters and disturbances. Hence, to tackle the dynamic changes, to enhance the wider operating speed, to achieve precise speed tracking capability, and improved efficiency, a novel control algorithm for the PMSM based EV is proposed in this paper. The control algorithm is implemented by adopting the merits of conventional proportional resonance (PR) and proportional integral (PI) controller. The proposed control strategy is designed with an outer PI speed regulator and the inner enhanced PR (EPR) current regulator. The uniqueness of the proposed EPR controller is that the controller is designed to damp the torsional mode oscillation owing to dynamic changes such as speed and torque regulation evading the additional control loop. The effectiveness of the control scheme is tested in MATLAB Simulink and hardware-in-loop (HIL) real time simulator RT5700. To validate the effectiveness of the proposed control scheme the results are compared with the conventional control schemes. The results presented show that the proposed control technique successfully enhances the static and dynamic performance, and resilience of the EV system. Also, the proposed scheme significantly reduces the flux ripples, torque ripples, current jitter, peak overshoot, undershoot compared to the conventional current controllers.

Trade-off between frequency stability and renewable generation – Studying virtual inertia from solar PV and operating stability constraints

The significant increase in solar PV and wind capacity worldwide has raised growing concerns about power system frequency stability in several countries. One reason for this is that these renewable technologies offer almost no inertial response. However, there are some options available to address this issue. Renewables could now offer virtual inertia. Also, power system operators could impose frequency stability constraints as part of the generation Unit Commitment (UC). These options could potentially have a large impact on renewable generation and hence also on energy costs and system emissions. In this paper, we study two key options improving stability, inertia from solar PV generators supplied by virtual synchronous machines, and frequency stability constraints as part of the UC. We assess N-1 generation contingencies for the interconnected power systems of Chile, Argentina, and Peru. We found that the option of virtual inertia reduces the violation of the RoCoF in hours of high solar generation, without affecting renewable generation. On the other hand, frequency stability constraints ensure non-violation of all stability parameters but reduce renewable generation by 12 %. This reduction increases total operating costs by about 35 %, even when the constraints are combined with virtual inertia and battery support.

Harmonic Sequence Component Model-Based Small-Signal Stability Analysis in Synchronous Machines during Asymmetrical Faults

Power systems are complex and often subject to faults, requiring accurate mathematical models for a thorough analysis. Traditional time-domain models are employed to evaluate the dynamic response of power system elements during transmission system faults. However, only the positive sequence components are considered for unbalanced faults, so the small-signal stability analysis is no longer accurate when assuming balanced conditions for asymmetrical faults. The dynamic phasor approach extends traditional models by representing synchronous machines with harmonic sequence components, making it suitable for an unbalanced condition analysis and revealing dynamic couplings not evident in conventional methods. By modeling electrical and mechanical equations with harmonic sequence components, the study implements an eigenvalue sensitivity analysis and participation factor analysis to identify the variable with significant participation in the critical modes and consequently in the dynamic response of synchronous machines during asymmetric faults, thereby control strategies can be proposed to improve system stability. The article validates the dynamic phasor model through simulations of a single-phase short circuit, demonstrating its accuracy and effectiveness in representing the transient and dynamic behavior of synchronous machines, and correctly identifies the harmonic sequence component with significant participation in the critical modes identified by the eigenvalue sensitivity to the rotor angular velocity and rotor angle.

Mathematical model for calculating steady-state conditions and static characteristics of salient-pole synchronous machines

Salient-pole synchronous machines occupy a paramount position in both the generation and consumption of electrical energy. Recent achievements in the design, manufacturing, and operation of salient-pole synchronous machines are the result of successful advancements in the fields of electromechanical engineering technology, semiconductor technology, and mathematical modeling. To calculate the nominal steady-state operation of salient-pole synchronous machines and their static characteristics (no-load, angular, V-shaped, regulatory, and external), a mathematical model has been developed. Its computer implementation enhances the technical and economic performance of synchronous pole machines. During the creation of the mathematical model, the following assumptions were made: the magnetic field of the machine is conditionally divided into a working field and scattered fields; the magnetic field of the machine is flat and parallel; the magnetic field in the active layer has only a radial component, while in the stator and rotor yokes, only a tangential one; the winding conductors are located in an infinitely thin layer and distributed along the slot according to a harmonic law; losses in the steel are absent. To create the mathematical model of salient-pole synchronous machine, a system of equations for the electrical and magnetic state is formulated. To obtain equations with coefficients independent of the rotor position, the coordinate transformation method (transformation to the dq0 rectangular coordinate system stationary with respect to the rotor) was employed.

High-Performance Position Estimation Method Based on the Error-Corrected State Observer and Its Application on Permanent Magnet Synchronous Machine

High-Performance Position Estimation Method Based on the Error-Corrected State Observer and Its Application on Permanent Magnet Synchronous Machine

Improved MTPA and MTPV Optimal Criteria Analysis Based on IPMSM Nonlinear Flux-Linkage Model

The use of interior permanent-magnet synchronous machines (IPMSMs) is prevalent in automotive and vehicle traction applications due to their high efficiency over a wide speed range. Given the high-power-density requirements of automotive IPMSMs, it is imperative to consider the effect of nonlinearities, such as saturation and cross-coupling, on the motor model. The aforementioned nonlinearities render conventional linear motor models incapable of accurately describing the operating characteristics of the IPMSM, including the maximum torque per ampere (MTPA) trajectory, the flux-weakening (FW) trajectory, and the maximum torque per volt (MTPV) trajectory. With respect to the linear motor model, the nonlinear flux-linkage model is gradually receiving attention from researchers. This modeling method represents the nonlinear behavior of the motor through the direct establishment of a bidirectional mapping relationship between flux-linkage and current. It is capable of naturally incorporating the effects of magnetic saturation and cross-coupling factors. However, the analysis of the current trajectory optimal criteria based on this model has not yet been reported. In this paper, the optimal criteria for the MTPA and MTPV current trajectories are analyzed based on the nonlinear flux-linkage model of IPMSMs. Firstly, the nonlinear flux-linkage model of the tested IPMSM is established by the experimental calibration method. The mathematical analytical expressions of the MTPA and MTPV optimal criteria are then analyzed by constructing and solving optimal problems with different objectives. Finally, the current command table applicable to actual motor control is constructed by calculating the current command for different operating conditions according to the optimal criteria proposed in this paper. The validity and feasibility of the optimal criteria proposed in this paper are verified through experimental tests on different operating conditions.

Dependability Analysis of the Negative-Sequence Turn-to-Turn Fault Protection Schemes for MMC-HVDC Converter Transformers

This paper addresses two complex areas of research: the detection of turn-to-turn faults (TTF) in power transformers and the impact of inverter-based resources on the TTF protection scheme operation. Detecting turn-to-turn faults in power transformers by protection algorithms poses a challenge due to the minimal fault currents observed at transformer terminals. Yet, the demand for dependable TTF protection is very high because of the high fault currents inside the shorted turns and the resulting damage consequences. On the other hand, for such sensitive protection, adverse conditions such as transformer inrush currents or CT errors may lead to protection maloperation. Moreover, the fault current characteristic of the inverter-based source infeed is very different compared to the synchronous machine infeed, particularly concerning the negative-sequence current used in the TTF protection schemes, which calls for thorough research analysis. A simulation model of the converter transformer capable of simulating TTFs, and the Modular Multilevel Converter (MMC) for a High Voltage Direct Current (HVDC) transmission link, has been developed. The test results of turn-to-turn fault protection schemes in inverter-based generation-dominated power systems compared to the synchronous generator infeed are presented. The negative-sequence current protection quantities are analysed in more detail for TTFs with small and large number of shorted turns, i.e. without and with reactive negative-sequence current injection by the MMC control. Finally, the paper assesses the dependability of the transformer differential protection and sensitive TTF protection schemes in detecting faults with different numbers of shorted turns and fault resistance for TTFs occurring in the star and delta winding of the converter transformer.

Predictive control of a series-connected two five-phase synchronous magnet permanent machines

The work presented in this paper focuses on studying the concept of two five-phase permanent magnet synchronous machines connected in series, powered by a single five-arm converter, in order to considerably minimize circulating currents. Firstly, we modeled a system composed of two identical five-phase synchronous machines, whose stator windings are connected in series. This modeling aims to demonstrate that the control of each machine in the group can be independent of the other, even though both machines are powered by a single five-phase converter. Then, we carried out the predictive control of the two five-phase machines connected in series. This control is based on the prediction of future switching states, which are managed via the discrete model of the system. The optimal switching state is obtained according to a predetermined cost function. To demonstrate the features of the presented control algorithm, the results of the simulation conducted using MATLAB/Simulink are presented and discussed to evaluate the performance and efficiency of the independent control of the two five-phase synchronous machines connected in series.

A unified approach to modeling and stability equivalence analysis for grid-forming and grid-following converters

With the increasing penetration of renewable energy generation, the large-scale integration of grid-connected converters, serving as interfaces, has led to the characteristics of a weak grid with low strength and low inertia, resulting in insufficient stability of existing grid-following (GFL) converters. Grid-forming (GFM) converters, by emulating the characteristics of traditional synchronous machines, can operate stably in weak grids, but their introduction creates a complex operational state with mixed modes, presenting unprecedented challenges to the system. To address this, this paper first analyzes the structure and GFM/GFL control strategies of grid-connected converters; based on this, a comprehensive model framework for GFM/GFL converters is established, and the control of the converters is divided into three parts: LCL with the grid, output control, and power control, each modeled with a small-signal approach; using the established small-signal models, the stability of GFM/GFL converters under different grid short circuit ratios (SCR) is analyzed. Finally, a 20 kW test platform was constructed, and the correctness of the modeling and analysis was jointly verified using simulation frequency sweep methods and experimental time-domain stability analysis techniques.

Detection of Demagnetization Faults in Electric Motors by Analyzing Inverter Based Current Data Using Machine Learning Techniques

Demagnetization of the rotor magnets is a significant failure mode that can occur in permanent magnet synchronous machines (PMSMs). Early detection of demagnetization faults can help change system parameters to reduce power output or ensure safety. In this paper, the effects of demagnetization faults were analyzed both in simulation and experiments using the example of drone motors. An approach was investigated to detect even minor demagnetization faults that does not require any additional sensing effort. Machine learning (ML) techniques are used to analyze the phase current data directly received from the inverter to enable anomaly detection. For this purpose, the phase current is transformed by the Fast Fourier Transform (FFT), the spectral data is then reduced in dimensionality, followed by an anomaly detection algorithm using a one-class support vector machine (OC-SVM). To ensure simplified initialization of the ML model without the need for training sets of damaged drives, only data from magnetically undamaged motors was used to train the models for anomaly detection. Different selections of considered harmonics and different metrics were investigated using the experimental data, achieving a precision of up to 99%, a specificity of up to 98%, and an accuracy of up to 90%.

Optimization of a damper system for noise and vibration reduction in a PMSM

PurposeThis paper aims to optimize passive damper system (PDS) design by configuring its parameters to improve its performance and behavior in permanent magnet synchronous machines (PMSM).Design/methodology/approachFirst, the principle and effectiveness of the PDS are recalled. Second, the impact of different PDS parameters on its operation is analyzed. Third, a multi-objective optimization is proposed to explore a compromise design of PDS. Finally, the transient finite element method simulation is performed to validate the optimized design, which can ensure an excellent noise reduction effect and weaker negative impacts.FindingsA suitable capacitance value in PDS is a key to realizing the damping effect. A larger copper wire can improve the noise reduction performance of PDS and reduce its Joule losses. A compromise solution obtained from a multi-objective optimization remains the excellent noise reduction and reduces Joule losses.Originality/valueThis paper explores the impact of PDS parameters on its operation and provides an orientation of PDS optimization, which is favorable to extend its application in different electrical machines.

Numerical and analytical calculation of the rotor mechanical stresses of a synchronous electricfl machine with incorporated permanent magnets

Numerical and analytical calculation of the rotor mechanical stresses of a synchronous electricfl machine with incorporated permanent magnets

Frequency stability of new energy power systems based on VSG adaptive energy storage coordinated control strategy

A self-adaptive energy storage coordination control strategy based on virtual synchronous machine technology was studied and designed to address the oscillation problem caused by new energy units. By simulating the characteristics of synchronous generators, the inertia level of the new energy power system was enhanced, and frequency stability optimization was achieved. This strategy is integrated with the frequency response model of the new energy power system to improve the system's frequency regulation capability and achieve more stable and efficient operation. From the results, the damping of the system increased, the oscillation frequency decreased after a duration of about 15 s, and the system stability improved by 76.09%. The proposed strategy based on virtual synchronous generator adaptive energy storage coordination control strategy was improved by 83.25%. In addition, the proposed strategy has improved stability indicators and system completion efficiency by 40.57% and 22.21% respectively, both of which are better than the comparative strategies. As a result, this strategy significantly enhances the frequency regulation capability of the system, which has a positive effect on achieving efficient operation of the new energy power system and maintaining the stability of the power system.

Multimaterial filtering applied to the topology optimization of a permanent magnet synchronous machine

PurposeThis study aims to propose a general methodology to handle multimaterial filtering for density-based topology optimization containing periodic or antiperiodic boundary conditions, which are expected to reduce the simulation time of electrical machines. The optimization of the material distribution in a permanent magnet synchronous machine rotor illustrates the relevance of this approach.Design/methodology/approachThe optimization algorithm relies on an augmented Lagrangian with a projected gradient descent. The 2D finite element method computes the physical and adjoint states to evaluate the objective function and its sensitivities. Concerning regularization, a mathematical development leads to a multimaterial convolution filtering methodology that is consistent with the boundary conditions and helps eliminate artifacts.FindingsThe method behaves as expected and shows the superiority of multimaterial topology optimization over bimaterial topology optimization for the chosen test case. Unlike the standard approach that uses a cropped convolution kernel, the proposed methodology does not artificially reflect the limits of the simulation domain in the optimized material distribution.Originality/valueAlthough filtering is a standard tool in topology optimization, no attention has previously been paid to the influence of periodic or antiperiodic boundary conditions when dealing with different natures of materials. The comparison between the bimaterial and multimaterial topology optimization of a permanent magnet machine rotor without symmetry constraints constitutes another originality of this work.

Analysis of Parameter Sensitivity to Overvoltage under DC Commutation Failure

Abstract In recent years, the growing integration of renewable energy sources into power systems has highlighted the significance of enhancing the grid’s capacity to accommodate these resources efficiently. Direct Current (DC) transmission stands out as a pivotal solution to bolster the integration of renewable energy. This study delves into the critical issue of overvoltage occurrences at the sending end, particularly triggered by failures in DC commutation. Through the development of a comprehensive PSCAD electromagnetic simulation model encompassing synchronous machines, centralized renewable energy sources, along with DC components, the research rigorously investigates the intricacies of DC commutation failures. Specifically, it explores their underlying mechanisms responsible for inducing overvoltage at the sending end. Furthermore, the paper undertakes an extensive analysis of the voltage dynamic processes and their associated sensitivity factors, shedding light on crucial aspects of grid stability and resilience in the face of evolving energy landscapes.

Investigation of a novel intensifying-flux hybrid excited permanent magnet machine for electric vehicles

PurposeTo address the issues of the insufficient output torque associated with the application of intensifying-flux permanent magnet (PM) machines in electric vehicles, this paper aims to propose an intensifying-flux hybrid excitation PM machine. It is possible to adjust the air gap magnetic field by adjusting the field current in the excitation winding, thereby increasing the torque output capability and speed range of the machine.Design/methodology/approachFirst, a novel intensifying-flux hybrid excited permanent magnet synchronous machine (IF-HEPMSM) is proposed on the basis of intensifying-flux permanent magnet synchronous machine (IF-PMSM) and an equivalent magnetic circuit model is established. Second, the tooth width and yoke thickness of the machine stator are optimized to ensure the overload capacity of the machine while effectively improving the wide flux regulation range. Furthermore, the electromagnetic characteristics of the IF-HEPMSM are investigated and compared with the IF-PMSM and conventional permanent magnet synchronous machine (PMSM) by using finite element simulations.FindingsThe id of IF-HEPMSM and IF-PMSM is greater than zero low-speed magnetizing current. And the flux-weakening current of the IF-HEPMSM is 18% and 3% smaller than of the conventional PMSM and IF-PMSM.Practical implicationsAiming at the problems of IF-PMSM applied to electric vehicles, this paper proposes an IF-HEPMSM. The air gap magnetic field is adjusted by controlling the current of the excitation winding to improve the reliability of the machine. Therefore, the IF-HEPMSM combines the advantages of high-power density and high efficiency of the PMSM and the controllable magnetic field of the electro-excitation machine, which is of great engineering value when applied in the field of electric vehicles.Originality/valueThe proposed IF-HEPMSM offers better flux regulation capability with electromagnetic characteristics analysis and maps of dq-axis current as compared to IF-PMSM and conventional PMSM. Moreover, the improvement of the torque can make up for the shortcomings of the insufficient torque output capability of the IF-PMSM.