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Abstract

This paper considers the feasibility of different technologies for an electromagnetic launcher to assist civil aircraft take-off. This method is investigated to reduce the power required from the engines during initial acceleration. Assisted launch has the potential of reducing the required runway length, reducing noise near airports and improving overall aircraft efficiency through reducing engine thrust requirements. The research compares two possible linear motor topologies which may be efficaciously used for this application. The comparison is made on results from both analytical and finite element analysis (FEA).

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Authors and Affiliations

Luca Bertola
Tom Cox
Patrick Wheeler
Seamus Garvey
Herve Morvan
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Abstract

In this paper, a creative dung beetle optimization (CDBO) algorithm is proposed and applied to the offline parameter identification of permanent magnet synchronous motors. First, in order to uniformly initialize the population state and increase the population diversity, a strategy to improve the initialization of the dung beetle population using Singer chaotic mapping is proposed to improve the global search performance; second, in order to improve the local search performance and enhance the convergence accuracy of the algorithm, a new dung beetle position update strategy is designed to increase the spatial search range of the algorithm. Simulation results show that the proposed optimization algorithm can quickly and accurately identify parameters such as resistance, inductance, and magnetic chain of the PMSM, with significant improvements in convergence algebra, identification accuracy and stability.
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Authors and Affiliations

Xiaoliang Yang
1 2
ORCID: ORCID
Yuyue Cui
1 2
Lianhua Jia
3
Zhihong Sun
3
Peng Zhang
3
ORCID: ORCID
Jiane Zhao
4
Rui Wang
1 2
ORCID: ORCID

  1. School of Electrical and Information Engineer, Zhengzhou University of Light Industry, Zhengzhou, China
  2. Henan Key Lab of Information based Electrical Appliances, Zhengzhou, China
  3. China Railway Engineering Equipment Group Co. Ltd, Zhengzhou, China
  4. School of Electrical and Electronic Engineering, Zhengzhou University of Science and Technology, Zhengzhou, China
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Abstract

The aim of the studywas to find an effective method of ripple torque compensation for a direct drive with a permanent magnet synchronous motor (PMSM) without time-consuming drive identification. The main objective of the research on the development of a methodology for the proper teaching a neural network was achieved by the use of iterative learning control (ILC), correct estimation of torque and spline interpolation. The paper presents the structure of the drive system and the method of its tuning in order to reduce the torque ripple, which has a significant effect on the uneven speed of the servo drive. The proposed structure of the PMSM in the dq axis is equipped with a neural compensator. The introduced iterative learning control was based on the estimation of the ripple torque and spline interpolation. The structurewas analyzed and verified by simulation and experimental tests. The elaborated structure of the drive system and method of its tuning can be easily used by applying a microprocessor system available now on the market. The proposed control solution can be made without time-consuming drive identification, which can have a great practical advantage. The article presents a new approach to proper neural network training in cooperation with iterative learning for repetitive motion systems without time-consuming identification of the motor.

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Authors and Affiliations

Adrian Wójcik
Tomasz Pajchrowski
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Abstract

The artificial bee colony (ABC) intelligence algorithm is widely applied to solve multi-variable function optimization problems. In order to accurately identify the parameters of the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes an improved ABC optimization method based on vector control to solve the multi-parameter identification problem of the PMSM. Because of the shortcomings of the existing parameter identification algorithms, such as high computational complexity and data saturation, the ABC algorithm is applied for the multi-parameter identification of the PMSM for the first time. In order to further improve the search speed of the ABC algorithm and avoid falling into the local optimum, Euclidean distance is introduced into the ABC algorithm to search more efficiently in the feasible region. Applying the improved algorithm to multi-parameter identification of the PMSM, this method only needs to sample the stator current and voltage signals of the motor. Combined with the fitness function, the online identification of the PMSM can be achieved. The simulation and experimental results show that the ABC algorithm can quickly identify the motor stator resistance, inductance and flux linkage. In addition, the ABC algorithm improved by Euclidean distance has faster convergence speed and smaller steady-state error for the identification results of stator resistance, inductance and flux linkage.
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Bibliography

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[11] Liu Z., Wei H., Li X., Global identification of electrical and mechanical parameters in PMSM drive based on dynamic self-learning PSO, IEEE Transactions on Power Electronics, vol. 33, no. 12, pp. 10858–10871 (2018), DOI: 10.1109/TPEL.2018.2801331.
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[19] Zawilak T., Influence of rotor’s cage resistance on demagnetization process in the line start permanent magnet synchronous motor, Archives of Electrical Engineering, vol. 69, no. 2, pp. 249–258 (2020), DOI: 10.24425/aee.2020.133023.

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Authors and Affiliations

Chunli Wu
1
ORCID: ORCID
Shuai Jiang
1
Chunyuan Bian
1

  1. College of Information Science and Engineering, Northeastern University, China
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Abstract

The paper presents a method of determining the efficiency of the slewing drive system applied in tower cranes. An algorithm for the proper selection of a permanent magnet synchronous motor (PMSM) for crane applications is presented. In the first stage of our research the proper PMSM was proposed on the basis of the simulation calculation. Next, the PM motor was examined on a special test bench. The experimental setup allows determining major electrical and mechanical parameters of the motor drive system. The applied slewing system consists of: an inverter, gear, cable drum and a permanent magnet motor. The performance and efficiency of the system were experimentally determined. Selected results of the experimental measurement are presented and discussed.
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Bibliography

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[6] Torrent M., Perat J.I., Jimenez J.A., Permanent magnet synchronous motor with different rotor structures for traction motor in high speed trains, Energies, vol. 11, no. 1549, pp. 1–17 (2018).
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[8] Zawilak T., Influence of rotor’s cage resistance on demagnetization process in the line start permanent magnet synchronous motor, Archives of Electrical Engineering, vol. 69, no. 2, pp. 249–258 (2020).
[9] Knypinski Ł., Pawełoszek K., Le Manech Y., Optimization of low-power line-start PM motor using gray wolf metaheuristic algorithm, Energies, vol. 13, no. 5, pp. 1–11 (2020).
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Authors and Affiliations

Łukasz Knypiński
1
ORCID: ORCID
Jacek Krupiński
2

  1. Poznan University of Technology, Poland
  2. Krupinski Cranes, Poland
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Abstract

The popularity of high-efficiency permanent magnet synchronous motors in drive systems has continued to grow in recent years. Therefore, also the detection of their faults is becoming a very important issue. The most common fault of this type of motor is the stator winding fault. Due to the destructive character of this failure, it is necessary to use fault diagnostic methods that facilitate damage detection in its early stages. This paper presents the effectiveness of spectral and bispectrum analysis application for the detection of stator winding faults in permanent magnet synchronous motors. The analyzed diagnostic signals are stator phase current, stator phase current envelope, and stator phase current space vector module. The proposed solution is experimentally verified during various motor operating conditions. The object of the experimental verification was a 2.5 kW permanent magnet synchronous motor, the construction of which was specially prepared to facilitate inter-turn short circuits modelling. The application of bispectrum analysis discussed so far in the literature has been limited to vibration signals and detecting mechanical damages. There are no papers in the field of motor diagnostic dealing with the bispectrum analysis for stator winding fault detection, especially based on stator phase current signal.
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Authors and Affiliations

Przemysław Pietrzak
1
ORCID: ORCID
Marcin Wolkiewicz
1
ORCID: ORCID

  1. Wrocław University of Science and Technology, Department of Electrical Machines, Drives and Measurements, Wybrzeze Wyspia ˙ nskiego 27, ´ 50-370 Wrocław, Poland
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Abstract

The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
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Authors and Affiliations

Łukasz Knypiński
1
ORCID: ORCID

  1. Poznan University of Technology, Institute of Electrical Engineering and Electronics, Piotrowo 3a, 60-965 Poznan, Poland
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Abstract

In recent years there has been an increasing demand for electric vehicles due to their attractive features including low pollution and increase in efficiency. Electric vehicles use electric motors as primary motion elements and permanent magnet machines found a proven record of use in electric vehicles. Permanent magnet synchronous motor (PMSM) as electric propulsion in electric vehicles supersedes the performance compared to other motor types. However, in order to eliminate the cumbersome mechanical sensors used for feedback, sensorless control of motors has been proposed. This paper proposes the design of sliding mode observer (SMO) based on Lyapunov stability for sensorless control of PMSM. The designed observer is modeled with a simulated PMSM model to evaluate the tracking efficiency of the observer. Further, the SMO is coded using MATLAB/Xilinx block models to investigate the performance at real-time.
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Authors and Affiliations

Soundirarajan Navaneethan
1
Srinivasan Kanthalakshmi
2
S. Aandrew Baggio

  1. Department of Instrumentation and Control Systems Engineering, PSG College of Technology, Coimbatore, 641004, Tamilnadu, India
  2. Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore, 641004, Tamilnadu, India
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Abstract

The traditional industrial robots come with the prime mover, i.e. Electric Motors (EM) which ranges from a few hundred too few kilo watts of power ratings. However, for autonomous robotic navigation systems, we require motors which are light weighted with the aspect of high torque and power density. This aspect is very critical, when the EMs in robotic navigations are subjected to harsh high temperature survival conditions, where the sustainability of the performance metrics of the electromagnetic system of the EMs degrade with the prevailing high temperature conditions. Hence, this research work address and formulate the design methodology to develop a 630 W High Temperature PMSM (HTPMSM) in the aspect of high torque and power density, which can be used for the autonomous robotic navigation systems under high temperature survival conditions of 200°C. Two types of rotor configurations i.e. the Surface Permanent Magnet type (SPM) and the Interior Permanent Magnet type (IPM) of HTPMSM are examined for its optimal electromagnetic metrics under the temperature conditions of 200°C. The 630 W HTPMSM is designed to deliver the rated torque of 2 Nm within the volumetric & diametric constraints of D x L which comes at 80 x 70 mm at the rated speed of 3000 rpm with the survival temperature of 200°C with the target efficiency of greater than 90%. The FEM based results are validated through the hardware prototypes for both SPM and IPM types, and the results confirm the effectiveness of the proposed design methodology of HTPMSM for sustainable autonomous robotic navigation applications.
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Authors and Affiliations

M Anand
M Sundaram
P Sivakumar
A Angamuthu
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Abstract

Efficiency, reliability, and durability play a key role in modern drive systems in line with the Industry 4.0 paradigm and the sustainability trend. To ensure this, highly efficient motors and appropriate systems must be deployed to monitor their condition and diagnose faults during the operation. For these reasons, in recent years, more and more research has been focused on developing new methods for fault diagnosis of permanent magnet synchronous motors (PMSMs). This paper proposes a novel hybrid method for the automatic detection and classification of PMSM stator winding faults based on combining the continuous wavelet transform (CWT) analysis of the negative sequence component of the stator phase currents with a convolutional neural network (CNN). CWT scalogram images are used as the inputs of the CNN-based interturn short circuits fault classifier model. Experimental tests were carried out to verify the effectiveness of the proposed approach under various motor operating conditions and at an incipient stage of fault propagation. In addition, the effects of the input image format, CNN structure, and training process parameters on model accuracy and classification effectiveness were investigated. The results of the experimental tests confirmed the high effectiveness of fault detection (99.4%) and classification (97.5%), as well as other important advantages of the developed method.
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Authors and Affiliations

P. Pietrzak
M. Wolkiewicz
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Abstract

In this paper, a voltage control system for a PMSM motor based on the QZSDMC converter is proposed, which allows operation in both buck and boost modes as a possible method to make the drive resistant to power grid voltage sags. The authors presented a method for measuring and transforming the output voltage from QZS, enabling the use of a PI controller to control the voltage supplied to the DMC converter. The publication includes simulation and experimental studies comparing the operation of a PMSM motor powered by DMC and the proposed QZSDMC with voltage regulation. Simulation studies confirm the drive with QZSDMC resistance to voltage sags up to 80% of the rated value. Experimental studies demonstrate the correct operation of PMSM even with a power grid voltage amplitude equal to 40% of the rated value.
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Authors and Affiliations

Przemysław Siwek
Konrad Urbański
ORCID: ORCID
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Abstract

The synchronisation of a complex chaotic network of permanent magnet synchronous motor systems has increasing practical importance in the field of electrical engineering. This article presents the control design method for the hybrid synchronization and parameter estimation of ring-connected complex chaotic network of permanent magnet synchronous motor systems. The design of the desired control law is a challenging task for control engineers due to parametric uncertainties and chaotic responses to some specific parameter values. Controllers are designed based on the adaptive integral sliding mode control to ensure hybrid synchronization and estimation of uncertain terms. To apply the adaptive ISMC, firstly the error system is converted to a unique system consisting of a nominal part along with the unknown terms which are computed adaptively. The stabilizing controller incorporating nominal control and compensator control is designed for the error system. The compensator controller, as well as the adopted laws, are designed to get the first derivative of the Lyapunov equation strictly negative. To give an illustration, the proposed technique is applied to 4-coupled motor systems yielding the convergence of error dynamics to zero, estimation of uncertain parameters, and hybrid synchronization of system states. The usefulness of the proposed method has also been tested through computer simulations and found to be valid.
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Authors and Affiliations

Nazam Siddique
1
ORCID: ORCID
Fazal U. Rehman
1

  1. Capital University of Science and Technology, Islamabad Expressway, Kahuta Road, Zone-V Islamabad, Pakistan
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Abstract

Inter-turn short circuit (ITSC) is a frequent fault of interior permanent magnet synchronous motors (IPMSM). If ITSC faults are not promptly monitored, it may result in secondary faults or even cause extensive damage to the entire motor. To enhance the reliability of IPMSMs, this paper introduces a fault diagnosis method specifically designed for identifying ITSC faults in IPMSMs. The sparse coefficients of phase current and torque are solved by clustering shrinkage stage orthogonal matching tracking (CcStOMP) in the greedy tracking algorithm.The CcStOMP algorithm can extract multiple target atoms at one time, which greatly improves the iterative efficiency. The multiple features are utilized as input parameters for constructing the random forest classifier. The constructed random forest model is used to diagnose ITSC faults with the results showing that the random forest model has a diagnostic accuracy of 98.61% using all features, and the diagnostic accuracy of selecting three of the most important features is still as high as 97.91%. The random forest classification model has excellent robustness that maintains high classification accuracy despite the reduction of feature vectors, which is a great advantage compared to other classification algorithms. The combination of greedy tracing and the random forest is not only a fast diagnostic model but also a model with good generalisation and anti-interference capability. This non-invasive method is applicable to monitoring and detecting failures in industrial PMSMs.
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Authors and Affiliations

Jianping Wang
1
Jian Ma
1
ORCID: ORCID
Dean Meng
1
Xuan Zhao
1
Kai Zhang
1
Qiquan Liu
1
Kejie Xu
1

  1. School of Automobile, Chang’an University, Xi’an 710064, China

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