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Advanced Electrical Machine and Power Electronics for the Charging and Drive System of Electric Vehicles (EVs)

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Guest Editor
School of Electrical and Information Engineering, The University of Sydney, Camperdown, NSW 2006, Australia
Interests: computational electromagnetics; measurement and modeling of magnetic properties of materials; electrical machines and drives; power electronics; renewable energy systems; smart microgrids; digital energy systems
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Department of Light Sources and Illuminating Engineering, Fudan University, Shanghai, China
Interests: new energy generation and electrical energy storage technology; low-carbon energy intelligent and green technology; large-capacity energy storage system digital technology; power system and information technology intersection

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Guest Editor
Department of Electrical Engineering, Nanjing University of Science and Technology, Nanjing, China
Interests: PM machines and control; electric drive for electric vehicles and hybrid propulsion

Special Issue Information

Dear Colleagues,

Electric vehicles (EVs) are rapidly transforming the automotive landscape, offering sustainable and energy-efficient transportation options. The effectiveness and efficiency of EVs hinge on the design and control of their drive systems, encompassing motors, power electronics, energy management, and integration with other vehicle components. In the realm of electric vehicles, electrical machines have evolved into sophisticated and highly efficient devices designed to meet the demands of modern transportation. These machines play a critical role in converting electrical energy into mechanical power, whether for propelling the vehicle or regenerating energy during deceleration. Power electronics, on the other hand, form the bridge that connects the vehicle to the charging infrastructure and ensures the safe, efficient conversion of electrical energy. They enable fast charging, bidirectional energy flow, and power management, revolutionizing how we charge our EVs and manage energy in the grid. 

This Special Issue seeks to advance the understanding of electric vehicle drive systems, exploring the latest innovations and addressing the challenges. We invite researchers, engineers, and experts in this field to submit their original research, review articles, and insights to foster knowledge exchange and shape the future of electric mobility.

Prof. Dr. Jianguo Zhu
Dr. Yu Wang
Dr. Weiwei Geng
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. World Electric Vehicle Journal is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • new principles and novel topologies of motors for drive systems
  • coupled and intelligent analysis of multi-discipline fields in drive motor systems
  • advanced and data-driven control strategy/analysis for drive and charging systems
  • fault diagnosis and health management of drive/charging systems
  • integration technology for drive/charging system
  • noise and vibration control
  • sustainability and environmental Impact
  • multilevel converters for charging system
  • energy management for V2G systems

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Published Papers (12 papers)

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Research

23 pages, 9774 KiB  
Article
Predictive Torque Control of Permanent Magnet Motor for New-Energy Vehicles Under Low-Carrier-Ratio Conditions
by Zhiqiang Wang, Zhichen Lin, Xuefeng Jin and Yan Yan
World Electr. Veh. J. 2025, 16(3), 146; https://doi.org/10.3390/wevj16030146 - 4 Mar 2025
Viewed by 204
Abstract
The model predictive-torque-control strategy of a permanent magnet synchronous motor (PMSM) has many advantages such as a fast dynamic response and the ease of implementation. However, when the permanent magnet motor has a large number of pole pairs or operates at high-speed, due [...] Read more.
The model predictive-torque-control strategy of a permanent magnet synchronous motor (PMSM) has many advantages such as a fast dynamic response and the ease of implementation. However, when the permanent magnet motor has a large number of pole pairs or operates at high-speed, due to constraints such as the inverter switching frequency, sampling time, and algorithm execution time, the motor carrier ratio (the ratio of control frequency to operating frequency) becomes relatively low. The discrete model derived from and based on the forward Euler method has a large model error when the carrier ratio decreases, which leads to voltage vector misjudgment and inaccurate duty cycle calculation, thus leading to the decline of control performance. Meanwhile, the shortcomings of the traditional model predictive-torque-control strategy limit the steady-state performance. In response to the above issues, this paper proposes an improved model predictive-torque-control strategy suitable for low-carrier-ratio conditions. The strategy consists of an improved discrete model that considers rotor-angle-position variations and a model prediction algorithm. It also analyzes the sensitivity of model predictive control to parameter changes and designs an online parameter optimization algorithm. Compared with the traditional forward Euler method, the improved discrete model proposed in this paper has obvious advantages under low-carrier-ratio conditions; at the same time, the parameter optimization process enhances the parameter robustness of the model prediction algorithm. Moreover, the proposed model predictive-torque-control strategy has high torque tracking accuracy. The experimental results verify the feasibility and effectiveness of the proposed strategy. Full article
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Figure 1
<p>The block diagram of traditional model predictive torque control.</p>
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<p>The block diagram of vector action within a unit carrier period.</p>
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<p>The plot of torque trajectories for different vector combinations.</p>
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<p>The block diagram of the optimal vector action combination.</p>
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<p>The comparison chart of action vectors, three-phase switching states, and torque fluctuations per unit carrier period with the improved sampling and duty cycle update strategy.</p>
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<p>The flow chart of the model reference adaptive-parameter-optimization algorithm.</p>
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<p>General block diagram of the control strategy proposed in this paper.</p>
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<p>The comparison waveforms of the current, stator flux, and torque of the predictive model at low speed.</p>
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<p>The comparison waveforms of the current, stator flux, and torque of the predictive model at medium speed.</p>
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<p>The improved prediction model current, stator flux, and torque waveform at high speed.</p>
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<p>The waveform of parameter optimization link current, stator flux, and torque.</p>
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<p>The comparison of difference in E before and after optimization.</p>
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<p>The current THD analysis of parameter normal, parameter mismatch, and optimization completion.</p>
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<p>The plot of model predictive-torque-control strategy current, stator flux and torque waveforms at low speed.</p>
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<p>The plot of model predictive-torque-control strategy current, stator flux, and torque waveforms at medium speed.</p>
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<p>The plot of model predictive-torque-control strategy current, stator flux and torque waveforms at high speed.</p>
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28 pages, 16912 KiB  
Article
Power Flow and Voltage Control Strategies in Hybrid AC/DC Microgrids for EV Charging and Renewable Integration
by Zaid H. Ali and David Raisz
World Electr. Veh. J. 2025, 16(2), 104; https://doi.org/10.3390/wevj16020104 - 14 Feb 2025
Viewed by 489
Abstract
This study outlines the creation and lab verification of a low-voltage direct current (LVDC) back-to-back (B2B) converter intended as a versatile connection point for low-voltage users. The converter configuration features dual inverters that regulate the power distribution to AC loads and grid connections [...] Read more.
This study outlines the creation and lab verification of a low-voltage direct current (LVDC) back-to-back (B2B) converter intended as a versatile connection point for low-voltage users. The converter configuration features dual inverters that regulate the power distribution to AC loads and grid connections through a shared DC circuit. This arrangement enables the integration of various DC generation sources, such as photovoltaic systems, as well as DC consumers, like electric vehicle chargers, supported by DC/DC converters. Significant advancements include sensorless current estimation for grid-forming inverters, which removes the necessity for conventional current sensors by employing mathematical models and established system parameters. The experimental findings validate the system’s effectiveness in grid-connected and isolated microgrid modes, demonstrating its ability to sustain energy quality and system stability under different conditions. Our results highlight the considerable potential of integrating grid-forming functionalities in inverters to improve microgrid operations. Full article
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<p>Grid-connected microgrid general architecture.</p>
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<p>Modes of power flow.</p>
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<p>EV and storage batteries and bidirectional DC/DC buck–boost converter.</p>
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<p>Battery charge and discharge controller.</p>
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<p>EVB charge and discharge controller.</p>
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<p>HLI control scheme.</p>
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<p>GFM standalone system configuration.</p>
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<p>Mode of operations flowchart.</p>
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<p>Mode one PV to batteries and HLI; various power values for sources and load.</p>
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<p>Mode one solar PV to batteries and HLI grid voltage and current.</p>
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<p>House load voltage and current.</p>
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<p>Mode one solar PV to grid and HLI; various power values for sources and load.</p>
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<p>Grid voltage and current during mode one solar PV to grid and HLI.</p>
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<p>Various power values for sources and load during mode two.</p>
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<p>Grid voltage and current during mode two and three.</p>
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<p>Various power values during mode two when SOC1 is higher than SOC.</p>
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<p>Various power values for sources and load during mode three.</p>
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<p>Imperix system configuration.</p>
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<p>System configuration.</p>
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<p>Only battery connected feeding to the dc-link.</p>
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<p>Excess energy is used to charge the battery.</p>
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<p>Battery and PV feeding into dc-link.</p>
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<p>Unbalanced GFM load.</p>
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<p>Balanced GFM with increased load.</p>
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<p>Increasing GFM voltage and DC-link voltage.</p>
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<p>Cinergia battery and PV emulator monitor.</p>
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<p>Cinergia battery and PV emulator monitor.</p>
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14 pages, 10803 KiB  
Article
Improvement on Electromagnetic Performance of Axial–Radial Flux Type Permanent Magnet Machines by Optimal Stator Slot Number
by Ran Yi, Chunwei Yuan, Hongbo Qiu, Wenhao Gao and Junyi Ren
World Electr. Veh. J. 2024, 15(11), 535; https://doi.org/10.3390/wevj15110535 - 19 Nov 2024
Viewed by 994
Abstract
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 [...] Read more.
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. Full article
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<p>Lateral and front view of the FTRHEM.</p>
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<p>Illustration of flux paths for PMs and axial MMF (<b>a</b>) radial magnetic flux; (<b>b</b>) axial magnetic flux; (<b>c</b>) flux-wakening; and (<b>d</b>) flux-enhancing.</p>
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<p>Schematic diagram of no-load flux linkage waveforms with different axial MMF.</p>
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<p>Winding layouts and phasors of ARFTPM machines (<b>a</b>) 9-slot; (<b>b</b>) 12-slot; and (<b>c</b>) 15-slot.</p>
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<p>The magnetic vector potential paths of ARFTPM machines. (<b>a</b>) 9-slot; (<b>b</b>) 12-slot; and (<b>c</b>) 15-slot.</p>
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<p>The ARFTPM machine meshing and open-circuit flux density distribution (<b>a</b>) 9-slot; (<b>b</b>) 12-slot; and (<b>c</b>) 15-slot.</p>
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<p>The key geometric parameters of ARFTPM machines.</p>
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<p>No-load back-EMFs at 250 r/min with only PM (<b>a</b>) waveforms; (<b>b</b>) spectra.</p>
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<p>Cogging torque waveforms with only PM (<b>a</b>) 9-slot and 12-slot; (<b>b</b>) 15-slot.</p>
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<p>Comparison of torque-angle characteristics.</p>
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<p>Variation in the back-EMF fundamental amplitude at 250 r/min versus axial MMF.</p>
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<p>Variation in the average torque versus axial MMF.</p>
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<p>Machine prototype.</p>
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<p>Experimental testing.</p>
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<p>Measured no-load back-EMF waveforms at 250 r/min with different axial MMF of the 12-slot ARFTPM machines (<b>a</b>) without axial MMF; (<b>b</b>) axial MMF 375 AT; (<b>c</b>) axial MMF 750 AT; and (<b>d</b>) axial MMF 1050 AT.</p>
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14 pages, 5498 KiB  
Article
Influence of Dual Air Gaps on Flux–Torque Regulation Hybrid Excitation Machine with Axial–Radial Magnetic Circuit
by Yong Dai, Yifeng Zheng, Chunwei Yuan, Yuqing Zhang and Hongbo Qiu
World Electr. Veh. J. 2024, 15(9), 430; https://doi.org/10.3390/wevj15090430 - 21 Sep 2024
Viewed by 1052
Abstract
In this paper, a flux–torque regulation hybrid excitation machine (FTRHEM) with axial–radial dual air gaps, which can increase torque and regulate magnetic flux by changing the exciting current, is studied. Dual air gaps have a huge impact on the magnetic flux and additional [...] Read more.
In this paper, a flux–torque regulation hybrid excitation machine (FTRHEM) with axial–radial dual air gaps, which can increase torque and regulate magnetic flux by changing the exciting current, is studied. Dual air gaps have a huge impact on the magnetic flux and additional torque. The effect of the air gap reluctances on the magnetic flux of the machine is obtained by establishing equivalent magnetic network models, which show that the dual air gaps are the key component in the axial–radial magnetic circuit. This study examines the flux regulation ability and the enhanced torque performance of an FTRHEM with dual air gaps. The mechanism by which the dual air gaps affect the machine’s magnetic field is clarified, and the constraints and relationships between the dual air gaps are explained, offering a theoretical foundation for future machine optimization. As the axial air gap decreases from 0.95 mm to 0.35 mm, the flux regulation capability improves from 15.44% to 26.51%, while the additional torque increases by 40.77%. Ultimately, prototypes are manufactured for experimental testing to validate the viability of the structure and the accuracy of the FEA for the FTRHEM featuring an axial–radial magnetic circuit. Full article
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<p>Lateral and front views of the FTRHEM.</p>
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<p>Principle of flux regulation by axial <span class="html-italic">d</span>-axis flux.</p>
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<p>Principle of additional torque generation by axial <span class="html-italic">q</span>-axis flux.</p>
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<p>Air gap equivalent models and dimensions.</p>
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<p>Radial EMF at different radial air gap lengths.</p>
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<p>Axial EMF at different radial air gap lengths.</p>
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<p>Radial EMF at different axial air gap lengths.</p>
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<p>Axial EMF with different axial air gap lengths.</p>
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<p>Flux regulation capability with different radial air gap lengths.</p>
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<p>Flux regulation capability with different axial air gap lengths.</p>
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<p>Additional torque and output torque at different radial air gap lengths.</p>
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<p>Additional torque and output torque at different axial air gap lengths.</p>
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<p>Experimental prototype.</p>
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<p>Machine testing platform.</p>
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<p>EMF waveform in PM-only mode. (<b>a</b>) Measured waveforms. (<b>b</b>) Analysis of results.</p>
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<p>The EMF of the prototype under different excitation currents.</p>
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12 pages, 5791 KiB  
Article
Analysis and Suppression of Spoke-Type Permanent Magnet Machines Cogging Torque with Different Conditions for Electric Vehicles
by Jinlin Huang and Chen Wang
World Electr. Veh. J. 2024, 15(8), 376; https://doi.org/10.3390/wevj15080376 - 19 Aug 2024
Viewed by 888
Abstract
Spoke-type permanent magnet (STPM) machines have high power density and low cost due to flux concentrated effect and high air-gap flux density, but they can cause high cogging torque and torque ripple. To reduce the cogging torque, the analytical model considering a rotor [...] Read more.
Spoke-type permanent magnet (STPM) machines have high power density and low cost due to flux concentrated effect and high air-gap flux density, but they can cause high cogging torque and torque ripple. To reduce the cogging torque, the analytical model considering a rotor slot is established and compared with the finite element mothed (FEM). Then, the cogging torque production mechanism is revealed and analyzed under different conditions, which provides direction to optimize the cogging torque STPM machines. The harmonic content of cogging torque under different conditions is obtained based on the freezing permeability (FP) method. It is found that the fundamental waves mainly generate the cogging torque under a no-load condition, and it is mainly generated by the second harmonics under an on-load condition. In addition, the optimization method is introduced and researched, including rotor slot width, uneven rotor core, and so on. Finally, a 50 kW STPM machine prototype is manufactured and tested to verify the accuracy and efficiency of the analysis method. Full article
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<p>Topology of the STPM machine.</p>
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<p>Cogging torques at no−load with different methods.</p>
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<p>Cogging torque under no−load. (<b>a</b>) Waveform. (<b>b</b>) Harmonic spectrum.</p>
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<p>Cogging torque with on−load. (<b>a</b>) Waveforms. (<b>b</b>) Harmonic.</p>
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<p>Cogging torque versus different rotor slots under no load. (<b>a</b>) Waveform. (<b>b</b>) Harmonic.</p>
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<p>Cogging torque versus different rotor slots under on-load. (<b>a</b>) Waveforms. (<b>b</b>) Harmonic.</p>
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<p>Uneven rotor core structure.</p>
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<p>Cogging torque versus different uneven rotor core distance under no-load. (<b>a</b>) Waveforms. (<b>b</b>) Harmonic.</p>
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<p>Cogging torque versus different uneven rotor core distance under on-load. (<b>a</b>) Waveforms. (<b>b</b>) Harmonic.</p>
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<p>Uneven stator core structure.</p>
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<p>Cogging torque versus different uneven stator core distance under no-load. (<b>a</b>) Waveforms. (<b>b</b>) Harmonic.</p>
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<p>Cogging torque versus different uneven stator core distance under on-load. (<b>a</b>) Waveforms. (<b>b</b>) Harmonic.</p>
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<p>Stator auxiliary slot designs. (<b>a</b>) One auxiliary slot. (<b>b</b>) Two auxiliary slots. (<b>c</b>) Three auxiliary slots. (<b>d</b>) Four auxiliary slots.</p>
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<p>Cogging torque with different auxiliary slots under no−load. (<b>a</b>) Waveform. (<b>b</b>) Harmonics.</p>
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<p>Cogging torques of STPM machine with different auxiliary slots under on−load. (<b>a</b>) Waveform. (<b>b</b>) Harmonics.</p>
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<p>STPM machine with a rotor slot prototype test platform.</p>
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<p>Line back-EMF under 4800 r/min. (<b>a</b>) Waveform. (<b>b</b>) Harmonic spectra.</p>
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<p>Torque versus phase current. (<b>a</b>) Waveforms. (<b>b</b>) Phase current waveform.</p>
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15 pages, 4744 KiB  
Article
Parameter Identification for Fault Analysis of Permanent Magnet Synchronous Motors Based on Transient Processes
by Chaoqiang Wu and Alexander Verl
World Electr. Veh. J. 2024, 15(8), 347; https://doi.org/10.3390/wevj15080347 - 1 Aug 2024
Viewed by 997
Abstract
As the market for hybrid and electric vehicles expands, electric motor production and testing technology must be continuously improved to meet the cost and quality requirements of mass production. In order to detect faults in motors during the production process, a condition monitoring [...] Read more.
As the market for hybrid and electric vehicles expands, electric motor production and testing technology must be continuously improved to meet the cost and quality requirements of mass production. In order to detect faults in motors during the production process, a condition monitoring tool is used for the motor end line. During most condition monitoring, the motor operates in a static state where the speed of the motor remains constant and the voltage/current is recorded for a certain period. This process usually takes a long time and requires a loader to drag the motor to a standstill at a constant speed. In this paper, various transient process testing methods are introduced. For these processes, only transient operation of the motor, such as acceleration, loss, or a short circuit, is required. By analyzing the measurement results and simulation results of motor models, unhealthy motors can be detected more effectively. Full article
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<p>Electromagnetic simulation model.</p>
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<p>Self-inductance and mutual inductance waveforms.</p>
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<p>Waveform diagrams of d-axis inductance and q-axis inductance.</p>
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<p>Transient system modeling flowchart for electric motors.</p>
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<p>Motor fault identification flowchart.</p>
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<p>Working points of a PMSM.</p>
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<p>Typical transient process (<b>a</b>) R–L circuit; (<b>b</b>) voltage pulse; (<b>c</b>) current profile as the step response with the time constant, T.</p>
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<p>Typical transient process (<b>a</b>) R–L circuit; (<b>b</b>) voltage pulse; (<b>c</b>) current profile as the step response with the time constant, T.</p>
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<p>Sub-transient, transient, and steady-state periods.</p>
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<p>Test setup for a sudden short circuit.</p>
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<p>Currents in d–q coordinates for sudden short circuits. (<b>a</b>) Currents in d coordinates; (<b>b</b>) Currents in q coordinates.</p>
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<p>Startup currents in three three-phase systems.</p>
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<p>Currents in the three-phase system for a converter switch.</p>
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<p>Speed and <span class="html-italic">U<sub>A</sub></span>, <span class="html-italic">I<sub>A</sub></span> during the whole acceleration period.</p>
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<p><span class="html-italic">U<sub>d</sub></span>, <span class="html-italic">U<sub>q</sub></span>, <span class="html-italic">I<sub>d,</sub></span> and <span class="html-italic">I<sub>q</sub></span> during the whole acceleration period.</p>
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<p>Speed and voltage <span class="html-italic">U<sub>1</sub></span> during the whole run-down period.</p>
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<p>Speed and voltage <span class="html-italic">U<sub>A</sub></span> in a short run-down period.</p>
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16 pages, 8374 KiB  
Article
Vibration Performance Analysis of a Yokeless Stator Axial Flux PM Motor with Distributed Winding for Electric Vehicle Application
by Xue Yu, Qin Wang, Yu Fu, Hao Chen, Jianfu Zhang and Weiwei Geng
World Electr. Veh. J. 2024, 15(8), 335; https://doi.org/10.3390/wevj15080335 - 26 Jul 2024
Viewed by 1669
Abstract
This article presents a detailed analysis of the electromagnetic force and vibration behavior of a new axial flux permanent magnet (AFPM) machine with a yokeless stator and interior PM rotor. Firstly, the configuration of an AFPM machine with a dual rotor and a [...] Read more.
This article presents a detailed analysis of the electromagnetic force and vibration behavior of a new axial flux permanent magnet (AFPM) machine with a yokeless stator and interior PM rotor. Firstly, the configuration of an AFPM machine with a dual rotor and a sandwiched stator is introduced, including the structural design, fixation of the yokeless stator and segmented skew rotor structure. Then, the influence of anisotropic material and a fixed structure on stator modes is analyzed, including elastic modulus, shear model, the skew angle of slot and the thickness of stator yoke. Furthermore, a new non-equally segmented skew rotor structure is proposed and calculated for the reduction in vibration based on the multiphysics model. Three different segmented skew rotor schemes are compared to illustrate the influence of reducing vibration and noise. The predicted results show that the effect of the non-equally segmented skew rotor on reducing vibration is better than the other two schemes. Finally, a 120 kW AFPM motor is experimented with and the result matches well with the predicted data. The vibration performance of the AFPM motor with a dual rotor and sandwiched yokeless stator is revealed comprehensively. Full article
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<p>Configuration of the proposed AFPM motor. (<b>a</b>) Overall structure. (<b>b</b>) Yokeless stator assembly.</p>
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<p>Influence of material-defined parameters on modes. (<b>a</b>) The impact of <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>x</mi> </msub> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>y</mi> </msub> </mrow> </semantics></math>). (<b>b</b>) The impact of <math display="inline"><semantics> <mrow> <msub> <mi>E</mi> <mi>z</mi> </msub> </mrow> </semantics></math>. (<b>c</b>) The impact of <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mrow> <mi>x</mi> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math>. (<b>d</b>) The impact of <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>The structure and mode of yokeless stator. (<b>a</b>) Yokeless stator core. (<b>b</b>) Zeroth order mode of stator core (298.2 Hz). (<b>c</b>) Yokeless stator with equivalent winding. (<b>d</b>) Zeroth order mode of stator with equivalent winding (287.6 Hz). (<b>e</b>) Yokeless stator with equivalent winding and structural part. (<b>f</b>) Zeroth order mode of stator with equivalent winding and structural part (346 Hz).</p>
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<p>The equivalent winding model structure.</p>
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<p>Influence of stator structure on mode. (<b>a</b>) The influence of skewed slot angle on the mode. (<b>b</b>) Influence of stator yoke thickness on the mode.</p>
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<p>Spatial orders and frequency of axial force. (<b>a</b>) Under no-load. (<b>b</b>) Under load.</p>
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<p>The diagram of continuous skew pole.</p>
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<p>The structure of the rotor of the built-in permanent.</p>
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<p>Influence of skew pole on the electromagnetic torque ripple, cogging torque and output torque.</p>
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<p>Rotor segmented skew pole methods. (<b>a</b>) The rotor is equally divided into segmented skew poles. (<b>b</b>) The rotor is not equally divided into segmented skew poles.</p>
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<p>The diagram of parametric modeling of segmented skew pole.</p>
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<p>Influence of skew pole methods with different angles on torque. (<b>a</b>) Influence on cogging torque. (<b>b</b>) Influence on rated torque.</p>
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<p>Comparison of three kinds of skew rotor. (<b>a</b>) Comparison of acceleration under no load. (<b>b</b>) Comparison of acceleration under load. (<b>c</b>) Comparison of noise under no load. (<b>d</b>) Comparison of noise under load.</p>
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<p>Comparison of experimental components. (<b>a</b>) Stator. (<b>b</b>) Rotor. (<b>c</b>) Complete machine. (<b>d</b>) Experimental bench.</p>
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<p>Measured and simulated line-to-line back-EMF waveforms @3600 r/min.</p>
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<p>Torque/power–speed curves of simulation and experiment.</p>
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<p>Comparison of different speed data. (<b>a</b>) No load. (<b>b</b>) Load.</p>
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<p>Radial vibration acceleration data.</p>
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21 pages, 5003 KiB  
Article
Analytical Calculation of Magnetic Field and Analysis of Rotor Permeability Effects on Permanent Magnet Synchronous Motor with Fractional Slot Concentrated Winding
by Xuandong Wu, Huaiyuan Zhang, Cunxiang Yang and Hongbo Qiu
World Electr. Veh. J. 2024, 15(7), 312; https://doi.org/10.3390/wevj15070312 - 16 Jul 2024
Cited by 1 | Viewed by 1730
Abstract
Accurate calculation of the flux and the magnetic field distribution of fractional slot concentrated winding permanent magnet synchronous motor (FSCW PMSM) is the basis for motor performance analysis, and rapid calculation is key. In this paper, to solve the problem of difficult modeling [...] Read more.
Accurate calculation of the flux and the magnetic field distribution of fractional slot concentrated winding permanent magnet synchronous motor (FSCW PMSM) is the basis for motor performance analysis, and rapid calculation is key. In this paper, to solve the problem of difficult modeling and accuracy guarantee of the flux linkage differential method, a method is proposed to calculate the flux and the no-load back EMF by the slotless subdomain model. By introducing the leakage flux calculation link, the calculation accuracy is improved, the analytical method results are compared with the finite element method results, and the effectiveness of the proposed method is verified. On this basis, the nonlinear variations of the magnetic field and the no-load back EMF with rotor permeability are determined, and the influence mechanism of rotor length and rotor permeability on the main magnetic circuit is revealed. Finally, an experiment of the prototype is carried out, and the correctness and accuracy of the analytical method and the finite element method is verified by comparing with the experimental results. Full article
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<p>Analytical calculation model.</p>
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<p>(<b>a</b>) schematic diagram of the main magnetic leakage flux; (<b>b</b>) magnetic circuits in the numerical calculation model.</p>
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<p>The diagram of the leakage flux circuit: (<b>a</b>) flux leakage is maximum; (<b>b</b>) flux leakage gradually decreases to 0; and (<b>c</b>) flux leakage increases gradually from 0.</p>
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<p>The periodic variation of flux leakage.</p>
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<p>Delectromagnetic field model of the motor.</p>
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<p>Comparison of air gap magnetic flux density waveforms: (<b>a</b>) radial flux density and (<b>b</b>) tangential flux density.</p>
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<p>The magnetic density distribution of the motor at different times: (<b>a</b>) time = 1 s; (<b>b</b>) time = 1.3.</p>
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<p>Effect of rotor core permeability on air gap flux density: (<b>a</b>) fundamental component; (<b>b</b>) third harmonic; (<b>c</b>) fifth harmonic; and (<b>d</b>) THD.</p>
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<p>Effect of rotor core permeability on on-load back EMF.</p>
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<p>Effect of rotor core permeability and thickness on motor performance: (<b>a</b>) flux density fundamental component; (<b>b</b>) no-load back-EMF.</p>
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<p>Experimental test platform.</p>
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<p>Comparison of no-load back-EMF: (<b>a</b>) experimental test; (<b>b</b>) FEM waveforms.</p>
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18 pages, 5451 KiB  
Article
Permanent Magnet Installation Optimization of Outer Rotor PMSM Depending on Adding Auxiliary Teeth
by Jiayin Su, Rui Nie, Peixin Wang, Shuai Xu, Jing Liang and Jikai Si
World Electr. Veh. J. 2024, 15(6), 271; https://doi.org/10.3390/wevj15060271 - 19 Jun 2024
Viewed by 1772
Abstract
To reduce the influence of the permanent magnet (PM) installation error on the electromagnetic characteristics of the outer rotor permanent magnet synchronous motor (OPMSM), the rotor structure of the OPMSM is optimized in this paper. The optimization method of adding auxiliary teeth on [...] Read more.
To reduce the influence of the permanent magnet (PM) installation error on the electromagnetic characteristics of the outer rotor permanent magnet synchronous motor (OPMSM), the rotor structure of the OPMSM is optimized in this paper. The optimization method of adding auxiliary teeth on the surface of the rotor core is studied, and the influence of different auxiliary teeth heights on the electromagnetic performance of OPMSM is analyzed. It is found that adding auxiliary teeth with suitable height can greatly reduce the installation error of the PM, increase the mechanical stability of the motor, and ensure that the electromagnetic characteristics of the motor remain at a good level. Firstly, the topology and parameters of the motor proposed in this paper are introduced and analyzed. Secondly, the influence of PM installation error on the electromagnetic performance of the motor is analyzed based on the finite element method (FEM), and the necessity of eliminating PM installation error is demonstrated. Then, the parametric scanning method is used to analyze the influence of auxiliary teeth height change on the electromagnetic performance of the motor, and the selection standard of the optimal auxiliary teeth height is determined. By comparing and analyzing OPMSM with different sizes and different pole–slot ratios, the universality of the conclusions is demonstrated. Full article
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<p>The structure of OPMSM proposed in this paper.</p>
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<p>The structure of motor rotor with auxiliary teeth.</p>
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<p>PM offset of OPMSM.</p>
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<p>Cogging torque of PM offset and ideal condition.</p>
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<p>Air gap flux density of PM offset and ideal condition. (<b>a</b>) Waveforms; (<b>b</b>) harmonic spectra.</p>
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<p>Torque of PM offset and ideal condition. (<b>a</b>) Waveforms; (<b>b</b>) average torque and torque ripple.</p>
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<p>Back EMF of PM offset and ideal condition. (<b>a</b>) Waveforms; (<b>b</b>) max and rms.</p>
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<p>Rotor auxiliary teeth of OPMSM.</p>
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<p>Electromagnetic torque characteristics of the OPMSM under different rotor teeth heights. (<b>a</b>) Electromagnetic torque waveform; (<b>b</b>) average torque curve; (<b>c</b>) torque ripple curve.</p>
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<p>Air gap flux density under different rotor teeth heights. (<b>a</b>) Waveform; (<b>b</b>) harmonic spectrum.</p>
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<p>Back EMF amplitude and its waveform distortion rate under different rotor teeth heights.</p>
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<p>Eddy current loss of magnetic steel.</p>
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<p>Core loss of the stator core and rotor core.</p>
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<p>Efficiency under different rotor teeth heights.</p>
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<p>Electromagnetic torque waveforms under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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<p>Average torque curve under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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<p>Torque ripple curve under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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<p>Air gap flux density waveforms under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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<p>Air gap flux density harmonic spectrum under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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<p>Back EMF amplitude and their waveform distortion rate under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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<p>Eddy current loss of magnetic steel under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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<p>Core loss of the stator core and rotor core under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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<p>Efficiency under different rotor teeth heights. (<b>a</b>) Type 1; (<b>b</b>) Type 2; (<b>c</b>) Type 3; and (<b>d</b>) Type 4.</p>
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19 pages, 26111 KiB  
Article
Optimization Design of Variable Reluctance Resolver Based on Three-phase Symmetrical Winding
by Xinmin Li, Jiannan Chen and Zhen Zhang
World Electr. Veh. J. 2024, 15(5), 201; https://doi.org/10.3390/wevj15050201 - 6 May 2024
Viewed by 2020
Abstract
In order to ease the structure and manufacturing process of the variable reluctance (VR) resolver, the three-phase symmetrical single-layer winding commonly used in the stator winding of permanent magnet synchronous motors (PMSM) is applied to the VR resolver in this paper. The proposed [...] Read more.
In order to ease the structure and manufacturing process of the variable reluctance (VR) resolver, the three-phase symmetrical single-layer winding commonly used in the stator winding of permanent magnet synchronous motors (PMSM) is applied to the VR resolver in this paper. The proposed resolver has the same winding direction and number of turns on all teeth. And the non-overlapping distribution of the three-phase windings of the resolver is ensured. For this novel resolver, the resolver-to-digital conversion (RDC) method references the ultra-high-frequency (UHF) signal injection method used when a PMSM is powered off and restarted. Instead of the need for the orthogonal envelope RDC required by conventional resolvers, the absolute position of the rotor can be obtained. In this paper, the prototype of the proposed resolver and the peripheral circuits are fabricated and compared with the position detected by the optical encoder, and the validity of the proposed resolver and the accuracy of the RDC are verified by the results of the comparison experiments. Full article
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<p>Structure of a conventional VR (variable reluctance) resolver.</p>
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<p>Equivalent winding model of the conventional VR resolver.</p>
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<p>Output waveforms and envelope of the Conventional resolver.</p>
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<p>Structure of the proposed VR resolver.</p>
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<p>4-X VR resolver.</p>
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<p>Winding distribution of a 4-X VR resolver.</p>
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<p>Simulation model of the proposed resolver.</p>
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<p>Field line distribution of the proposed resolver.</p>
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<p>Flux density map of the proposed resolver.</p>
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<p>Simulated waveforms of three self-inductances of the proposed resolver.</p>
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<p>Simulated waveforms of phase-to-phase mutual inductance of the proposed resolver.</p>
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<p>Equivalent winding model of the proposed resolver.</p>
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<p>Simulation waveform of the B and C output voltage envelopes.</p>
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<p>Simulation waveform of the A and C output voltage envelopes.</p>
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<p>System structure of the resolver-to-digital conversion method.</p>
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<p>Timing sequence of the ultra-high frequency sinusoidal signal injection.</p>
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<p>Experimental system.</p>
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<p>Prototype of the produced resolver.</p>
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<p>Software program flow chart.</p>
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<p>Excitation and output signals and their average values for each phase at 2000 r/min.</p>
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<p>Estimated position, actual position, <span class="html-italic">k</span><sub>1</sub> and demodulation envelope at 300 r/min.</p>
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<p>Estimated position, actual position, <span class="html-italic">k</span><sub>1</sub> and demodulation envelope at 1500 r/min.</p>
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<p>Estimated position, actual position, <span class="html-italic">k</span><sub>1,</sub> and demodulation envelope at 3000 r/min.</p>
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<p>Estimated position, actual position, and rotor position errors of the proposed resolver at 300 r/min.</p>
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<p>Estimated position, actual position, and rotor position errors of the proposed resolver at 1500 r/min.</p>
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<p>Estimated position, actual position, and rotor position errors of the proposed resolver at 3000 r/min.</p>
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21 pages, 4797 KiB  
Article
Sliding Mode Control of an Electric Vehicle Driven by a New Powertrain Technology Based on a Dual-Star Induction Machine
by Basma Benbouya, Hocine Cheghib, Daniela Chrenko, Maria Teresa Delgado, Yanis Hamoudi, Jose Rodriguez and Mohamed Abdelrahem
World Electr. Veh. J. 2024, 15(4), 155; https://doi.org/10.3390/wevj15040155 - 9 Apr 2024
Cited by 2 | Viewed by 2169
Abstract
This article examines a new powertrain system for electric vehicles based on the dual-star induction machine, presented as a promising option due to its significant advantages in terms of performance, energy efficiency, and reliability. This system could play a key role in the [...] Read more.
This article examines a new powertrain system for electric vehicles based on the dual-star induction machine, presented as a promising option due to its significant advantages in terms of performance, energy efficiency, and reliability. This system could play a key role in the evolution of electro-mobility technology. The dual-star induction machine reduces electromagnetic torque fluctuations, limits current harmonics, improves power factor, and enables half-speed operation. Our study focuses on the control strategy and operation of the traction chain for electric vehicles propelled by the dual-star induction machine (DSIM) using Matlab software with version 2017. We integrate the battery as the main energy source, along with three-level static converters for energy conversion in the vehicle’s four operating quadrants. We have opted for sliding mode control, which has proven to be feasible and robust against external disturbances. Although we have modeled driver behavior, we consider it as an aspect of control, to which we add the driving profile to guide our evaluation of the control to be used for vehicle operation. The results of our study demonstrate the reliability and robustness of DSIM for electric vehicle motorization and speed control. Promoting this technology is essential to improve the overall performance and efficiency of electric vehicles, especially in traction and braking modes for energy recovery. This underscores the importance of DSIM in the sustainable development of the electric transportation system. Full article
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<p>Typical driving force components of a vehicle.</p>
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<p>Schematical presentation of the traction chain of an electric vehicle.</p>
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<p>Representation of the machine’s windings.</p>
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<p>Sliding mode control diagram for electric vehicle.</p>
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<p>(<b>a</b>). Simulation results of test 1: Characteristic of the EV. (<b>b</b>). Simulation results of test 1: Characteristic of the battery.</p>
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<p>(<b>a</b>). Simulation results of test 2: Characteristic sizes of the EV. (<b>b</b>). Simulation results of test 2: Characteristic of the battery.</p>
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<p>Power of electric vehicle.</p>
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<p>(<b>a</b>). Simulation results of test 3: Characteristic of the EV. (<b>b</b>). Simulation results of test 3: Characteristic of the battery.</p>
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<p>(<b>a</b>). Simulation results of test 4: Characteristic of the EV. (<b>b</b>). Simulation results of test 4: Characteristic of the battery.</p>
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<p>(<b>a</b>). Simulation results of test 4: Characteristic of the EV. (<b>b</b>). Simulation results of test 4: Characteristic of the battery.</p>
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<p>(<b>a</b>). Simulation results of test 5: Characteristic of the EV. (<b>b</b>). Simulation results of test 5: Characteristic of the battery.</p>
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<p>(<b>a</b>). Simulation results of test 6: Characteristic of the EV. (<b>b</b>). Simulation results of test 6: Characteristic of the battery.</p>
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<p>(<b>a</b>). Simulation results of test 6: Characteristic of the EV. (<b>b</b>). Simulation results of test 6: Characteristic of the battery.</p>
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17 pages, 6709 KiB  
Article
An Open-Circuit Fault Diagnosis System Based on Neural Networks in the Inverter of Three-Phase Permanent Magnet Synchronous Motor (PMSM)
by Kenny Sau Kang Chu, Kuew Wai Chew, Yoong Choon Chang and Stella Morris
World Electr. Veh. J. 2024, 15(2), 71; https://doi.org/10.3390/wevj15020071 - 16 Feb 2024
Viewed by 2202
Abstract
Three-phase motors find extensive applications in various industries. Open-circuit faults are a common occurrence in inverters, and the open-circuit fault diagnosis system plays a crucial role in identifying and addressing these faults to enhance the safety of motor operations. Nevertheless, the current open-circuit [...] Read more.
Three-phase motors find extensive applications in various industries. Open-circuit faults are a common occurrence in inverters, and the open-circuit fault diagnosis system plays a crucial role in identifying and addressing these faults to enhance the safety of motor operations. Nevertheless, the current open-circuit fault diagnosis system faces challenges in precisely detecting specific faulty switches. The proposed work presents a neural network-based open-circuit fault diagnosis system for identifying faulty power switches in inverter-driven motor systems. The system leverages trained phase-to-phase voltage data from the motor to recognize the type and location of faults in each phase with high accuracy. Employing separate neural networks for each of the three phases in a three-phase permanent magnet synchronous motor, the system achieves an outstanding overall fault detection accuracy of approximately 99.8%, with CNN and CNN-LSTM architectures demonstrating superior performance. This work makes two key contributions: (1) implementing neural networks to significantly improve the accuracy of locating faulty switches in open-circuit fault scenarios, and (2) identifying the optimal neural network architecture for effective fault diagnosis within the proposed system. Full article
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<p>Structure of the electrical three-phase inverter.</p>
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<p>Space vector voltages of the three-phase inverter.</p>
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<p>Structure of the switches in one phase.</p>
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<p>Block diagram of proposed OCFDS.</p>
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<p>Experimental Setup of OCFDS.</p>
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<p>Flow diagram of OCFDS program.</p>
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<p>General structure of neural network used in the proposed open-circuit fault diagnosis system.</p>
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<p>Structure of the open-circuit fault diagnosis system (OCFDS)’s neural network.</p>
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<p>Confusion matrix for the performance of CNN1D.</p>
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<p>Confusion matrix for the performance of CNN-LSTM.</p>
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<p>Confusion matrix for the performance of DNN.</p>
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<p>Characteristics of the phase-to-phase voltage, phase current, and deep learning output in one-phase fault conditions (eg: Phase W: high-side gate fault).</p>
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<p>Characteristics of the phase-to-phase voltage, phase current, and deep learning output in two-phase fault conditions (eg: Phase V: high-side gate fault and Phase W: high-side gate fault).</p>
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<p>Characteristics of the phase-to-phase voltage, phase current, and deep learning output in three-phase fault conditions (eg: Phase U: low-side gate fault and Phase V: low and high-side gate fault and Phase W: high-side gate fault).</p>
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