A Flux-Controllable NI HTS Flux-Switching Machine for Electric Vehicle Applications

2020 ◽  
Vol 10 (5) ◽  
pp. 1564 ◽  
Author(s):  
Young Jin Hwang ◽  
Jae Young Jang ◽  
SangGap Lee
Keyword(s):  
Electric Vehicle ◽  
Large Scale ◽  
Rotating Machines ◽  
Field Coil ◽  
Rotating Machine ◽  
Operating Stability ◽  
Electric Aircraft ◽  
Switching Structure ◽  
Constant Output ◽  
Characteristic Resistance

This paper deals with a flux-controllable NI HTS flux-switching machine (FSM) for electric vehicle (EV) applications. In a variable-speed rotating machine for EVs, such as electric buses, electric aircraft and electric ships, an electric motor capable of regulating the flux offers the advantage of constant output operation. In general, conventional HTS rotating machines have excellent flux-regulation performance, because they excite an HTS field coil. However, it is difficult to ensure any flux-regulation capabilities in HTS rotating machines using HTS field coils that apply the no-insulation (NI) winding technique, due to the inherent charge and discharge delays in these machines. Nevertheless, the NI winding technique is being actively researched as a key technology for the successful development of HTS rotating machines, because it can dramatically improve the operational stability of HTS field coils. Therefore, research to implement an HTS rotating machine with flux-regulation capabilities, while improving the operating stability of the HTS field coil using the NI winding technique, is required for EV applications. In this paper, we propose an HTS rotating machine with a flux switching structure, a type of topology of a rotating machine that is being actively studied for application to the electric motors used in EVs. The proposed HTS flux-switching machine (FSM) uses NI field coils, but additional field windings are applied for flux regulation, which enables flux control. In this study, an NI HTS field coil was also fabricated and tested because the characteristic resistance value should be used for the design and characteristic analyses of machines which utilize an NI coil. The simulation model used to analyze the flux-regulation performance capabilities of the NI HTS FSM were devised based on the characteristic resistance values obtained from a charging test of the fabricated NI HTS field coil. This study can provide a good reference for further research, including work on the manufacturing of a prototype NI HTS FSM for EV applications, and it can be used as a reference for the development of other HTS rotating machines, such as those used in large-scale wind power generation, where flux-regulation capabilities are required.

Effects of the Shaft Normal Modes on the Model-Based Identification of Unbalances in Rotating Machines

2011 ◽  
Author(s):  
A. Vania ◽  
P. Pennacchi ◽  
S. Chatterton
Keyword(s):  
Normal Modes ◽  
Fault Identification ◽  
Diagnostic Strategy ◽  
Rotating Machines ◽  
Large Power ◽  
Identification Methods ◽  
Model Based ◽  
Rotating Machine ◽  
Experimental Response ◽  
Innovative Techniques

Model-based methods can be applied to identify the most likely faults that cause the experimental response of a rotating machine. Sometimes, the objective function, to be minimized in the fault identification method, shows multiple sufficiently low values that are associated with different sets of the equivalent excitations by means of which the fault can be modeled. In these cases, the knowledge of the contribution of each normal mode of interest to the vibration predicted at each measurement point can provide useful information to identify the actual fault. In this paper, the capabilities of an original diagnostic strategy that combines the use of common fault identification methods with innovative techniques based on a modal representation of the dynamic behavior of rotating machines is shown. This investigation approach has been successfully validated by means of the analysis of the abnormal vibrations of a large power unit.

A simulative framework for a multi-regional assessment of local energy markets – A case of large-scale electric vehicle deployment in Germany

2021 ◽  
Vol 299 ◽  
pp. 117249
Author(s):  
Wilhelm Cramer ◽  
Klemens Schumann ◽  
Michael Andres ◽  
Chris Vertgewall ◽  
Antonello Monti ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Large Scale ◽  
Energy Markets ◽  
Local Energy ◽  
Regional Assessment

scholarly journals Sustainable Electric Vehicle Transportation

2021 ◽  
Vol 13 (22) ◽  
pp. 12379
Author(s):  
Raymond Kene ◽  
Thomas Olwal ◽  
Barend J. van Wyk
Keyword(s):  
Electric Vehicle ◽  
Energy Demand ◽  
Large Scale ◽  
Common Knowledge ◽  
Distribution Network ◽  
Electricity Grid ◽  
Current State ◽  
The World ◽  
The Impact ◽  
Ev Charging

The future direction of electric vehicle (EV) transportation in relation to the energy demand for charging EVs needs a more sustainable roadmap, compared to the current reliance on the centralised electricity grid system. It is common knowledge that the current state of electricity grids in the biggest economies of the world today suffer a perennial problem of power losses; and were not designed for the uptake and integration of the growing number of large-scale EV charging power demands from the grids. To promote sustainable EV transportation, this study aims to review the current state of research and development around this field. This study is significant to the effect that it accomplishes four major objectives. (1) First, the implication of large-scale EV integration to the electricity grid is assessed by looking at the impact on the distribution network. (2) Secondly, it provides energy management strategies for optimizing plug-in EVs load demand on the electricity distribution network. (3) It provides a clear direction and an overview on sustainable EV charging infrastructure, which is highlighted as one of the key factors that enables the promotion and sustainability of the EV market and transportation sector, re-engineered to support the United Nations Climate Change Agenda. Finally, a conclusion is made with some policy recommendations provided for the promotion of the electric vehicle market and widespread adoption in any economy of the world.

Load Forecasting of Charging and Swapping in Large-Scale Electric Vehicle

2014 ◽  
Vol 568-570 ◽  
pp. 1969-1977 ◽  
Author(s):  
Jian Cheng Ye ◽  
Yu Ling Li ◽  
Dong Liang Zhang ◽  
Xiang Jing Zhu ◽  
Jin Da Zhu
Keyword(s):  
Electric Vehicle ◽  
Large Scale ◽  
Access Network ◽  
Calculation Model ◽  
Simulation Algorithm ◽  
Charging Time ◽  
Load Calculation ◽  
Other Information ◽  
Charging Mode ◽  
Ev Charging

This article combs the charging mode of electric vehicle,and analyzes different charging ways for buses,taxis and sedans,thereby drawing their appropriate charging time and characteristics of the interaction with grid. The paper establishes the load calculation model for the charging and swapping in Evs respectively. The load calculation model divides one day into 1440 minutes, and use the Monte Carlo simulation algorithm to extract the initial SOC, the initial charging time and other information for load calculation and analyze the EV charging load. The results show that the charging load of electric vehicle has obvious difference between peak and vally,and provide reference for the management and policy oriented electric vhicle access network.

Integrated Approach for Vibration-Based Condition Monitoring of Rotating Machines

2015 ◽  
Author(s):  
Jyoti K. Sinha
Keyword(s):  
Condition Monitoring ◽  
Experimental Studies ◽  
Integrated Approach ◽  
Rotating Machines ◽  
Rotating Machine ◽  
Research Studies

Conventional Vibration-based Condition Monitoring (VCM) is well known and well accepted in industries to identify the fault(s), if any, in rotating machine since decades. However over the last 3 decades, significant advancement in both computational and instrumentation technologies has been noticed which resulted in number of research studies to find the alternate and efficient methods for fault(s) diagnosis. But most of the research studies may not be leading to an Integrated Modern VCM (IMVCM). It may be because of mainly 2 reasons; (a) the recent proposed methods in the literature are based on numerically simulated studies and a very limited experimental studies and (b) none of the recent studies applied on all kind of faults. In this paper, a summary of a couple of methods proposed and published earlier by author to meet the requirement of the IMVCM is presented.

Cost Effective On-Site Fault Diagnosis Home Appliance Using a Smart Phone and Support Vector Machine

2019 ◽  
Author(s):  
Ji Min Baek ◽  
Kyeong Ha Lee ◽  
Seung Ho Lee ◽  
Ja Choon Koo
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Smart Phone ◽  
Poor Performance ◽  
Cost Effective ◽  
Consumer Electronics ◽  
Support Vector ◽  
Rotating Machines ◽  
Pass Filter ◽  
Rotating Machine

Abstract One of the common rotating machines of the consumer electronics might be a washing machine. The rotating machinery normally suffers mechanical failures even during daily operations that results in poor performance or shortening lifetime of the machine. Therefore, engineers have been interested in the earliest fault diagnosis of the rotating machine. Existing fault diagnosis methods for rotating machines have used fast fourier transform (FFT) method in frequency domain to detect abnormal frequency. However, it is difficult to diagnose using the FFT method if the normal frequency components of the rotating machines overlaps with the fault frequencies. In this paper, sets of acoustic signals generated by the washing machines are collected by using a smart phone in which an inexpensive microphone is equipped, and collected data are analyzed using a new algorithm, which combining the skewness, kurtosis, A-weighting filter, high-pass filter (HPF), and FFT. The analyzed data is applied to support vector machine (SVM) to determine defect existence. The proposed algorithm solves the disadvantages of the existing method and is accurate enough to discriminate the data collected by the cheap microphone of the smart phone.

Diagnosis of rotating machine unbalance using machine learning algorithms on vibration orbital features

2020 ◽  
pp. 107754632092983
Author(s):  
Leonardo S Jablon ◽  
Sergio L Avila ◽  
Bruno Borba ◽  
Gustavo L Mourão ◽  
Fabrizio L Freitas ◽  
...  
Keyword(s):  
Machine Learning ◽  
Learning Strategies ◽  
Machine Learning Algorithms ◽  
Vibration Measurement ◽  
Machine Learning Techniques ◽  
Rolling Element Bearings ◽  
Rotating Machines ◽  
Signal To Noise ◽  
Rotating Machine ◽  
Rolling Element

The diagnosis of failures in rotating machines has been subject to studies because of its benefits to maintenance improvement. Condition monitoring reduces maintenance costs, increases reliability and availability, and extends the useful life of critical rotating machinery in industry ambiance. Machine learning techniques have been evolving rapidly, and its applications are bringing better performance to many fields. This study presents a new strategy to improve the diagnosis performance of rotating machines using machine learning strategies on vibration orbital features. The advantage of using orbits in comparison to other vibration measurement systems is the simplicity of the instrumentation involved as well as the information multiplicity contained in the orbit. On the other hand, rolling element bearings are prevalent in industrial machinery. This type of bearing has less orbital oscillation and is noisier than sliding contact bearings. Therefore, it is more difficult to extract useful information. Practical results on an industry motor workbench with rolling element bearings are presented, and the algorithm robustness is evaluated by calculating diagnosis accuracy using inputs with different signal-to-noise ratios. For this kind of noisy scenario where signal analysis is naturally tough, the algorithm classifies approximately 85% of the time correctly. In a completely harsh environment, where the signal-to-noise ratio can be smaller than −25 dB, the accuracy achieved is close to 60%. These statistics show that the strategy proposed can be robust for rotating machine unbalance condition diagnosis even in the worst scenarios, which is required for industrial applications.

Can green taxation trigger plug-in hybrid electric vehicle acquisition?

2019 ◽  
Vol 14 (2) ◽  
pp. 168-186
Author(s):  
Victor Barros ◽  
Hugo Pádua
Keyword(s):  
Electric Vehicle ◽  
Financial Incentives ◽  
Structural Equation ◽  
Hybrid Electric Vehicle ◽  
Large Scale ◽  
Tax Reform ◽  
Financial Incentive ◽  
Content Type ◽  
Green Tax Reform ◽  
Hybrid Electric

Purpose The purpose of this paper is to analyse to what extent financial incentives under the green tax reform introduced in Portugal in 2014 drive behaviours of acquiring a plug-in hybrid electric vehicle (PHEV). Design/methodology/approach The existent literature identifies a number of factors that influence the interest for PHEV acquisition, including access to financial incentives. However, empirical evidence is not clear as to which factors are more relevant. The authors extend an existent theoretical model of five factors by including ten factors. On this basis, the study carries out a survey and develops a structural equation model to investigate what drives the interest to acquire a PHEV. Findings Financial incentives are superior to other factors in explaining the interest in acquiring a PHEV. Education, lower income levels, living in larger cities and driving smaller vehicles shape the interest on these vehicles differently. Financial incentives were found to closely offset the difference in price between conventional vehicles and plug-in hybrids. Social implications This study finds that public policies can be powerful in shaping consumers’ behaviour, although the amount of the financial incentive is key to triggering a large-scale effect. Originality/value The survey in this study allows an in-depth and ex ante analysis of the interest in acquiring PHEV under a green tax reform, taking into account other dimensions and socio-economic variables not accounted for in existent studies.

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