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JCR Impact Factor: 0.459
JCR 5-Year IF: 0.442
Issues per year: 4
Current issue: Feb 2017
Next issue: May 2017
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
Issue 4/2016



Anomaly Detection Using Power Signature of Consumer Electrical Devices, CERNAZANU-GLAVAN, C., MARCU, M.
Issue 1/2015


Optimizing Decision Tree Attack on CAS Scheme, PERKOVIC, T., BUGARIC, M., CAGALJ, M.
Issue 2/2016


Stability Aspects in One-Cycle Controlled Buck Converters, GURBINA, M., LASCU, D.
Issue 1/2014


Single-phase Multilevel Current Source Inverter with Reduced Device Count and Current Balancing Capability, MOALLEMI KHIAVI, A., FARHADI KANGARLU, M., DAIE KOOZEHKANANI, Z., SOBHI, J., HOSSEINI, S. H.
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Visual Peoplemeter: A Vision-based Television Audience Measurement System, SKELIN, A. K., SUPUK, T. G., BONKOVIC, M.
Issue 4/2014


A Novel Non-Iterative Method for Real-Time Parameter Estimation of the Fricke-Morse Model, SIMIC, M., BABIC, Z., RISOJEVIC, V., STOJANOVIC G. M.
Issue 4/2016



With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "Big Data - " before the paper title in OpenConf.

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Thomson Reuters published the Journal Citations Report for 2015. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.459, and the JCR 5-Year Impact Factor is 0.442.

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  1/2016 - 7

Analysis Platform for Energy Efficiency Enhancement in Hybrid and Full Electric Vehicles

NICOLAICA, M.-O. See more information about NICOLAICA, M.-O. on SCOPUS See more information about NICOLAICA, M.-O. on IEEExplore See more information about NICOLAICA, M.-O. on Web of Science, TARNICERIU, D. See more information about TARNICERIU, D. on SCOPUS See more information about TARNICERIU, D. on SCOPUS See more information about TARNICERIU, D. on Web of Science
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,269 KB) | Citation | Downloads: 288 | Views: 681

Author keywords
batteries, data analysis, energy efficiency, electric vehicles, modeling

References keywords
electric(17), vehicle(10), hybrid(9), vehicles(8), power(6), motor(5), electronics(5), control(5), technology(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-02-28
Volume 16, Issue 1, Year 2016, On page(s): 47 - 52
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.01007
Web of Science Accession Number: 000376995400007
SCOPUS ID: 84960092815

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The current paper presents a new virtual analysis method that is applied both on hybrid and electric vehicle architectures with the purpose of contributing to the improvement of energy efficiency. The study is based on Matlab modeling and simulation. A set of parameters are considered in order to assess the system performance. The benefit is given by the comparative overview obtained after the completed analysis. The effectiveness of the analysis method is confirmed by a sequence of simulation results combined in several case studies. The impulse of the research is given by the fact that the automotive market is focusing on wider simulation techniques and better control strategies that lead to more efficient vehicles. Applying the proposed method during design would improve the battery management and controls strategy. The advantage of this method is that the system behavior with regards to energy efficiency can be evaluated from an early concept phase. The results contribute to the actual necessity of driving more efficient and more environmental friendly vehicles.

References | Cited By  «-- Click to see who has cited this paper

[1] G. Livint, V. Horga, D. Sticea, M. Ratoi, M. Albu, "Hybrid Electric Vehicle Experimental Model with CAN Network Real Time Control," Advances in Electrical and Computer Engineering, vol. 10, no. 2, pp. 102-107, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 4] [SCOPUS Times Cited 4]

[2] Y. Gao, M. Ehsani, J. M. Miller, "Hybrid electric vehicle: overview and state of the art," IEEE International Symposium - Industrial Electronics, pp. 307-316, Dubrovnik, Croatia, 2005.

[3] X. Hu, S. Li, H. Peng, "A Comparative Study of Equivalent Circuit Models for Li-Ion Batteries," Journal of Power Sources, vol. 198, pp. 359-367, 2012.
[CrossRef] [Web of Science Times Cited 292] [SCOPUS Times Cited 360]

[4] M. Ehsani, Y. Gao, S. E. Gay, A. Emadi, "Modern Electric, Hybrid Electric, and Fuel Cell Vehicles", pp. 48-50, CRC Press, 2005.

[5] N. Kim, S.W. Cha, H. Peng, "Optimal Equivalent Fuel Consumption for Hybrid Electric Vehicles," Control Systems Technology, IEEE Transactions, vol. 20, pp. 817-825, May 2012.
[CrossRef] [Web of Science Times Cited 30] [SCOPUS Times Cited 50]

[6] L. Lu, X. Han, J. Li, J. Hua, M. Ouyang, "A Review on the Key Issues for Lithium-Ion Battery Management in Electric Vehicles," Journal of Power Sources, vol. 226, pp.272-288, 2013.
[CrossRef] [Web of Science Times Cited 465] [SCOPUS Times Cited 564]

[7] A. Panday, H.O. Bansal, "A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle," International Journal of Vehicular Technology, vol. 2014, 19 pages, 2014.
[CrossRef] [SCOPUS Times Cited 10]

[8] S. Miller, "Hybrid-Electric Vehicle Model in Simulink #28441," Matlab Central, August 2010.

[9] D. Wenzhong, Gao, C. Mi, A. Emadi, "Modeling and Simulation of Electric and Hybrid Vehicles," Proceedings of the IEEE, vol. 95, no. 4, pp. 729-745, 2007,
[CrossRef] [Web of Science Times Cited 116] [SCOPUS Times Cited 222]

[10] F. Wu, T. Yeh, C. Huang, "Motor control and torque coordination of an electric vehicle actuated by two in-wheel motors," Mechatronics, vol. 23, no. 1, pp. 46-60, 2013.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 21]

[11] N. Bouchetata, M. Bourahla, L. Ghaouti, "Behavior Modeling and Simulation of Double Wheeled Electric Vehicle Drive," Przeglad Elektrotechniczny, vol. 88, no. 10A, pp. 218-223, 2012.

[12] S. Haghbin, K. Khan, S. Zhao, M. Alakula, S. Lundmark, O. Carlson, "An Integrated 20-kW Motor Drive and Isolated Battery Charger for Plug-In Vehicles," IEEE Transactions on Power Electronics, vol. 28, no. 8, pp. 4013-4029, 2013.
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 33]

[13] D. Hamza, M. Pahlevaninezhad, P. K. Jain, "Implementation of a Novel Digital Active EMI Technique in a DSP-Based DC-DC Digital Controller Used in Electric Vehicle (EV)," IEEE Transactions on Power Electronics, vol. 28, no. 7, pp. 3126-3137, 2013.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 28]

[14] C. C. Chan, K. T. Chau, "An Overview of Power Electronics in Electric Vehicles," IEEE Transactions On Industrial Electronics, vol. 44, no. 1, February 1997.
[CrossRef] [Web of Science Times Cited 131] [SCOPUS Times Cited 212]

[15] W. Li, G. Xu, H. Tong, Y. Xu, "Design of optimal, robust energy management strategy for a parallel HEV," IEEE International Conference Robotics and Biomimetics, 2007. ROBIO 2007.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 1]

[16] F. R. Salmasi, "Control Strategies for Hybrid Electric Vehicles: Evolution, Classification, Comparison, and Future Trends," IEEE Transactions on Vehicular Technology, vol. 56, no. 5, pp. 2393 - 2404, September 2007.
[CrossRef] [Web of Science Times Cited 207] [SCOPUS Times Cited 339]

[17] R. Hodkinson, J. Fenton, "Electric motor and drive-controller design," Automotive Engineering Series, pp. 56-79, 2000.

[18] B. Tabbache, A. Kheloui, M.E.H. Benbouzid, "Design and control of the induction motor propulsion of an Electric Vehicle," Vehicle Power and Propulsion Conference (VPPC) IEEE, pp. 1-6, 2010.
[CrossRef] [SCOPUS Times Cited 4]

[19] S. C. Oh, "Evaluation of motor characteristics for hybrid electric vehicles using the hardware-in-the-loop concept," IEEE Transactions - Vehicular Technology, vol. 54(3), pp. 817-824, May 2005.
[CrossRef] [Web of Science Times Cited 38] [SCOPUS Times Cited 64]

[20] Z. Xiaowei, H. Hongwen, X. Rui, "Hardware in loop simulation for vehicle controller in hev based on dspace," Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference, vol. 2, pp. 489-492, August 2010.

References Weight

Web of Science® Citations for all references: 1,346 TCR
SCOPUS® Citations for all references: 1,912 TCR

Web of Science® Average Citations per reference: 64 ACR
SCOPUS® Average Citations per reference: 91 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references background updated on 2017-02-25 20:49 in 126 seconds.

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Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

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Faculty of Electrical Engineering and Computer Science
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