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Tytuł artykułu

Light electric vehicle powertrain analysis.

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper describes the structure of a light electric vehicle known as the Mia Electric vehicle. The vehicle parameters and exploitation properties are presented, while the advantages and disadvantages of the vehicle’s technical solutions are discussed, along with possible ideas for their improvement. Vehicle test results on a roller dyno and under actual driving conditions are presented. The data recorded during tests form the basis of an analysis of the vehicle powertrain, whose findings are described in the summary along with testing conclusions.
Rocznik
Tom
Strony
123--137
Opis fizyczny
Bibliogr. 30 poz.
Twórcy
  • Faculty of Electrical Engineering, Gdynia Maritime University, Morska 83 Street, 81-225 Gdynia, Poland
Bibliografia
  • 1. Lange Stefan, Ulbrich Fritz, Daniel Goehring. 2016. “Online vehicle detection using deep neural networks and lidar based preselected image patches.” IEEE Intelligent Vehicles Symposium. DOI: http://doi.org/10.1109/IVS.2016.7535503.
  • 2. Chuanrong Li, Mei Zhou, Liu Menghua, Ma Lian, Wang Jinhu. 2016. “A concealed car extraction method based on full-waveform LiDAR data”. Mobile Information Systems. DOI: http://doi.org/10.1155/2016/3854217.
  • 3. Yansong Liu, Sildomar T. Monteiro, Eli Saber. 2016. “Vehicle detection from aerial color imagery and airborne LiDAR data.” IEEE International Geoscience and Remote Sensing Symposium (IGARSS). DOI: http://doi.org/10.1109/IGARSS.2016.7729354.
  • 4. Michael Kusenbach, Michael Himmelsbach, Hans-Joachim Wuensche. 2016. “A new geometric 3D LiDAR feature for model creation and classification of moving objects.” IEEE Intelligent Vehicles Symposium. DOI: http://doi.org/10.1109/IVS.2016.7535397.
  • 5. Kenneth Schofield, Mark L. Larson, Keith J. Vadas. 1999. “Display enhancements for vehicle vision system”. US Patent US5949331A.
  • 6. O'Cualain Diarmad, Martin Glavin, Edward Jones. 2016. “Method for detecting an object in an environmental region of a motor vehicle by means of a camera system of the motor vehicle, camera system and motor vehicle.” US Patent US9340156B2.
  • 7. Rosolia Ugo, Stijn De Bruyne, Andrew G. Alleyne. 2016. “Autonomous vehicle control: a nonconvex approach for obstacle avoidance.” IEEE Transactions on Control Systems Technology, Vol. PP, Iss. 99.
  • 8. Boyuan Li, Du Haiping, Li Weihua. 2015. “Trajectory control for autonomous electric vehicles with in-wheel motors based on a dynamics model approach.” IET Intelligent Transport Systems, Vol. 10, Iss. 5: 318-330. DOI: http://doi.org/10.1049/ietits.2015.0159.
  • 9. Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Huimin Ma, Sanja Fidler, Raquel Urtasun. 2016. “3D object proposals using stereo imagery for accurate object class detection.” Computer Vision and Pattern Recognition. arXiv:1608.07711.
  • 10. Mutz Filipe, Lucas P. Veronese, Thiago Oliveira-Santos, Edilson de Aguiar, Fernando A. Auat Cheein, Alberto Ferreira De Souza. 2016. “Large-scale mapping in complex field scenarios using an autonomous car.” Expert Systems with Applications, Vol. 46: 439-462.
  • 11. Ingle Shantanu, Madhuri Phute. 2016. “Tesla autopilot: semi autonomous driving, an uptick for future autonomy.” International Research Journal of Engineering and Technology, Vol. 3, Iss. 9.
  • 12. Le Vinea Scott, Alireza Zolfaghari, John Polak. 2015. “Autonomous cars: the tension between occupant experience and intersection capacity”. Transportation Research Part C: Emerging Technologies, Vol. 52.
  • 13. “Reduction of pollutant emissions from light vehicles.” 2016. Available at: http://eurlex.europa.eu.
  • 14. “10 of the best electric vehicles”. 2016. Available at: http://www.carbase.co.uk.
  • 15. “Mia, the ideal electric car designed for the city.” 2016. Available at: mia-automobileclub.com.
  • 16. “Mia electric micro.bus”. 2016. Available at: http://www.greencardesign.com.
  • 17. “Mia electric innove pour mieux rebondir”. 2016. Available at: http://www.largus.fr.
  • 18. Łebkowski Andrzej. 2017. “Electric vehicle data recorder”. Przegląd Elektrotechniczny, Vol. 2. ISSN 0033-2097. Doi: http://doi.org/10.15199/48.2017.02.62.
  • 19. Łebkowski Andrzej. 2016. “Temperature, overcharge and short-circuit studies of batteries used in electric vehicles”. Przegląd Elektrotechniczny. ISSN 0033-2097. (In print).
  • 20. Figlus Tomasz, Jozef Gnap, Tomas Skrucany, Branislav Sarkan, Jozef Stoklosa. 2016. “The Use of Denoising and Analysis of the Acoustic Signal Entropy in Diagnosing Engine Valve Clearance”. Entropy, Vol. 18, Issue 7: 1-11. DOI: http://doi.org/10.3390/e18070253. ISSN: 1099-4300.
  • 21. Kotak B., Y. Kotak. 2016. “Review of European Regulations and Germany's Action to Reduce Automotive Sector Emissions”. European Transport\Trasporti Europei, Issue 61, Paper no 7: 1-19. ISSN: ISSN 1825-3997.
  • 22. Łebkowski Andrzej. 2015. “Emission of noise in electric vehicles”. Economics and Organization of Enterprise, No.7: 48-62. ISSN 0860-6846.
  • 23. Bensana T., S. Mekhilef. 2016. “Numerical and experimental analysis of vibratory signals for rolling bearing fault diagnosis”. Mechanika, Vol. 22, No 3: 217-224. DOI: http://dx.doi.org/10.5755/j01.mech.22.3.11962. ISSN: 1392-1207.
  • 24. Czech Piotr, Grzegorz Wojnar, Rafał Burdzik, Łukasz Konieczny, Jan Warczek. 2014. “Application of the discrete wavelet transform and probabilistic neural networks in IC engine fault diagnostics”. Journal of Vibroengineering, Vol. 16, Issue 4: 1619-1639. ISSN 1392-8716.
  • 25. Czech Piotr. 2012. “Identification of leakages in the inlet system of an internal combustion engine with the use of Wigner-Ville transform and RBF neural networks”. In Jerzy Mikulski (ed.). 12th International Conference on Transport Systems Telematics. Katowice Ustron, Poland. 10-13 October 2012. Telematics in the Transport Environment. Book Series: Communications in Computer and Information Science, Vol. 329: 414-422.
  • 26. Czech Piotr. 2013. “Intelligent approach to valve clearance diagnostic in cars”. In Bronius Baksys, Algirdas Bargelis, Stasys Bockus, Algimantas Fedaravicius, Vylius Leonavicius, Pranas Ziliukas, Romualdas Dundulis, Tilmute Pilkaite (eds.). Proceedings of the18th International Conference on Mechanika. Kaunas University of Technology, Kaunas, Lithuania. 4-5 April 2013. Kaunas University of Technology. Book Series: Mechanika Kaunas University of Technology: 58-61.
  • 27. Louahem M‘sabah H., A. Bouzaouit. 2016. “Degradation model of the bearings by wiener process”. Mechanika, Vol. 22, No 3: 225-228. DOI: http://dx.doi.org/10.5755/j01.mech.22.3.13000. ISSN: 1392-1207.
  • 28. Madej Henryk, Piotr Czech. 2010. “Discrete wavelet transform and probabilistic neural network in IC engine fault diagnosis”. Eksploatacja i Niezawodnosc - Maintenance and Reliability, Vol. 4(48): 47-54. ISSN: 1507-2711.
  • 29. Obuchowski Jakub, Radoslaw Zimroz, Agnieszka Wylomanska. 2016. “Blind equalization using combined skewness-kurtosis criterion for gearbox vibration enhancement”. Measurement, Vol. 88: 34-44. DOI: http://doi.org/10.1016/j.measurement.2016.03.034. ISSN: 0263-2241.
  • 30. Wodecki Jacek, Pawel Stefaniak, Jakub Obuchowski, Agnieszka Wylomanska, Radosław Zimroz. 2016. “Combination of principal component analysis and timefrequency representations of multichannel vibration data for gearbox fault detection”. Journal of Vibroengineering, Vol. 18, Issue 4: 2167-2175. DOI: 10.21595/jve.2016.17114. ISSN: 1392-8716.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-dfb9840f-217c-4858-bed4-43879a96e5cb
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