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A review of the factors and input parameters influencing the range of an Edison electric vehicle according to measurements

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Research and development help improve the reliability of EVs range, battery capacity, and trouble-free charging (or service). These factors affect consumers’ interest in EVs. The quality of EV use can be supported by a modern technology called Energy Assistant (EA). The task of EA is to inform the driver about the current range, the necessity to recharge the batteries, and so on to avoid a critical situation. The main aim of this article was to investigate factors and input parameters for the proposal of EA. The Edison EV designed at the University of Žilina, was used for experimental work under real conditions and in an accredited lab with MAHA equipment.
Rocznik
Strony
270--282
Opis fizyczny
Bibliogr. 34 poz., rys., tab., wykr.
Twórcy
  • University of Žilina, Faculty of Mechanical Engineering, Slovakia
  • University of Žilina, Faculty of Mechanical Engineering, Slovakia
  • University of Žilina, Faculty of Mechanical Engineering, Slovakia
  • University of Žilina, Faculty of Mechanical Engineering, Slovakia
Bibliografia
  • Argue, Ch. (2020). To what degree does temperature impact EV range? Retrieved from: https://www.geotab.com/blog/ev-range [accessed 27.10.2021].
  • Chang, N., Baek, D. & Hong, J. (2014). Power consumption characterization, modeling and estimation of electric vehicles. In 2014 IEEE/ /ACM International Conference on Computer-Aided Design (ICCAD), San Jose, CA, USA, 2–6 November 2014 (pp. 175-182). https://doi.org/10.1109/ICCAD.2014.7001349
  • Chen, D. C. & Crolla, D. A. (2007). Subjective and objective measures of vehicle handling: drivers & experiments. International Journal of Vehicle Mechanics and Mobility, 29 (S1), 576-597. https://doi.org/10.1080/00423119808969588
  • Cieslik, W., Szwajca, F., Zawartowski, J., Pietrzak, K., Rosolski, S., Szkarlat, K. & Rutkowski, M. (2021). Capabilities of nearly zero energy building (nZEB) electricity generation to charge electric vehicle (EV) operating in real driving conditions (RDC). Energies, 14 (22), 7591. https://doi.org/10.3390/en14227591
  • Commission Regulation (EC) No 692/2008 of 18 July 2008 implementing and amending Regulation (EC) No 715/2007 of the European Parliament and of the Council on type-approval of motor vehicles with respect to emissions from light passenger and commercial vehicles (Euro 5 and Euro 6) and on access to vehicle repair and maintenance information. OJ L 199, 28.7.2008, p. 1.
  • Commission Regulation (EU) 2017/1151 of 1 June 2017 supplementing Regulation (EC) No 715/2007 of the European Parliament and of the Council on type-approval of motor vehicles with respect to emissions from light passenger and commercial vehicles (Euro 5 and Euro 6) and on access to vehicle repair and maintenance information, amending Directive 2007/46/EC of the European Parliament and of the Council, Commission Regulation (EC) No 692/2008 and Commission Regulation (EU) No 1230/2012 and repealing Commission Regulation (EC) No 692/2008. C/2017/3521. OJ L 175, 7.7.2017, p. 1.
  • De Pinto, S., Lu, Q., Camocardi, P., Chatzikomis. Ch., Sorniotti. A., Ragonese, D., Iuzzolino, G., Perlo, P. & Lekakou, C. (2016). Electric vehicle driving range extension using photovoltaic panels. In IEEE Vehicle Power and Propulsion Conference (VPPC), Hangzhou, China, 17-20 October 2016 (pp. 1-6). Piscataway Township: IEEE. https://doi.org/10.1109/VPPC.2016.7791674
  • Dwibedi, R. K., Jayaprakash, R., Siva, T. & Gopinath, N. P. (2020). Hybrid electric vehicle using photovoltaic panel and chemical battery. Materials Today: Proceedings, 33, 4713-4718. https://doi.org/10.1016/j.matpr.2020.08.351
  • Franke, T., Neumann, I., Buhler, F., Cocoron, P. & Krems, J. F. (2012) Experiencing range in an electric vehicle - understanding psychological barriers. Applied Psychology, 61 (3), 368-391. https://doi.org/10.1111/j.1464-0597.2011.00474.x
  • Franke, T., Rauh, N. & Krems, J. F. (2016). Individual differences in BEV drivers’ range stress during first encounter of a critical range situation. Applied Ergonomics, 57, 28-35. https://doi.org/10.1016/j.apergo.2015.09.010
  • Geotab (2021). Temperature tool for EV range. Retrieved from: https://www.geotab.com/fleet-management-solutions/ev-temperaturetool [accessed 27.10.2021].
  • Habek, P., Lavios, J. & Krupah, E. (2022). How car producers are driving toward sustainable supplier development. Production Engineering Archives, 28 (3) 268-278. https://doi.org/10.30657/pea.2022.28.33
  • Hong, J., Park S. & Chang, N. (2016). Accurate remaining range estimation for electric vehicles. In 21st Asia and South Pacific Design Automation Conference (ASP-DAC), Macao, China, 25-28 January 2016 (pp. 781-786). Piscataway Township: IEEE. https://doi.org/10.1109/ASPDAC.2016.7428106
  • Hrček, S., Medvecký, Š. & Bisták, M. (2017). Axle weighing system. In Proceedings of the 58th International Conference of Machine Design Departments, Prague, Czech Republic, 6-8 September 2017 (pp. 36-39). Prague: Czech University of Life Science. Retrieved from: http://2017.icmd.cz/proceedings/7_ICMD.pdf [accessed 27.10.2021].
  • Hu, X., Zheng, Y., Howey, D. A., Perez, H., Foley, A. & Pecht, M. (2020). Battery warm-up methodologies at subzero temperatures for automotive applications: recent advances and perspectives. Progress in Energy and Combustion Science, 77, 100806. https://doi.org/10.1016/j.pecs.2019.100806
  • Jaguemont, J., Boulon, L. & Dubé, Y. (2016). A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures. Applied Energy, 164, 99-114. https://doi.org/10.1016/j.apenergy.2015.11.034
  • Ji, Y. & Wang Ch. Y. (2013). Heating strategies for Li-ion batteries operated from subzero temperatures. Electrochimica Acta, 107, 664–674. https://doi.org/10.1016/j.electacta.2013.03.147
  • Kavianipour, M., Fakhrmoosavi, F., Singh, H., Ghamami, M., Zockaie, A., Ouyang, Y. & Jackson, R. (2021). Electric vehicle fast charging infrastructure planning in urban networks considering daily travel and charging behavior. Transportation Research Part D: Transport and Environment, 93, 102769. https://doi.org/10.1016/j.trd.2021.102769
  • Kucukoglu, I., Dewil, R. & Cattrysse, D. (2021). The electric vehicle routing problem and its variations: a literature review. Computers & Industrial Engineering, 161, 107650. https://doi.org/10.1016/j.cie.2021.107650
  • Li, S., Yu, B. & Feng, X. (2020). Research on braking energy recovery strategy of electric vehicle based on ECE regulation and I curve. Science Progress, 103 (1), 1-17. https://doi.org/10.1177/0036850419877762
  • Li, X., Wang, T., Wu, C., Tian, J. & Tian, Y. (2021). Battery pack state of health prediction based on the electric vehicle management platform data. World Electric Vehicle Journal, 12 (4), 204. https://doi.org/10.3390/wevj12040204
  • Lindgren, J. & Lund, P. D. (2016). Effect of extreme temperatures on battery charging and performance of electric vehicles. Journal of Power Sources, 328, 37-45. https://doi.org/10.1016/j.jpowsour.2016.07.038
  • MAHLE (2021). MAHLE develops new battery cooling system for faster charging of electric cars (Press release 07.09.2021 Stuttgart). Retrieved from: https://www.mahle.com/en/news-and-press/press-releases/mahle-develops-new-battery-cooling-system-for-fastercharging-of-electric-cars-85120 [accessed 02.10.2021].
  • Miri, I., Fotouhi, A. & Ewin, N. (2021). Electric vehicle energy consumption modelling and estimation - a case study. International Journal of Energy Research, 45 (1), 501-520. https://doi.org/10.1002/er.5700
  • Münster, M., Schäffer, M., Kopp, G., Kopp, G. & Friedrich, H. E. (2016). New approach for a comprehensive method for urban vehicle concepts with electric powertrain and their necessary vehicle structures. Transportation Research Procedia, 14, 3686-3695. https://doi.org/10.1016/j.trpro.2016.05.487
  • Nanaki, E. A. (2021). Electric vehicles. Electric vehicles for smart cities, trends, challenges, and opportunities (pp. 13-49). Amsterdam: Elsevier. https://doi.org/10.1016/B978-0-12-815801-2.00006-X
  • Ozatay, E., Onori, S., Wollaeger, J., Ozguner, U., Rizzoni, R., Filev, D., Michelini, J. & Di Cairano, S. (2014). Cloud-based velocity profile optimization for everyday driving: a dynamic-programming-based solution. IEEE Transactions on Intelligent Transportation Systems, 15 (6), 2491-2505. https://doi.org/10.1109/TITS.2014.2319812
  • Pavlovič, J., Ciuffo, B. Fontaras, G., Valverde, V. & Marotta, A. (2018). How much difference in type-approval CO2 emissions from passenger cars in Europe can be expected from changing to the new test procedure (NEDC vs. WLTP)? Transportation Research Part A: Policy and Practice, 111, 136-147. https://doi.org/10.1016/j.tra.2018.02.002
  • Redelbach, M., Özdemir, E. D. & Friedrich, H. E. (2014). Optimizing battery sizes of plug-in hybrid and extended range electric vehicles for different user types. Energy Policy, 73, 158-168. https://doi.org/10.1016/j.enpol.2014.05.052
  • Schmid, M., Tomek, P. & Hanus, P. (2022). Multi-physical contact simulation in vehicle applications. Production Engineering Archives, 28 (4) 369-374. https://doi.org/10.30657/pea.2022.28.45
  • Vatanparvar, K. & Faruque, M. A. A. (2017). Electric vehicle optimized charge and drive management. ACM Transactions on Design Automation of Electronic Systems (TODAES), 23 (1), 1-25. https://doi.org/10.1145/3084686
  • Vatanparvar, K. & Faruque, M. A. A. (2018). Design and analysis of battery-aware automotive climate control for electric vehicles. ACM Transactions on Embedded Computing Systems (TECS), 17 (4), 1-22. https://doi.org/10.1145/3203408
  • Weiss, M., Cloos, K. C. & Helmers, E. (2020). Energy efficiency trade-offs in small to large electric vehicles. Environmental Sciences Europe, 32 (1), 1-17. https://doi.org/10.1186/s12302-020-00307-8
  • Xiong, R. (2020). Battery management algorithm for electric vehicles. Singapore: Springer. https://doi.org/10.1007/978-981-15-0248-4
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fb241163-0bb8-4762-83f6-578710366ea5
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