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Methodology for Assessing the Impact of Aperiodic Phenomena on the Energy Balance of Propulsion Engines in Vehicle Electromobility Systems for Given Areas

Author

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  • Piotr Wróblewski

    (Division of Aircraft Construction and Operation, Institute of Aviation Technology, Faculty of Mechatronics, Armament and Aerospace of the Military University of Technology, Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland)

  • Wojciech Drożdż

    (Research Center for Management of Energy Sector, Institute of Management, University of Szczecin, Cukrowa Street 8, 71-004 Szczecin, Poland)

  • Wojciech Lewicki

    (Faculty of Economics, West Pomeranian University of Technology Szczecin, Żołnierska 47, 71-210 Szczecin, Poland)

  • Paweł Miązek

    (Research Center for Management of Energy Sector, Institute of Management, University of Szczecin, Cukrowa Street 8, 71-004 Szczecin, Poland)

Abstract

The article presents the methodology of isolating aperiodic phenomena constituting the basis of the energy balance of vehicles for the analysis of electromobility system indicators. The symptom observation matrix (SOM) and experimental input data are used to analyze periodic phenomena symptoms. The multidimensional nature of the engine efficiency shortage has been well defined and analyzed in terms of errors in the general model using neural networks, singular value decomposition, and principal component analysis. A more difficult task is the analysis of a multidimensional decision-making process. The research used a data fusion method and the concept of symptom reliability, which is applied to the generalized failure symptom obtained by applying the singular value decomposition (SVD). The model research has been based on the gray system theory (GST) and GM forecasting models (1,1). Input data were obtained from the assessment of driving cycles and analysis of the failure frequency for 1200 vehicles and mileage of 150,000 km. Based on this analysis, it can be concluded that with the current infrastructure and operating costs and the frequency of failure of PHEV and BEV drives, ICEV vehicles are unrivaled in terms of their operating costs.

Suggested Citation

  • Piotr Wróblewski & Wojciech Drożdż & Wojciech Lewicki & Paweł Miązek, 2021. "Methodology for Assessing the Impact of Aperiodic Phenomena on the Energy Balance of Propulsion Engines in Vehicle Electromobility Systems for Given Areas," Energies, MDPI, vol. 14(8), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2314-:d:539754
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    1. Lee, Seongjun & Kim, Jonghoon, 2017. "Implementation methodology of powertrain for series-hybrid military vehicles applications equipped with hybrid energy storage," Energy, Elsevier, vol. 120(C), pages 229-240.
    2. Du, Jiuyu & Chen, Jingfu & Song, Ziyou & Gao, Mingming & Ouyang, Minggao, 2017. "Design method of a power management strategy for variable battery capacities range-extended electric vehicles to improve energy efficiency and cost-effectiveness," Energy, Elsevier, vol. 121(C), pages 32-42.
    3. Macharis, Cathy & Van Hoeck, Ellen & Pekin, Ethem & van Lier, Tom, 2010. "A decision analysis framework for intermodal transport: Comparing fuel price increases and the internalisation of external costs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(7), pages 550-561, August.
    4. Khan, Mobashwir & Kockelman, Kara M., 2012. "Predicting the market potential of plug-in electric vehicles using multiday GPS data," Energy Policy, Elsevier, vol. 46(C), pages 225-233.
    5. Li, Maobing & Xu, Hui & Li, Weimin & Liu, Yin & Li, Fade & Hu, Yue & Liu, Li, 2016. "The structure and control method of hybrid power source for electric vehicle," Energy, Elsevier, vol. 112(C), pages 1273-1285.
    6. Wojciech Drozdz, 2019. "The development of electromobility in Poland," Virtual Economics, The London Academy of Science and Business, vol. 2(2), pages 61-69, April.
    7. Zhang, Pei & Yan, Fuwu & Du, Changqing, 2015. "A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 88-104.
    8. Liu, Teng & Wang, Bo & Yang, Chenglang, 2018. "Online Markov Chain-based energy management for a hybrid tracked vehicle with speedy Q-learning," Energy, Elsevier, vol. 160(C), pages 544-555.
    9. Shen, Peihong & Zhao, Zhiguo & Zhan, Xiaowen & Li, Jingwei & Guo, Qiuyi, 2018. "Optimal energy management strategy for a plug-in hybrid electric commercial vehicle based on velocity prediction," Energy, Elsevier, vol. 155(C), pages 838-852.
    10. Shen, Peihong & Zhao, Zhiguo & Zhan, Xiaowen & Li, Jingwei, 2017. "Particle swarm optimization of driving torque demand decision based on fuel economy for plug-in hybrid electric vehicle," Energy, Elsevier, vol. 123(C), pages 89-107.
    11. Fontaras, Georgios & Dilara, Panagiota, 2012. "The evolution of European passenger car characteristics 2000–2010 and its effects on real-world CO2 emissions and CO2 reduction policy," Energy Policy, Elsevier, vol. 49(C), pages 719-730.
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