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Physics-Based Prediction for the Consumption and Emissions of Passenger Vehicles and Light Trucks up to 2050

Author

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  • Manfred Dollinger

    (Chair of Measurement and Control Systems, Center of Energy Technology (ZET), Universität Bayreuth, Universitätsstr. 30, 95447 Bayreuth, Germany)

  • Gerhard Fischerauer

    (Chair of Measurement and Control Systems, Center of Energy Technology (ZET), Universität Bayreuth, Universitätsstr. 30, 95447 Bayreuth, Germany)

Abstract

The increasing market share of electric vehicles and the politically intended phase-out of the internal combustion engine require reliable and realistic predictions for future consumption and greenhouse gas emissions as a function of technological solutions. This also includes the consumption- and emission-intensive transport of goods. We consider both passenger vehicles and commercial vehicle traffic in our study and have investigated whether there are drive alternatives to the battery electric vehicle that enable uninterrupted trips with a long range, especially for regional delivery services and internationally active freight forwarders. To this end, we have analysed three system architectures and their expected technological progress until 2050: battery electric vehicles (BEV), fuel cell electric vehicles (FCEV), and internal combustion engine vehicles (ICEV) running on compressed natural gas (CNG). The latter case serves as a best-practice reference from a combustion technology perspective. The analysis is based on a validated and proven physical model and predicts that the BEV2050 will consume 3.5 times less energy and emit 15 times fewer greenhouse gases than the ICEV-CNG2020, whereas the FCEV2050 will consume 2.5 times less energy and emit 6.5 times fewer greenhouse gases than the ICEV-CNG2020 on the road (hilly terrain, transition season, and WLTP triple-mixed drive cycle). The advantages of the BEV result from the shorter drive train with lower total losses. Our results thus confirm the expected role of the BEV as the dominant drive technology in the future, and light vehicles with low-to-medium-range requirements will especially benefit from it. On the other hand, since the greenhouse gas emissions of the FCEV2050 are lower by a factor of 6.5 than those of the ICEV-CNG2020, it is reasonable to conclude that the FCEV can play a significant role in transport until 2050 when long distances have to be covered. Our model-based approach also allows us to determine the energy fractions of the acting physical forces and thus calculate the consumption shares: electric drive recuperation increases BEV and FCEV range by about 15% in 2020 and will increase it by about 20% in 2050, depending on drive technology and vehicle type. Air and rolling resistance contribute 20% each to the total consumption. The consumption of the accessories of modern vehicles with a share of about 10% of the total consumption cannot be neglected.

Suggested Citation

  • Manfred Dollinger & Gerhard Fischerauer, 2023. "Physics-Based Prediction for the Consumption and Emissions of Passenger Vehicles and Light Trucks up to 2050," Energies, MDPI, vol. 16(8), pages 1-29, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3591-:d:1129261
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    1. Simon Randau & Dominik A. Weber & Olaf Kötz & Raimund Koerver & Philipp Braun & André Weber & Ellen Ivers-Tiffée & Torben Adermann & Jörn Kulisch & Wolfgang G. Zeier & Felix H. Richter & Jürgen Janek, 2020. "Benchmarking the performance of all-solid-state lithium batteries," Nature Energy, Nature, vol. 5(3), pages 259-270, March.
    2. Tri Cuong Do & Hoai Vu Anh Truong & Hoang Vu Dao & Cong Minh Ho & Xuan Dinh To & Tri Dung Dang & Kyoung Kwan Ahn, 2019. "Energy Management Strategy of a PEM Fuel Cell Excavator with a Supercapacitor/Battery Hybrid Power Source," Energies, MDPI, vol. 12(22), pages 1-24, November.
    3. Sara Luciani & Andrea Tonoli, 2022. "Control Strategy Assessment for Improving PEM Fuel Cell System Efficiency in Fuel Cell Hybrid Vehicles," Energies, MDPI, vol. 15(6), pages 1-17, March.
    4. José Luis Sampietro & Vicenç Puig & Ramon Costa-Castelló, 2019. "Optimal Sizing of Storage Elements for a Vehicle Based on Fuel Cells, Supercapacitors, and Batteries," Energies, MDPI, vol. 12(5), pages 1-27, March.
    5. Jacek Pielecha & Kinga Skobiej & Karolina Kurtyka, 2020. "Exhaust Emissions and Energy Consumption Analysis of Conventional, Hybrid, and Electric Vehicles in Real Driving Cycles," Energies, MDPI, vol. 13(23), pages 1-21, December.
    6. Min Soo Kim & Joo Hee Song & Dong Kyu Kim, 2020. "Development of Optimal Conditioning Method to Improve Economic Efficiency of Polymer Electrolyte Membrane (PEM) Fuel Cells," Energies, MDPI, vol. 13(11), pages 1-11, June.
    7. Manfred Dollinger & Gerhard Fischerauer, 2021. "Model-Based Range Prediction for Electric Cars and Trucks under Real-World Conditions," Energies, MDPI, vol. 14(18), pages 1-27, September.
    8. Cedric De Cauwer & Joeri Van Mierlo & Thierry Coosemans, 2015. "Energy Consumption Prediction for Electric Vehicles Based on Real-World Data," Energies, MDPI, vol. 8(8), pages 1-21, August.
    9. Gert Berckmans & Maarten Messagie & Jelle Smekens & Noshin Omar & Lieselot Vanhaverbeke & Joeri Van Mierlo, 2017. "Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030," Energies, MDPI, vol. 10(9), pages 1-20, September.
    10. Eugenio Meloni & Giuseppina Iervolino & Concetta Ruocco & Simona Renda & Giovanni Festa & Marco Martino & Vincenzo Palma, 2022. "Electrified Hydrogen Production from Methane for PEM Fuel Cells Feeding: A Review," Energies, MDPI, vol. 15(10), pages 1-34, May.
    11. Christoph Kern & Andreas Jess, 2021. "Reducing Global Greenhouse Gas Emissions to Meet Climate Targets—A Comprehensive Quantification and Reasonable Options," Energies, MDPI, vol. 14(17), pages 1-21, August.
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    1. Gábor Horváth & Attila Bai & Sándor Szegedi & István Lázár & Csongor Máthé & László Huzsvai & Máté Zakar & Zoltán Gabnai & Tamás Tóth, 2023. "A Comprehensive Review of the Distinctive Tendencies of the Diffusion of E-Mobility in Central Europe," Energies, MDPI, vol. 16(14), pages 1-29, July.

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