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Gasoline Hybrid

Gasoline hybrid electric vehicles use both an internal combustion engine that uses gasoline and an electric motor (or motors). Electrical energy for the motors is stored as chemical energy in batteries. They have high fuel economy and low tailpipe emissions, with power and range comparable to conventional vehicles (DOE, 2019). For additional information, see the Alternative Fuels Data Center's Hybrid Electric Vehicles webpage.

On this page, explore key cost and performance metrics for gasoline hybrid electric vehicles, including modeled vehicle price, fuel economy, levelized cost of driving, and emissions. Caveats for comparing powertrains are listed on the Light-Duty Vehicle Comparison page.

Vehicle Metrics: Fuel Economy and Modeled Vehicle Price

The chart below shows fuel economy and modeled vehicle price, metrics associated with the vehicle. Fuel economy represents how efficiently a vehicle converts fuel during operation. Modeled vehicle price represents an estimated cost to the consumer to purchase a new vehicle, based on modeling that includes manufacturing costs and profit.

The source of the 2022 Transportation ATB modeled vehicle price and fuel economy is the Argonne National Laboratory report (Islam et al., 2022); the original data are available here. These data are developed using ANL's Autonomie simulation tool.

Select the data to display using the menus above the chart. Use the Metric filter to switch between fuel economy and modeled vehicle cost. Select the vehicle class, powertrain, and other powertrain details using the additional filters.

Vehicle and Fuel Metrics: Levelized Cost of Driving and CO2e Emissions

The chart below shows levelized cost of driving and CO2emissions, in addition to the associated fuel data. Levelized cost of driving is a metric that combines modeled vehicle price, fuel economy, fuel cost, and other assumptions for the selected fuel. CO2e emissions represents the emissions for the fuel well-to-wheels portion of the life cycle for the selected fuel. Emissions associated with vehicle life cycles are not included here.  

These calculations use data from Argonne National Laboratory, which develops and applies the Autonomie simulation tool and GREET model (Wang et al., 2022). Links to data from the Argonne National Laboratory report (Islam et al., 2022) on modeled vehicle price and fuel economy are available here.   

Select the data to display using the buttons and menus to the above the chart. Use the Metric filter to switch between levelized cost of driving and CO2e emissions data. Select the pathway, scenario, vehicle class and powertrain details using the additional filters. Clicking the black arrows on the top right of the figure shows additional details of the selected fuel pathways. The source underlying for a data point in the chart can be seen by placing your mouse cursor over that data point. The data sources are also cited—with hyperlinked linked references—in the Key Assumptions section below.

Notes:

Key Assumptions

The data and estimates presented here are based on the following key assumptions:

  • Fuel Economy Improvements: The assumptions about fuel economy improvements reflect adoption of lightweighting and engine efficiency technologies consistently across vehicle powertrains for a given trajectory; they do not account for the trade-offs between efficiency and performance in various vehicle markets. 
  • Cost and Fuel Economy Trajectories: The cost and fuel economy trajectories are based on the analysis-year Autonomie modeling results from Islam et al. (Islam et al., 2022). The ATB Advanced trajectory corresponds to the Base performance, High technology progress case. The ATB Mid trajectory corresponds to the Base performance, Low technology progress case. The ATB Constant trajectory is set to the 2022 values in the Base performance, Low technology progress case and held constant through 2050.
  • Powertrain Detail Filter: The Powertrain Detail filter allows for selection of multiple powertrain configurations. For full descriptions of alternative configurations, refer to documentation by Islam et al. (Islam et al., 2022).
  • High Production Volume: The estimates from Islam et al. (Islam et al., 2022), and those shown here, represent costs and technology performance at high production volume. Gasoline hybrid electric vehicles are currently manufactured at high volume, and the high-volume estimates should therefore reflect the current state of technology.
  • Vehicle Variations: The Transportation ATB presents estimates for a representative light-duty vehicle; we do not account for variations in make, model, and trim or for pricing incentives or geographic heterogeneity that influence prices in the market. As a result, representative values shown here may differ from specific models available on the market.
  • Technology Advances: Technology advances include changes that may reduce costs or may increase costs while improving performance, which implies costs do not always decline between less- and more-advanced scenarios.
  • Non-Monotonic Behavior: Modeled vehicle price trajectories may exhibit non-monotonic behavior resulting from the combination of advanced technology costs and the impact on engine efficiency. For example, though the engine cost might increase over time due to advanced technologies, the overall engine power required decreases over time due to lightweighting, improved aerodynamics, or other factors. As a result, though per unit of power engine costs might go up, lower engine power requirements decrease the total engine cost.
  • Baseline Fuel Pathway: The baseline fuel pathway used for this powertrain in the levelized cost of driving and emissions estimates is conventional E10 gasoline with starch ethanol. Additional selected fuel pathways can be displayed by choosing Lowest Cost or Lowest Emissions under the Fuel Pathway filter. Additional information about these and other fuels can be found on the Gasoline and Ethanol page.
  • Frozen Fuel Price Level: The fuel price and emissions of the selected fuel pathways (e.g., Baseline, Lowest Cost, and Lowest Emissions) are associated with a single year. Because we do not provide a time-series trajectory, here we show fuel price at a frozen level for all years so we can offer a range of fuel price values. In the levelized cost of driving and emissions charts, this approach clearly distinguishes effects of fuels from those of vehicle technologies, because fuels remain constant while vehicle technologies change over time.
  • Fuels References: See fuels and blendstock pages, especially for ethanol and BOB for a full description of fuels references. Those for ethanol include (EIA, 2021)(Elgowainy et al., 2016)(Dutta et al., 2011)(Wang et al., 2022)(Lee et al., 2021)(Humbird et al., 2011)(Tao et al., 2014), and (Dunn et al., 2013). Those for BOB include (EIA, 2020),  (EIA, 2021) , and (Wang et al., 2022).
  • Fuel Economy on Substitutable Fuels: The Transportation ATB assumes the fuel economy (on a miles per gallon gasoline equivalent basis) remains constant when operating on substitutable fuels (e.g., conventional E10 gasoline versus reformulated E15 gasoline). In reality, fuel composition may affect engine performance.

The data downloads include additional details of assumptions and calculations for each metric.

Definitions

For detailed definitions, see:

Emissions

Fuel economy

Levelized cost of driving

Scenarios

Modeled Vehicle Price

Vehicle Range

References

The following references are specific to this page; for all references in this ATB, see References.

DOE. “Alternative Fuels Data Center,” 2019. https://afdc.energy.gov/.

Islam, Ehsan Sabri, Ram Vijayagopal, Benjamin Dupont, Namdoo Kim, Ayman Moawad, Daniela Nieto Prada, and Aymeric Rousseau. “A Comprehensive Simulation Study to Evaluate Future Vehicle Energy and Cost Reduction Potential.” Report to the US Department of Energy. Argonne National Laboratory, June 2022. https://vms.taps.anl.gov/research-highlights/u-s-doe-vto-hfto-r-d-benefits/.

Wang, Michael, Amgad Elgowainy, Uisung Lee, Kwang Hoon Baek, Adarsh Bafana, Pahola Thathiana Benavides, Andrew Burnham, et al. “Summary of Expansions and Updates in GREET® 2022.” Argonne National Lab. (ANL), Argonne, IL (United States), October 1, 2022. https://doi.org/10.2172/1891644.

EIA. “Annual Energy Outlook 2021.” Washington, D.C.: U.S. Energy Information Administration, February 2021. https://www.eia.gov/outlooks/aeo/.

Elgowainy, Amgad, Jeongwoo Han, Jacob Ward, Fred Joseck, David Gohlke, Alicia Lindauer, Todd Ramsden, et al. “Cradle-to-Grave Lifecycle Analysis of U.S. Light-Duty Vehicle-Fuel Pathways: A Greenhouse Gas Emissions and Economic Assessment of Current (2015) and Future (2025–2030) Technologies,” September 1, 2016. https://doi.org/10.2172/1324467.

Dutta, A., M. Talmadge, J. Hensley, M. Worley, D. Dudgeon, D. Barton, P. Groendijk, et al. “Process Design and Economics for Conversion of Lignocellulosic Biomass to Ethanol: Thermochemical Pathway by Indirect Gasification and Mixed Alcohol Synthesis.” Golden, CO (United States): National Renewable Energy Laboratory, May 1, 2011. https://doi.org/10.2172/1015885.

Lee, Uisung, Hoyoung Kwon, May Wu, and Michael Wang. “Retrospective Analysis of the U.S. Corn Ethanol Industry for 2005–2019: Implications for Greenhouse Gas Emission Reductions.” Biofuels, Bioproducts, and Biorefining 15, no. 5 (2021): 1318–31. https://doi.org/10.1002/bbb.2225.

Humbird, D, R Davis, L Tao, C Kinchin, D Hsu, A Aden, P Schoen, et al. “Process Design and Economics for Biochemical Conversion of Lignocellulosic Biomass to Ethanol: Dilute-Acid Pretreatment and Enzymatic Hydrolysis of Corn Stover,” March 1, 2011. https://doi.org/10.2172/1013269.

Tao, L., D. Schell, R. Davis, E. Tan, R. Elander, and A. Bratis. “NREL 2012 Achievement of Ethanol Cost Targets: Biochemical Ethanol Fermentation via Dilute-Acid Pretreatment and Enzymatic Hydrolysis of Corn Stover,” April 1, 2014. https://doi.org/10.2172/1129271.

Dunn, Jennifer, Michael Johnson, Zhichao Wang, Michael Wang, Kara Cafferty, Jake Jacobson, Erin Searcy, et al. “Supply Chain Sustainability Analysis of Three Biofuel Pathways: Biochemical Conversion of Corn Stover to Ethanol Indirect Gasification of Southern Pine to Ethanol Pyrolysis of Hybrid Poplar to Hydrocarbon Fuels.” Argonne, IL (United States): Argonne National Laboratory, November 2013. https://publications.anl.gov/anlpubs/2014/07/78878.pdf.

EIA. “U.S. Gasoline and Diesel Retail Prices,” July 13, 2020. https://www.eia.gov/dnav/pet/pet_pri_gnd_dcus_nus_a.htm.

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