Hybrid-Electric Passenger Car Carbon Dioxide and Fuel Consumption Benefits Based on Real-World Driving

Abstract

Hybrid-electric vehicles (HEVs) have lower fuel consumption and carbon dioxide (CO2) emissions than conventional vehicles (CVs), on average, based on laboratory tests, but there is a paucity of real-world, on-road HEV emissions and performance data needed to assess energy use and emissions associated with real-world driving, including the effects of road grade. This need is especially great as the electrification of the passenger vehicle fleet (from HEVs to PHEVs to BEVs) increases in response to climate and energy concerns. We compared tailpipe CO2 emissions and fuel consumption of an HEV passenger car to a CV of the same make and model during real-world, on-the-road network driving to quantify the in-use benefit of one popular full HEV technology. Using vehicle specific power (VSP) assignments that account for measured road grade, the mean CV/HEV ratios of CO2 tailpipe emissions or fuel consumption defined the corresponding HEV "benefit" factor for each VSP class (1 kW/ton resolution). Averaging over all VSP classes for driving in all seasons, including temperatures from -13 to +35 °C in relatively steep (-13.2 to +11.5% grade), hilly terrain, mean (±SD) CO2 emission benefit factors were 4.5 ± 3.6, 2.5 ± 1.7, and 1.4 ± 0.5 for city, exurban/suburban arterial and highway driving, respectively. Benefit factor magnitude corresponded to the frequency of electric-drive-only (EDO) operation, which was modeled as a logarithmic function of VSP. A combined model explained 95% of the variance in HEV benefit for city, 75% for arterial and 57% for highway driving. Benefit factors consistently exceeded 2 for VSP classes with greater than 50% EDO (i.e., only city and arterial driving). The reported HEV benefits account for real-world road grade that is often neglected in regulatory emissions and fuel economy tests. Fuel use HEV benefit factors were 1.3 and 2 for the regulatory highway (HWFET) and city (FTP) cycles, respectively, 18% and 31% higher than the EPA adjusted fuel economy values. This study establishes the significant need for high-resolution vehicle activity and road grade data in transportation data sets to accurately forecast future petroleum and GHG emissions savings from hybridization of the passenger vehicle fleet.

Development of Hybrid-Vehicle Energy-Consumption Model for Transportation Applications—Part I: Driving-Power Equation Development and Coefficient Calibration

“…Since 1999, a great number of studies have applied the conventional VSP equation and coefficients for LDV to estimate the driving power of passenger cars regardless of vehicle model and technology. VSP has been utilized to estimate driving power to construct fuel-consumption and -emission models, and conduct further analysis on the influential factors or contributors to vehicle fuel consumption [1,3,[7][8][9][10][11][12][13][14][15][16][17][18][19]. Nevertheless, before implementing the VSP equation and the LDV coefficients, none of them has performed validation to confirm prediction accuracy of whether the equation and coefficients estimated by the vehicles from the last 20 years can still accurately capture a vehicle or studied vehicle fleet.…”

Development of Hybrid Vehicle Energy Consumption Model for Transportation Applications—Part II: Traction Force-Speed Based Energy Consumption Modeling

“…In the past decades, a number of researchers have been applying vehicle fuel consumption models to transportation research such as prediction and analysis. The conventional approach of vehicle fuel consumption modeling consists of two main processes, which are vehicle driving power estimation, and fuel consumption and driving power relationship construction [2,[7][8][9][10][11][12][13][14][15]. In 1999, Jiménez et al [16] derived an equation for vehicle driving power estimation, and also provided a set of coefficients specified for light-duty vehicles' (LDVs) application called vehicle-specific power (VSP).…”

“…The equation simply requires data that can be observed from outside of the vehicles, such as speed, acceleration, road grade, and wind speed. Furthermore, a large number of researchers adopting VSP in their research have reported on the monotonically increasing relationship between VSP and fuel consumption [2,[7][8][9][10][11][12][13][14][15][16][17][18].…”

“…Holmén and Sentoff [14] utilized the conventional VSP equation with LDV coefficients and the 1-kW VSP binning method to analyze the benefit of hybrid vehicles compared to internal combustion engine vehicles. This study separated the model into three driving scenarios-city, suburban, and highway-in an attempt to investigate the benefit factors for hybrid vehicles' fuel savings at each driving scenario.…”

Reducing Mobile Air Conditioner (MAC) Power Consumption Using Active Cabin-Air-Recirculation in A Plug-In Hybrid Electric Vehicle (PHEV)

“…New government regulations have demanded an increase in automotive fuel economy (MPG-miles per gallon) to reduce dependency on imported oil for transportation [1,2]. This not only pushed automotive manufacturers to improve the efficiency of the powertrain design, but they also had to consider improving other components and systems in the vehicle.…”