The findings of the study, they suggest, both demonstrate the important interactions between driving patterns and the electricity generation supply that affect WTW energy use and GHG emissions of PHEVs and thus have implications for informing environmentally beneficial usage and adoption patterns for these vehicles.

For the study, they developed well-to-wheel models to investigate energy use and GHG emissions of a PHEV, HEV (hybrid electric vehicle), and conventional internal combustion engine vehicle (ICEV). They considered four different electricity generation scenarios:

1. 100% hydroelectric
2. 100% natural gas (combined cycle)
3. 100% coal (pulverized coal boiler)
4. Current average Ontario electricity generation mix, based on the Province’s 2010 electrical energy output by fuel type, which was 55% nuclear, 20% hydroelectric, 14% natural gas boiler, 8% coal, 2% wind, and 1% biomass.

They also used three categories of driving cycles:

1. City (C): short distance, low speed, congested; no highway driving.
2. Suburban (SU): intermediate distance, speed, and congestion; some congested highway driving.
3. Highway (HWY): long distance, high speed, and uncongested; primarily uncongested highway driving.

Within each category, distance varied (e.g., C1 is shorter than C2, which is shorter than C3). As driving cycle distance increases, driving speed also increases and the coefficient of variation of speed and number of stops in the driving cycle decrease. For C1 (the shortest driving cycle), driving distance is 20 km, average speed is 29 km/h, coefficient of variation of speed is 58%, and there are 29 stops; for HWY2 (the longest driving cycle), driving distance is 68 km, average speed is 94 km/h, coefficient of variation of speed is 31%, and there are two stops.

For each driving cycle, they used the Autonomie vehicle simulation software to estimate the fuel efficiency of the PHEV, HEV, and ICEV. For their study, as in their previous work, they used an 8 kWh intermediate battery capacity.

(Results for a similar PHEV with a 16 kWh battery (generally resembling the 2011 Chevrolet Volt) and a PHEV with a split drivetrain configuration and blended mode control strategy (generally resembling the plug-in Toyota Prius) are provided in the paper’s Supporting Information.)

Among their findings were:

• Regardless of the charging scenario, total energy use of the PHEV is lowest for the city driving patterns (C1−C3) and generally highest for the highway driving patterns (HWY1-HWY2). Regardless of the driving pattern, total energy use of the PHEV is lowest for the hydroelectric scenario and highest for the coal scenario.

• For the hydroelectric scenario, total energy use is 59% lower for C1 than for HWY2, whereas for the coal scenario total energy use is only 29% lower. I.e., driving distance can have a large impact on total energy use of PHEVs when charging from hydroelectricity, but a much smaller impact when charging from coal-based electricity.

• For the coal scenario, total energy use of the PHEV is essentially the same as that of the HEV for all driving patterns.

• PHEVs charging from coal-based electricity use less total energy than ICEVs for the city and suburban driving patterns, but these reductions occurs due to differences in fuel efficiency between the vehicles and not due to electric propulsion.

• For the hydroelectric scenario, fossil energy use is 81% lower for C1 than for HWY2. For the coal and natural gas scenarios, fossil and total energy use of electric propulsion are essentially equal because almost all energy used in those electricity pathways is fossil based.

• Petroleum energy use of the PHEV is insensitive to the electricity generation scenario due to the small amount of petroleum used in all examined electricity scenarios. For C1, petroleum energy use of the PHEV is 82% and 89% lower than that of the HEV and ICEV, respectively; however, for HWY2, petroleum energy use of the PHEV is only 27% and 30% lower than that of the HEV and ICEV.

• As with total and fossil energy use, GHG emissions of the PHEV are lowest for the city driving patterns with hydroelectric charging and are generally highest for the highway driving patterns with coal charging.

• For all charging scenarios except for coal, reductions in GHG emissions relative to the non-plug-in alternatives are highest for the city but occur for all driving patterns. For the coal scenario, GHG emissions of the PHEV are consistently higher than those of the HEV and are higher than those of the ICEV for the highway driving patterns.

This study demonstrates important interactions between driving patterns and the electricity generation supply that affect WTW energy use and GHG emissions of PHEVs and have implications for informing environmentally beneficial usage and adoption patterns for these vehicles.

Regardless of the electricity generation supply, city driving conditions (i.e., low speed and congested) result in lower WTW energy use and GHG emissions of PHEVs and larger reductions in these metrics relative to ICEVs than highway conditions (i.e., high speed and uncongested). Frequent charging (i.e., short distance driving) results in the lowest WTW energy use and GHG emissions of PHEVs in regions that have ‘favorable’ electricity generation supplies (i.e., energy efficient, low fossil energy, low GHG emissions) but can increase GHG emissions in regions dominated by coal facilities.

Within regions, PHEVs can have lower energy use and GHG emissions if charging occurs when the marginal electricity generation supply is favorable (e.g., natural gas on the margin in a region otherwise dominated by coal). Regions in which PHEVs achieve significant market penetration can reduce the energy use and GHG emissions of the light-duty vehicle fleet by advocating or incentivizing charging during these periods and by investing in favorable electricity generation facilities. Under coal charging, PHEVs do not reduce WTW energy use and GHG emissions relative to HEVs or ICEVs due to electric mode driving but can reduce WTW energy use and GHG emissions relative to ICEVs under relatively favorable driving conditions. However, under those electricity generation scenarios, HEVs can achieve similar energy use reductions and greater GHG emissions reductions at lower cost to the consumer.

—Raykin et al.

Resources

• Leon Raykin, Heather L. MacLean, and Matthew J. Roorda (2012) Implications of Driving Patterns on Well-to-Wheel Performance of Plug-in Hybrid Electric Vehicles. Environmental Science & Technology doi: 10.1021/es203981a