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CMU study finds driving conditions have “substantial” impact on benefits of electrified vehicles; policy implications

NHTS-Averaged Annual GHG Emissions per vehicle type by drive cycle. (Base Case). Source: Karabasoglu and Michalek. Click to enlarge.

A new analysis by Orkun Karabasoglu and Jeremy Michalek of the Carnegie Mellon Vehicle Electrification Group at Carnegie Mellon University found that driving conditions affect the economic and environmental benefits of electrified vehicles “substantially”.

As a result, they suggested, vehicle window stickers, fuel economy standards, and life cycle studies using average lab-test vehicle efficiency estimates are incomplete. Driver heterogeneity matters, they found, and efforts to encourage adoption of hybrid and plug-in vehicles will have greater impact if targeted to urban drivers vs. highway drivers. Further, electrified vehicles perform better on some drive cycles than others, so non-representative tests can bias consumer perception and regulation of alternative technologies. Their study is published in the journal Energy Policy.

The fuel economy and emissions of vehicles depend on the way they are driven, including daily driving distance and driving conditions. Official fuel economy ratings are based on standard test driving conditions—called a driving cycle—but real-world driving patterns can vary substantially from standard test cycles, leading real-world costs and emissions to deviate from those estimated on window stickers or in life cycle studies.

In the literature, vehicle life cycle assessment and design optimization studies are typically conducted using efficiency estimates from federal test cycles, with results that favor certain powertrains over others. In this paper, we investigate variation in life cycle cost and emission benefits of hybrid and plug-in vehicles under a range of driving conditions with a sensitivity analysis to critical factors such as gasoline prices, vehicle costs and electricity grid mix.

Specifically, we compare conventional vehicle (CV), hybrid electric vehicle (HEV), PHEV, and BEV powertrain technologies and identify changes in all-electric range (AER), vehicle efficiency, and battery life, under a variety of driving patterns to determine the most cost effective and lowest GHG-intensive powertrains. Then we discuss the energy policy implications of our findings considering multiple scenarios related to market, vehicle technology, and electricity grid mix.

—Karabasoglu and Michalek

They used the Powertrain Systems Analysis Toolkit (PSAT) SP1 Version 6.2, developed by Argonne National Laboratory (2008), to model conventional, hybrid, plug-in hybrid, and battery electric vehicles with identical body characteristics, comparable control strategies, and comparable performance characteristics. They simulated each vehicle over a range of drive cycles to compare vehicle efficiency and life cycle implications.

In the analysis, they accounted for battery degradation, different daily driving distances and different scenarios for costs, vehicle technology and electricity grid.

The battery degradation model was based on laboratory-tested A123 LiFePO4 cells at room temperature. The data ignore temperature variation and calendar fade, they do not account for the higher C-rate implied by more aggressive driving cycles, and they do not examine other chemistries, which can have degradation characteristics more sensitive to state of charge and other factors.

Degradation also affects vehicle performance, which can prevent the vehicle from satisfying some drive cycles and acceleration tests later in the vehicle’s life.

The team assumed a single charge per day for the PHEV simulations, and ignored range limitations of the BEV100. Multiple daily charges would increase the benefits of PHEVs and extend the applicability of BEVs.

They also ignored differences in maintenance, insurance and charging infrastructure costs across vehicle types and focused only on the split hybrid drivetrain—results for series and parallel designs and for blended control strategies may vary somewhat, they noted.

They also ignored any salvage value of the battery pack at end of life as well as opportunities for energy arbitrage in vehicle-to-grid applications. They accounted only for GHG emissions and ignored other life cycle emissions and impacts, and assumed that CO2 tax costs are passed through the supply chain to the vehicle customer.

They ignored government subsidies—which reduce costs observed by consumers but transfer these costs to taxpayers rather than eliminating them. With government subsidies, plug-in vehicles are somewhat more attractive purchase options for consumers, they noted.

They also noted that advancements in technology and other changes, such as gasoline prices, grid mix, vehicle efficiency, driving patterns, and public policy will affect cost and environmental comparisons in the future.

Among their findings:

  • Michalek
    All-electric range for different types of plug-ins under different drive cycles. Source: Karabasoglu and Michalek. Click to enlarge.

    All-electric range (AER). Karabasoglu and Michalek found that driving patterns affect AER significantly. An aggressive driving cycle (US06) can reduce AER by 45% relative to a gentle cycle (UDDS). As one example, a PHEV with a split powertrain designed to achieve a 70-mi AER on the UDDS drive cycle provides only a 40 mi AER under the US06 drive cycle.

    Reduced range is particularly important for BEVs, they noted, but reduced range also affects life cycle cost and emissions of PHEVs and can negatively affect customer satisfaction and perception of plug-in vehicle technology. The vehicles components of this study were sized to satisfy the target AER under the EPA combined mpg (2008+) which adjusts FTP and HWFET test results to estimate outcomes from a 5-cycle test, which results in lower efficiency estimates and thus AER.

  • Life-cycle cost. Under HWFET, US06 and the EPA-5 cycle, the conventional vehicle (CV) is the cost minimum followed closely by the hybrid (HEV); under the UDDS and NYC driving cycles the HEV minimizes cost. CV is the most sensitive to driving cycle, especially stop-and-go driving and traffic conditions.

    Electrified vehicles are less sensitive to drive cycle. In the base case, plug-in vehicles are consistently more expensive than HEVs over the life, primarily due to the cost of larger battery packs, and only in NYC conditions is the PHEV20 lower cost than the CV.

    The BEV powertrain cost is least sensitive to drive cycle because electricity consumption is a small portion of overall cost, and regenerative braking together with the lack of an idling gasoline engine makes electrified powertrains less sensitive to stopping frequency. The cost associated with CV is 30% higher under NYC conditions than under HWFET conditions.

  • Life-cycle greenhouse gas emissions. Increased battery size results in greater displacement of gasoline with electricity; however, battery production emissions also increase, and vehicle efficiency decreases with vehicle mass. This results in increased GHG emissions of longer-range PHEVs with average US electricity.

    Under HWFET conditions all powertrains produce comparable life cycle emissions. In all other conditions, hybrid and electric vehicles release significantly lower GHGs than CV—in particular, HEVs reduce emissions by 60% relative to CV in the NYC cycle.

    In the base case, plug-in vehicles do not provide substantial GHG reductions relative to HEVs except for the BEV100 in the EPA 5-cycle, which may be optimistic due to application of EPA regression equations to electric operation.

  • Base case cost and GHG comparison. Drive cycles with more aggressive acceleration demands and more stops increase both cost and emissions simultaneously, they found. The CV is much more sensitive to drive cycle, whereas the electrified powertrains experience less variation with drive cycle.

    A move from CV to HEV with larger battery packs reduces GHG emissions at no cost or at modest cost, depending on the drive cycle. A move from HEV to the plug-in powertrains with larger battery packs reduces or increases GHGs, depending on the vehicle and drive cycle, but comes at a substantial increase in costs.

  • Cost and GHGs per mile for different daily driving distances and patterns. PHEVs with small battery packs have lower emissions when charged frequently and driven primarily in charge-depleting (CD) mode but may have higher emissions if charged infrequently.

    The cost curves show a decline of annualized cost/ mile with daily driving distance, which results from capital cost of initial vehicle and battery purchase comprising a larger portion of total cost for short daily driving distances, which imply long vehicle life and discounted future fuel costs.

    Under NYC conditions, HEV and PHEV20 are lower cost than CV. In both cases, BEVs increase the costs significantly.

With the introduction of hybrid and plug-in vehicles, it has become more important that the right vehicles are targeted to the right drivers. Drivers who travel in NYC conditions could cut lifetime costs by up to 20% and cut GHG emissions 60% by selecting hybrid vehicles instead of conventional vehicles, while for HWFET drivers conventional vehicles provide a lower cost option with a much smaller GHG penalty. CV owners observe more variability in cost and emissions subject to driving conditions, while HEVs offer the most robust, cost effective configuration across the driving patterns tested.

When comparing HEVs to PHEVs under the average US grid mix, it is clear that most of the GHG-reduction benefit of PHEVs comes from hybridization, and relatively little additional benefit can be achieved through plugging in. HEVs provide an optimal or near optimal economic and environmental choice for any driving cycle. However, given a substantially decarbonized electricity grid plug-in vehicles could reduce life cycle GHG emissions across all driving cycles, and lower battery costs combined with high gasoline prices would make plug-in vehicles more economically competitive.

—Karabasoglu and Michalek

Policy implications. Karabasoglu and Michalek suggested that their results have several key policy implications:

  • The benefits of plug-in vehicles vary dramatically from driver to driver depending on drive cycle (driving style, traffic, road networks, etc.). While hybrid and plug-in vehicles offer little GHG benefit at higher cost for highway driving (HWFET), they can offer dramatic GHG reductions and cost savings in NYC-cycle-style driving with frequent stops and idling.

    Electrification will have more positive impact if targeted to drivers who travel primarily in NYC-like conditions rather than HWFET-like conditions, they suggested, noting that government could play a role through information campaigns, driver education, as well as modifying fuel economy labels to help target the right drivers.

  • The choice of standardized test used to assess vehicle efficiency for window labels and for CAFE standards can have an important effect on the measured benefit of hybrid and plug-in vehicles relative to conventional vehicles.

    While choice of testing protocol has always had impact on the relative benefits of vehicles, the unique features of hybrid and electric vehicle powertrains and their importance in certain types of driving amplify this impact and the potential for bias that could systemically underestimate the benefits of hybridization and electrification, influencing adoption rates and corporate strategy for compliance with CAFE standards.

    —Karabasoglu and Michalek

    With the presence of hybrid and electric vehicles in the marketplace, the test cycles used to assess fuel efficiency should be reexamined to minimize bias, they suggested.

    In particular, CAFE standards are still based on old UDDS and HWFET tests that produce estimates with about 20% lower fuel consumption for CV, 30% lower for HEV, and 40% lower for plug-in vehicles than the EPA 5-cycle regression tests. The CAFE measurement is about 60% lower fuel consuming for CVs and 30% lower for hybrid and electric vehicles than the NYC test. The CAFE tests artificially inflate fuel economy estimates and do so unevenly for different vehicle technologies. Using a common test for CAFE standards and window labels—one that is as representative as possible of the resulting efficiency experienced by US drivers across vehicle technologies—would help reduce bias against certain technologies as well as confusion about why the high fuel efficiency standards cited by politicians fail to match the reality of the vehicle fleet observed by consumers.

    —Karabasoglu and Michalek

  • As suggested in prior studies, HEVs and small-battery PHEVs provide comparable GHG reductions at lower cost than large-battery PHEVs or BEVs with today’s electricity grid. This holds true across the driving cycles tested.

    In particular, in NYC conditions HEVs show the lowest cost and GHG emissions. This is because hybridization (regenerative braking, efficient engine operation, Atkinson cycle, engine off at idle, etc.) offers most of the GHG benefit, and additional benefits of using electricity rather than gasoline as the energy source are dependent on grid decarbonization. Current federal and state policy favors large battery packs, but this is misaligned with potential for GHG reductions. In fact, given binding CAFE standards plug-in vehicle subsidies may produce no net benefit unless they succeed in stimulating a breakthrough that leads to cost competitive plug-in vehicles and sustainable mainstream adoption that would not have happened otherwise.

    —Karabasoglu and Michalek

  • Government fleet purchases should account for the anticipated driving conditions of vehicles when selecting powertrain type.


  • Karabasoglu, O., Michalek, J. (2013) Influence of driving patterns on life cycle cost and emissions of hybrid and plug-in electric vehicle powertrains. Energy Policy doi: 10.1016/j.enpol.2013



Of course, adding the additional information recommended on the fuel economy label means not just complicating the label and the testing behind it, but making use of it means asking drivers to rate their own driving style.

Bob Wallace

Perhaps we need an easy to use web site that lets people enter their driving particulars along with gas/electricity prices and get suggestions as to which electrics might save them money.

People could narrow down their choices before going to the dealerships.

Jim McLaughlin

Another report from the Institute for Studies of Things We Already Know.

But that is what science is about half the time. Just making sure.



No mention of diesel.
I suppose it would be like CV on steroids.
You could make an app for a smartphone which would measure the acceleration etc of the car and estimate your driving style over (say) a month.
Then it would recommend what to get.
But anyone who goes to that amount of trouble will probably just get a hybrid.
(or a diesel if the live in Europe).

Kit P

"Another report from the Institute for Studies of Things We Already Know."

Who is 'we' Jim? There a lot who post here that BEV are efficient no matter how they are used, or BEV will save money, or BEV will reduce ghg.

The purpose of this paper is a learning exercise for college students. There is nothing wrong with that. When I went to grand school I did a LCA. Now I an able to better understand how we can reduce environmental impact of producing and using energy.

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