Current and Future United States Light-Duty Vehicle Pathways: Cradle-to-Grave Lifecycle Greenhouse Gas Emissions and Economic Assessment.

Greenhouse gas emissions of conventional and alternative vehicles: Predictions based on energy policy analysis in South Korea

Plug-in hybrid electric vehicles (PHEVs) are being developed for mass production by the automotive industry. PHEVs have been touted for their potential to reduce the US transportation sector's dependence on petroleum and cut greenhouse gas (GHG) emissions by (1) using off-peak excess electric generation capacity and (2) increasing vehicles energy efficiency. A well-to-wheels (WTW) analysis - which examines energy use and emissions from primary energy source through vehicle operation - can help researchers better understand the impact of the upstream mix of electricity generation technologies for PHEV recharging, as well as the powertrain technology and fuel sources for PHEVs. For the WTW analysis, Argonne National Laboratory researchers used the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model developed by Argonne to compare the WTW energy use and GHG emissions associated with various transportation technologies to those associated with PHEVs. Argonne researchers estimated the fuel economy and electricity use of PHEVs and alternative fuel/vehicle systems by using the Powertrain System Analysis Toolkit (PSAT) model. They examined two PHEV designs: the power-split configuration and the series configuration. The first is a parallel hybrid configuration in which the engine and the electric motor are connected to a single mechanical transmission that incorporates a power-split device that allows for parallel power paths - mechanical and electrical - from the engine to the wheels, allowing the engine and the electric motor to share the power during acceleration. In the second configuration, the engine powers a generator, which charges a battery that is used by the electric motor to propel the vehicle; thus, the engine never directly powers the vehicle's transmission. The power-split configuration was adopted for PHEVs with a 10- and 20-mile electric range because they require frequent use of the engine for acceleration and to provide energy when the battery is depleted, while the series configuration was adopted for PHEVs with a 30- and 40-mile electric range because they rely mostly on electrical power for propulsion. Argonne researchers calculated the equivalent on-road (real-world) fuel economy on the basis of U.S. Environmental Protection Agency miles per gallon (mpg)-based formulas. The reduction in fuel economy attributable to the on-road adjustment formula was capped at 30% for advanced vehicle systems (e.g., PHEVs, fuel cell vehicles [FCVs], hybrid electric vehicles [HEVs], and battery-powered electric vehicles [BEVs]). Simulations for calendar year 2020 with model year 2015 mid-size vehicles were chosen for this analysis to address the implications of PHEVs within a reasonable timeframe after their likely introduction over the next few years. For the WTW analysis, Argonne assumed a PHEV market penetration of 10% by 2020 in order to examine the impact of significant PHEV loading on the utility power sector. Technological improvement with medium uncertainty for each vehicle was also assumed for the analysis. Argonne employed detailed dispatch models to simulate the electric power systems in four major regions of the US: the New England Independent System Operator, the New York Independent System Operator, the State of Illinois, and the Western Electric Coordinating Council. Argonne also evaluated the US average generation mix and renewable generation of electricity for PHEV and BEV recharging scenarios to show the effects of these generation mixes on PHEV WTW results. Argonne's GREET model was designed to examine the WTW energy use and GHG emissions for PHEVs and BEVs, as well as FCVs, regular HEVs, and conventional gasoline internal combustion engine vehicles (ICEVs). WTW results are reported for charge-depleting (CD) operation of PHEVs under different recharging scenarios. The combined WTW results of CD and charge-sustaining (CS) PHEV operations (using the utility factor method) were also examined and reported. According to the utility factor method, the share of vehicle miles traveled during CD operation is 25% for PHEV10 and 51% for PHEV40. Argonne's WTW analysis of PHEVs revealed that the following factors significantly impact the energy use and GHG emissions results for PHEVs and BEVs compared with baseline gasoline vehicle technologies: (1) the regional electricity generation mix for battery recharging and (2) the adjustment of fuel economy and electricity consumption to reflect real-world driving conditions. Although the analysis predicted the marginal electricity generation mixes for major regions in the United States, these mixes should be evaluated as possible scenarios for recharging PHEVs because significant uncertainties are associated with the assumed market penetration for these vehicles. Thus, the reported WTW results for PHEVs should be directly correlated with the underlying generation mix, rather than with the region linked to that mix.

Cost and energy performance of advanced light duty vehicles: Implications for standards and subsidies

We calculated the total cost of ownership (TCO) of fuel cell electric vehicles (FCEVs) in 2017, 2020, 2035, and 2050. Our TCO model incorporates proton exchange membrane fuel cell (PEMFC) cost and durability data that we obtained during our expert elicitation interviews [1]. Our assumptions, including hydrogen storage system and fuel costs, are consistent with those published by the U.S. Department of Energy [2, 3]. We characterized the uncertainty associated with FCEV life cycle costs, and we compared our FCEV projections to the DOE’s 2035 projections for internal combustion engine vehicles (ICEVs), battery electric vehicles (BEVs), hybrid-electric vehicles (HEVs), and plug-in hybrid electric vehicles (PHEVs). In our sensitivity analyses, we studied the dependence of FCEV TCO on vehicle lifetime, hydrogen fuel cost, and hydrogen storage system cost. All monetary values are expressed in 2017 USD. On median, we estimated the FCEV TCO to be $0.42/mile in 2017, $0.33/mile in 2020, $0.19/mile in 2035, and $0.18/mile in 2050 (Figure 1). Our 2017 and 2020 estimates ranged widely. Our 2017 estimates ranged from $0.40 to $0.75/mile and 2020 estimates ranged from $0.31 to $0.51/mile. By 2035, FCEVs could be competitive with ICEVs, BEVs, HEVs, and PHEVs, as long as the PEMFC stack lasts sufficiently long. If the FCEV’s lifetime falls below 11 yrs, FCEVs could become more expensive than competing vehicles. At about 11 yrs, the FCEV’s TCO exceeds that of the BEV. If stack durability remains a challenge, replacing the stack could be economical. Achieving a hydrogen fuel cost below $4/kg H2 and hydrogen system cost below $390/kg H2 could further improve FCEVs’ competitiveness.

Decarbonizing transport is central to global climate goals. Addressing this challenge requires a multifaceted approach, yet dominant policy narratives continue to promote battery electric vehicles (BEVs) as a universally optimal solution. This study assesses that narrative by evaluating the life cycle greenhouse gas (GHG) emissions and environmental trade-offs of multiple passenger vehicle technologies – internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), BEVs, and fuel cell electric vehicles (FCEVs) – within Saudi Arabia’s petroleum-based and seasonally variable energy context. Using a temporally resolved life cycle assessment (LCA), we incorporate projected grid evolution, charging behaviors, and seasonal energy demand to assess climate and environmental outcomes over a 10-year lifespan of a vehicle. Results show that BEVs currently generate 15% higher life cycle GHG emissions than HEVs due to the carbon intensity of Saudi Arabia’s power sector.

Electrified vehicles, including plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs), have the potential to reduce greenhouse gas (GHG) emissions from personal transportation by shifting energy demand from gasoline to electricity. GHG reduction potential depends on vehicle design, adoption, driving and charging patterns, charging infrastructure, and electricity generation mix. We construct an optimization model to study these factors by determining optimal design of conventional vehicles (CVs), hybrid electric vehicles (HEVs), PHEVs, and BEVs and optimal allocation of vehicle designs and charging infrastructure in the fleet for minimum lifecycle GHG emissions over a range of scenarios. We focus on vehicles with similar size and acceleration to a Toyota Prius under urban EPA driving conditions. We find that under today’s U.S. average grid mix, the vehicle fleet allocated for minimum GHG emissions includes HEVs and PHEVs with ~30 miles (48 km) of electric range. Allocating only CVs, HEVs, PHEVs, or BEVs will produce 86%, 1%, 0%, or 13+% more life cycle GHG emissions, respectively. Unlike BEVs, PHEVs do consume some gasoline; however, PHEVs can power a large portion of vehicle miles on electrical energy while accommodating infrequent long trips without need for a large battery pack, with its corresponding production and weight implications. Availability of workplace charging for 90% of vehicles optimistically reduces optimized GHG emissions by 0.5%. Under decarbonized grid scenarios, larger battery packs are more competitive and reduce life cycle GHG emissions significantly. Future work will relax modeling assumptions and address life cycle cost and cost-effectiveness of GHG reductions.

The transportation sector is generally thought to be contributing up to 25% of all greenhouse gases (GHG) emissions globally. Hence, reducing the usage of fossil fuels by the introduction of electrified powertrain technologies such as hybrid electric vehicle (HEV), battery electric vehicle (BEV) and Fuel Cell Electric Vehicle (FCEV) is perceived as a way towards a more sustainable future. With a seemingly more significant shift towards BEV development and roll-out, the research and development of BEV technologies has taken on increasing importance in improving BEV performance and ensuring its competitiveness. Numerical simulation, using MATLAB, is performed as a tool to investigate and to improve the overall performance of BEVs. This study provides an overview of the possible technology outcome and market consequences for future compact BEVs along with HEVs, FCEVs and internal combustion engine vehicles (ICEV). The techno-economics of BEVs, market projection and cost analysis up to 2050 are investigated, as are important BEV characteristics alongside those of other types of vehicles. Well-to-wheel analysis of BEVs is also studied and compared with HEV, FCEV and ICE.

By using the 2017 National Household Travel Survey (NHTS) data, this study explores the status quo of ownership and usage of conventional vehicles (CVs) and alternative fuel vehicles (AFVs), i.e., Hybrid Electric Vehicles (HEVs), Plug-in Hybrid Electric Vehicles (PHEVs) and Battery Electric Vehicles (BEVs), in the United States. The young ages of HEVs (6.0 years), PHEVs (3.2 years) and BEVs (3.1 years) demonstrate the significance of the 2017 NHTS data. The results show that after two decades of development, AFVs only occupy about 5% of annual vehicle sales, and their share does not show big increases in recent years. Meanwhile, although HEVs still dominate the AFV market, the share of PHEVs & BEVs has risen to nearly 50% in 2017. In terms of ownership, income still seems to be a major factor influencing AFV adoption, with the median annual household incomes of CVs, HEVs, PHEVs and BEVs being $75,000, $100,000, $150,000 and $200,000, respectively. Besides, AFV households are more likely to live in urban areas, especially large metropolitan areas. Additionally, for AFVs, the proportions of old drivers are much smaller than CVs, indicating this age group might still have concerns regarding adopting AFVs. In terms of travel patterns, the mean and 85th percentile daily trip distances of PHEVs and HEVs are significantly larger than CVs, followed by BEVs. BEVs might still be able to replace CVs for meeting most travel demands after a single charge, considering most observed daily trip distances are fewer than 93.5 km for CVs. However, the observed max daily trip distances of AFVs are still much smaller than CVs, implying increasing the endurance to meet extremely long-distance travel demands is pivotal for encouraging consumers to adopt AFVs instead of CVs in the future.

This paper examines the impact on the life cycle greenhouse gas (GHG) emissions reduction when fossil-fueled ICE gasoline, diesel and natural gas vehicles, hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) are banned in a step-by-step manner from 2035. We examine the impact of vehicle bans on life cycle GHG emissions and on the marginal cost (MC) of emissions reduction using four different scenarios defined by hydrogen production method, renewable energy share, and infrastructure development for refueling stations. The vehicle penetration and the fuel demand are determined by a consumer choice model characterized by a multinomial logit algorithm. Our analysis found that vehicle bans significantly promote battery electric vehicles (BEVs) for mini-sized vehicles and hydrogen fuel cell vehicles (FCVs) for light and heavy-duty vehicles. A vehicle ban that excludes BEVs and FCVs from 2035 under an enhanced infrastructure plan can reduce the life cycle GHG emissions as much as 438 million tonnes by 2060 compared to the 2017 level. The MC of the life cycle GHG mitigation decreases continuously and reaches as low as $482 per tonne CO2eq in 2060. However, if PHEVs are excluded from the ban, the life cycle GHG emissions are reduced more by 88 Mt-CO2eq in 2060 at a lower MC of $122 per tonne CO2eq. This is due to decreases in GHG emissions from VP where the replacement of PHEVs for BEVs and FCVs reduces the production of batteries and fuel cells. The main structure of the model.

Environmental impacts and behavioral drivers of deep decarbonization for transportation through electric vehicles

Energy consumption of electric vehicles based on real-world driving patterns: A case study of Beijing

Assessing the life-cycle benefits of vehicle lightweighting requires a quantitative description of mass-induced fuel consumption (MIF) and fuel reduction values (FRVs). We have extended our physics-based model of MIF and FRVs for internal combustion engine vehicles (ICEVs) to electrified vehicles (EVs) including hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). We illustrate the utility of the model by calculating MIFs and FRVs for 37 EVs and 13 ICEVs. BEVs have much smaller MIF and FRVs, both in the range 0.04-0.07 Le/(100 km 100 kg), than those for ICEVs which are in the ranges 0.19-0.32 and 0.16-0.22 L/(100 km 100 kg), respectively. The MIF and FRVs for HEVs and PHEVs mostly lie between those for ICEVs and BEVs. Powertrain resizing increases the FRVs for ICEVs, HEVs and PHEVs. Lightweighting EVs is less effective in reducing greenhouse gas emissions than lightweighting ICEVs, however the benefits differ substantially for different vehicle models. The physics-based approach outlined here enables model specific assessments for ICEVs, HEVs, PHEVs, and BEVs required to determine the optimal strategy for maximizing the life-cycle benefits of lightweighting the light-duty vehicle fleet.

Electric vehicles (EVs) are rapidly advancing as a sustainable transportation solution in the global effort to reduce carbon emissions. There are four main types of EVs: battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), hybrid electric vehicles (HEVs), and fuel cell electric vehicles (FCEVs). This article reviews each EV type's advantages, limitations, and prospects based on energy efficiency, carbon emissions, technological development, and infrastructure readiness. The findings indicate that BEVs hold the most significant potential for personal vehicles and urban transportation, while FCEVs are more suited for heavy-duty and long-distance applications. PHEVs and HEVs are considered transition solutions, but their relevance is expected to decrease as technology and global policies evolve. BEVs provide zero emissions. PHEVs provide high flexibility, while HEVs do not require charging infrastructure, and FCEVs offer zero emissions and long-range and fast charging times. FCEV can travel up to more than 800 KM, which is very promising for the distance travelled problem, which is a challenge for electric vehicles.

Reducing greenhouse gas (GHG) emissions from the transportation sector is the goal of several current policies and battery electric vehicles (BEVs) are seen as one option to achieve this goal. However, the introduction of BEVs in the fleet is gradual and their benefits will depend on how they compare with increasingly more energy-efficient internal combustion engine vehicles (ICEVs). The aim of this article is to assess whether displacing ICEVs by BEVs in the Portuguese light-duty fleet is environmentally beneficial (focusing on GHG emissions), taking into account the dynamic behavior of the fleet. A dynamic fleet-based life-cycle assessment (LCA) of the Portuguese light-duty fleet was performed, addressing life-cycle (LC) GHG emissions through 2030 across different scenarios. A model was developed, integrating: (i) a vehicle stock sub-model of the Portuguese light-duty fleet; and (ii) dynamic LC sub-models of three vehicle technologies (gasoline ICEV, diesel ICEV and BEV). Two metrics were analyzed: (i) Total fleet LC GHG emissions (in Mton CO2 eq); and (ii) Fleet LC GHG emissions per kilometer (in g CO2 eq/km). A sensitivity analysis was performed to assess the influence of different parameters in the results and ranking of scenarios. The model baseline projected a reduction of 30–39 % in the 2010–2030 fleet LC GHG emissions depending on the BEV fleet penetration rate and ICEV fuel consumption improvements. However, for BEV introduction in the fleet to be beneficial compared to an increasingly more efficient ICEV fleet, a high BEV market share and electricity emission factor similar or lower to the current mix (485 g CO2 eq/kWh) need to be realized; these conclusions hold for the different conditions analyzed. Results were also sensitive to parameters that affect the fleet composition, such as those that change the vehicle stock, the scrappage rate, and the activity level of the fleet (11–19 % variation in GHG emissions in 2030), which are seldom assessed in the LCA of vehicles. The influence of these parameters also varies over time, becoming more important as time passes. These effects can only be captured by assessing Total fleet GHG emissions over time as opposed to the GHG emissions per kilometer metric. These results emphasize the importance of taking into account the dynamic behavior of the fleet, technology improvements over time, and changes in vehicle operation and background processes during the vehicle service life when assessing the potential benefits of displacing ICEVs by BEVs.

New energy vehicles (NEVs), especially electric vehicles (EVs), address the important task of reducing the greenhouse effect. It is particularly important to measure the environmental efficiency of new energy vehicles, and the life cycle analysis (LCA) model provides a comprehensive evaluation method of environmental efficiency. To provide researchers with knowledge regarding the research trends of LCA in NEVs, a total of 282 related studies were counted from the Web of Science database and analyzed regarding their research contents, research preferences, and research trends. The conclusion drawn from this research is that the stages of energy resource extraction and collection, carrier production and energy transportation, maintenance, and replacement are not considered to be research links. The stages of material, equipment, and car transportation and operation equipment settling, and forms of use need to be considered in future research. Hydrogen fuel cell electric vehicles (HFCEVs), vehicle type classification, the water footprint, battery recovery and reuse, and battery aging are the focus of further research, and comprehensive evaluation combined with more evaluation methods is the direction needed for the optimization of LCA. According to the results of this study regarding EV and hybrid power vehicles (including plug-in hybrid electric vehicles (PHEV), fuel-cell electric vehicles (FCEV), hybrid electric vehicles (HEV), and extended range electric vehicles (EREV)), well-to-wheel (WTW) average carbon dioxide (CO2) emissions have been less than those in the same period of gasoline internal combustion engine vehicles (GICEV). However, EV and hybrid electric vehicle production CO2 emissions have been greater than those during the same period of GICEV and the total CO2 emissions of EV have been less than during the same period of GICEV.