Injury crash risk of battery and hybrid electric passenger cars

Objective: We examined both fatal and injury at-fault crashes of a population of passenger cars fitted with electronic stability control (ESC). Crash rates were calculated in relation to both registration years and mileage. Crash rates were also calculated for a non-ESC car population and crash rate ratios were calculated to compare the crash risk between ESC-fitted and non-ESC-fitted passenger cars.Methods: Passenger car models with and without ESC were identified (ESC-equipped cars: 3,352,813 registration years; non-ESC-equipped: 5,839,946 registration years) and their vehicle information for the period 2009–2013, including mileage (ESC-equipped vehicles: 89.3 billion kilometers; non-ESC-equipped: 72.4 billion kilometers), was drawn from the national Vehicular and Driver Data Register.The registry of Finnish road accident investigation teams was accessed and all fatal at-fault crashes among the cars in the study populations (ESC 97; non-ESC 377) for the period 2009–2013 were analyzed. The motor insurance database includes at-fault crashes leading to injuries and was utilized for analyses (ESC: N = 8,827, non-ESC: N = 21,437).Crash rates and crash rate ratios were calculated to evaluate crash risk of both ESC-equipped and non-ESC-equipped passenger cars. Poisson regression was used to model crash involvement rate ratios both per registration year and per mileage for vehicles with ESC and without ESC, controlling for age and gender of the vehicle owner and vehicle mass.Results: Passenger cars fitted with ESC showed lower crash rates than non-ESC-equipped cars in all crash types studied. In general, the difference in crash rates between ESC-equipped and non-ESC-equipped vehicles was greater when the crashes were compared to the mileage rather than registration years. The mileage-proportional crash rate of ESC-equipped cars was 64% (95% confidence interval, 61%; 67%) lower in run-off-road crashes resulting in injury and as much as 82% (65%; 91%) lower in fatal run-off-road crashes when suicides and disease attacks were not taken into account.Conclusions: Our results show that modern passenger cars provide a significant crash risk reduction, which depends on both ESC and passive safety features introduced. Results also show that exposure evaluation in terms of registration years (or vehicle population) instead of true mileage can provide an overly pessimistic view of the crash risk.

Global warming (GW) and urban pollution focused a great interest on hybrid electric vehicles (HEVs) and battery electric vehicles (BEVs) as cleaner alternatives to traditional internal combustion engine vehicles (ICEVs). The environmental impact related to the use of both ICEV and HEV mainly depends on the fossil fuel used by the thermal engines, while, in the case of the BEV, depends on the energy sources employed to produce electricity. Moreover, the production phase of each vehicle may also have a relevant environmental impact, due to the manufacturing processes and the materials employed. Starting from these considerations, the authors carried out a fair comparison of the environmental impact generated by three different vehicles characterized by different propulsion technology, i.e., an ICEV, an HEV, and a BEV, following the life cycle analysis methodology, i.e., taking into account five different environmental impact categories generated during all phases of the entire life of the vehicles, from raw material collection and parts production, to vehicle assembly and on-road use, finishing hence with the disposal phase. An extensive scenario analysis was also performed considering different electricity mixes and vehicle lifetime mileages. The results of this study confirmed the importance of the life cycle approach for the correct determination of the real impact related to the use of passenger cars and showed that the GW impact of a BEV during its entire life amounts to roughly 60% of an equivalent ICEV, while acidifying emissions and particulate matter were doubled. The HEV confirmed an excellent alternative to ICEV, showing good compromise between GW impact (85% with respect to the ICEV), terrestrial acidification, and particulate formation (similar to the ICEV). In regard to the mineral source deployment, a serious concern derives from the lithium-ion battery production for BEV. The results of the scenario analysis highlight how the environmental impact of a BEV may be altered by the lifetime mileage of the vehicle, and how the carbon footprint of the electricity used may nullify the ecological advantage of the BEV.

The impact of human behavior on vehicle efficiency has been vastly explored for internal combustion engine (ICE) vehicles. However, human behavioral impacts on vehicle efficiency have not yet transitioned to include battery electric vehicles (BEVs). Understanding the impact of human behavior that achieves BEV efficiency is essential globally, as BEVs begin to retain a significant portion of the automotive market share. BEV sales trends in the US have seen consistent growth since 2010, amounting to over 200,000 units sold by 2015. Globally, the total amount of BEVs and plug-in hybrid electric vehicles (PHEVs) is expected to be 40-70 million by 2025. In light of the growth estimates, defining behavior that induces efficient energy consumption when driving BEVs is essential as these vehicles have a traveling distance constrained to 60-120 miles and can require 1-8 hours to attain a fully charged battery at commercial charging stations. With firm traveling distances and long charging times, defining human behavioral impacts on BEV efficiency will allow drivers to get the most range out of their vehicle. In order to develop categories of BEV drivers in terms of efficiency, an empirical experiment was conducted to determine if clustering drivers on their energy consumption profiles invokes significant categories. The driving attributes that defined the clusters were extracted to compare whether or not efficient BEV driving is similar to eco-driving in ICE vehicles. Furthermore, BEV drivers can suffer from anxiety that stems from limited traveling distance, a phenomenon known as range anxiety. However, there exist other sources of anxiety-related human driving behavior, three of which can be measured using the driving behavior survey (DBS). The three anxiety measures from the DBS were contrasted against the BEV efficiency clusters found from this research, to determine if the anxiety factors defined by the DBS were responsible for efficient BEV driving. The results from this research found two significantly different clusters of BEV driving efficiency, which were defined as efficient and inefficient BEV driving. In comparison to eco-driving in ICE vehicles, both aggressive speed and acceleration were found to be contributing factors to BEV efficiency. The results from the DBS proved that anxiety was not a contributing factor to BEV efficiency, as both clusters had similar answers. The information accumulated through this research can be used to guide new BEV drivers to adopt sustainable driving behaviors, which can help maximize their traveling distance on a single charge. Behavioral contributions to

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

The transition from conventional vehicles to battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) is expected to significantly contribute to reducing greenhouse gas emissions in the transportation sector. However, the effectiveness of this transition depends on how BEVs and PHEVs are used compared to internal combustion engine vehicles (ICEVs) and hybrid electric vehicles (HEVs). This paper analyzes data from the 2018–2020 Dutch National Travel Surveys to assess travel behavior of single-car households across four vehicle types: ICEVs, HEVs, PHEVs, and BEVs. Specifically, we focus on daily trip frequency and vehicle kilometers traveled (VKT) for both commuting and non-commuting purposes, while examining how these vehicle usage patterns correlate with vehicle attributes, socioeconomic and demographic factors, and the built environment. Our descriptive analysis shows that BEV and PHEV users have significantly longer daily VKT for both commuting and non-commuting travel compared to ICEV and HEV users. The model results reveal that after controlloing for various factors, BEVs are associated with shorter daily VKT for non-commuting travel compared to other powertrain types, while a pattern not observed for commuting travel. Notably, there is no evidence of a rebound effect linked to the use of BEV and PHEV powertrains. Additionally, leased or company vehicles, regardless of powertrain type, are associated with higher daily VKT and a higher probability of trip-making compared to privately owned vehicles. This higher daily VKT observed for BEV and PHEV users is largely due to the higher prevalence of their vehicles being leased or company cars, rather than the powertrain type itself.

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

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.

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

Volatility in energy markets has made the purchase of battery electric vehicles (BEV) or hybrid vehicles (HEVs) attractive versus internal combustion engine vehicles (ICEVs). However, the total cost of ownership (TCO) and true environmental effects, are difficult to assess. This study provides a publicly available, user-driven simulation that estimates the consumer and environmental costs for various vehicle purchase options, supporting policymaker, producer, and consumer information requirements. It appears to be the first to provide a publicly available, user interactive simulation that compares two purchase options simultaneously. It is likely that the first paper to simulate the effects of solar recharging of electric vehicles (EV) on both cost-benefit for the consumer and environmental benefit (e.g., carbon dioxide, oxides of nitrogen, non-methane organic gasses, particulate matter, and formaldehyde) simultaneously, demonstrating how, as an example, solar-based charging of BEVs and HEVs reduces carbon emissions over grid-based charging. Two specific scenarios are explicated, and the results of show early break-even for both BEV and Plug-in HEV (PHEV) options over ICEV (13 months, and 12 months, respectively) with CO2 emissions about ½ that of the gasoline option (including production emissions.) The results of these simulations are congruent with previous research that identified quick break-even for HEVs versus ICEV.

Author(s): Muehlegger, Erich; Rapson, David | Abstract: This research project explores the plug-in electric vehicle (PEV) market, including both Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs), and the sociodemographic characteristics of purchasing households. The authors use detailed micro-level data on PEV purchase records to answer two primary research questions. Their results confirm that low-income households exhibit a lower share of PEV purchases than they do for conventional, internal combustion engine (ICE) vehicles. Households with annual income less than $50,000 comprise 33 percent of ICE purchases and only 14 percent of PEVS. By comparison, high-income households earning more than $150,000 annually comprise only 12 percent of ICE purchases and 35 percent of PEV purchases over their sample period. Similarly, unsurprising patterns can be seen across ethnicities. For example, non-Hispanic Whites represent 41 percent of ICE purchases but 55 percent of PEV purchases, as compared to Hispanics (38 percent of ICE and 10 percent of PEVs) and African Americans (3 percent of ICEs and 2 percent of PEVS). These differences naturally raise questions about barriers to PEV adoption among low-income and minority ethnic populations. By comparing outcomes in the ICE, hybrid, and PEV markets across income and ethnic groups, the authors are able to test whether price discrimination and barriers to market access are higher in PEV markets for low-income and minority ethnic groups. The authors find that, overall, they are not, although there are mixed results for the used PEV market. In general, non-white, low-income populations face higher prices in the used PEV market, relative to a baseline, than they do in the new PEV market. While some people travel farther to buy used PEVs than they do to buy used ICE vehicles, there is not a pattern that would indicate systematic discrimination (e.g. Hispanics travel farther to buy used PHEVs but less far to buy used BEVs). While the authors admit that their empirical approach cannot control for all potential vehicle composition effects, the authors view their results as being most consistent with a market that provides access to all ethnicities and income groups.View the NCST Project Webpage

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 article presents a cradle-to-grave (C2G) assessment of greenhouse gas (GHG) emissions and costs for current (2015) and future (2025-2030) light-duty vehicles. The analysis addressed both fuel cycle and vehicle manufacturing cycle for the following vehicle types: gasoline and diesel internal combustion engine vehicles (ICEVs), flex fuel vehicles, compressed natural gas (CNG) vehicles, hybrid electric vehicles (HEVs), hydrogen fuel cell electric vehicles (FCEVs), battery electric vehicles (BEVs), and plug-in hybrid electric vehicles (PHEVs). Gasoline ICEVs using current technology have C2G emissions of ∼450 gCO2e/mi (grams of carbon dioxide equivalents per mile), while C2G emissions from HEVs, PHEVs, H2 FCEVs, and BEVs range from 300-350 gCO2e/mi. Future vehicle efficiency gains are expected to reduce emissions to ∼350 gCO2/mi for ICEVs and ∼250 gCO2e/mi for HEVs, PHEVs, FCEVs, and BEVs. Utilizing low-carbon fuel pathways yields GHG reductions more than double those achieved by vehicle efficiency gains alone. Levelized costs of driving (LCDs) are in the range $0.25-$1.00/mi depending on time frame and vehicle-fuel technology. In all cases, vehicle cost represents the major (60-90%) contribution to LCDs. Currently, HEV and PHEV petroleum-fueled vehicles provide the most attractive cost in terms of avoided carbon emissions, although they offer lower potential GHG reductions. The ranges of LCD and cost of avoided carbon are narrower for the future technology pathways, reflecting the expected economic competitiveness of these alternative vehicles and fuels.

Developing an Eco-Cooperative Automated Control System (Eco-CAC)

A comparison of technologies for carbon-neutral passenger transport

Electrification can reduce the greenhouse gas (GHG) emissions of light-duty vehicles. Previous studies have focused on comparing battery electric vehicle (BEV) sedans to their conventional internal combustion engine vehicle (ICEV) or hybrid electric vehicle (HEV) counterparts. We extend the analysis to different vehicle classes by conducting a cradle-to-grave life cycle GHG assessment of model year 2020 ICEV, HEV, and BEV sedans, sports utility vehicles (SUVs), and pickup trucks in the United States. We show that the proportional emissions benefit of electrification is approximately independent of vehicle class. For sedans, SUVs, and pickup trucks we find HEVs and BEVs have approximately 28% and 64% lower cradle-to-grave life cycle emissions, respectively, than ICEVs in our base case model. This results in a lifetime BEV over ICEV GHG emissions benefit of approximately 45 tonnes CO2e for sedans, 56 tonnes CO2e for SUVs, and 74 tonnes CO2e for pickup trucks. The benefits of electrification remain significant with increased battery size, reduced BEV lifetime, and across a variety of drive cycles and decarbonization scenarios. However, there is substantial variation in emissions based on where and when a vehicle is charged and operated, due to the impact of ambient temperature on fuel economy and the spatiotemporal variability in grid carbon intensity across the United States. Regionally, BEV pickup GHG emissions are 13%–118% of their ICEV counterparts and 14%–134% of their HEV counterparts across U.S. counties. BEVs have lower GHG emissions than HEVs in 95%–96% of counties and lower GHG emissions than ICEVs in 98%–99% of counties. As consumers migrate from ICEVs and HEVs to BEVs, accounting for these spatiotemporal factors and the wide range of available vehicle classes is an important consideration for electric vehicle deployment, operation, policymaking, and planning.