Variability of daily car usage and the frequency of long-distance driving

The limited electric range of battery electric vehicles (BEV) and plug-in hybrid electric vehicles (PHEV) requires an understanding of the variation in day-to-day driving and the frequency of long-distance driving. Existing literature suggests high regularity of human mobility. However, large longitudinal mobility samples for empirical tests are hardly available. Here, we analyze the regularity of daily vehicle kilometers travelled (VKT) of 10,000 vehicles observed between two months and several years and quantify the regularity of daily VKT and the frequency of long-distance driving. Our results indicate limited regularity of daily VKT beyond one day of time lag (mean autocorrelation ≤ 0.11). Long-distance driving with daily km over 100 km (200 km) typically take place on less than 20% (5% for 200 km) of driving days but make up 40% (18%) of annual VKT. Our results have implications for sustainable transport research and the design of travel surveys

Empirical charging behavior of plug-in hybrid electric vehicles

Plug-in hybrid electric vehicles (PHEV) offer greenhouse gas emission reduction in car usage if charged frequently and driven mainly on electricity. However, little is known about the actual charging behavior of PHEV owners. Here, we investigate the daily charging of 10,488 Chevrolet Volt PHEV driven on a total of 4.3 million total driving days in the US and Canada. We propose a new method to detect the frequency of individual charging behavior from the daily utility factor and daily distance travelled. Our results show that no charging overnight occurs typically on 3–7% of the driving days per user and additional charging happens on 20–26% of the driving days. We also analyze the relation between charging frequency and utility factor for different user groups and days. Our results show that the utility factor should not be used as the only measure of environmental performance of PHEVs

Battery electric long-haul trucks in Europe: Public charging, energy, and power requirements

Electric battery trucks (BETs) have the potential to significantly reduce emissions from heavy-duty vehicles. However, adopting BETs for long-haul operations depends on the availability of sufficient charging infrastructure. In this study, we use a trip chain model to assess the charging requirements for BETs in long-haul operations in Europe in 2030. Our model accounts for truck driving regulations and different stop types. We find that the number of overnight chargers (50–100 kW) required is 4–5 times higher than the number of megawatt chargers (0.7–1.2 MW) needed to support a BET share of 15% in long-haul operations. We estimate that approximately 40,000 overnight and 9,000 megawatt chargers are required, with an average of eight overnight and two megawatt chargers per charging area serving an average of two and 11 BETs daily, respectively. These findings provide insights for planning charging infrastructure for BETs in long-haul operations in Europe

A Review of Big Data in Road Freight Transport Modeling: Gaps and Potentials

Road transport accounted for 20% of global total greenhouse gas emissions in 2020, of which 30% come from road freight transport (RFT). Modeling the modern challenges in RFT requires the integration of different freight modeling improvements in, e.g., traffic, demand, and energy modeling. Recent developments in \u27Big Data\u27 (i.e., vast quantities of structured and unstructured data) can provide useful information such as individual behaviors and activities in addition to aggregated patterns using conventional datasets. This paper summarizes the state of the art in analyzing Big Data sources concerning RFT by identifying key challenges and the current knowledge gaps. Various challenges, including organizational, privacy, technical expertise, and legal challenges, hinder the access and utilization of Big Data for RFT applications. We note that the environment for sharing data is still in its infancy. Improving access and use of Big Data will require political support to ensure all involved parties that their data will be safe and contribute positively toward a common goal, such as a more sustainable economy. We identify promising areas for future opportunities and research, including data collection and preparation, data analytics and utilization, and applications to support decision-making

Exploring the Role of Plug-In Hybrid Electric Vehicles in Electrifying Passenger Transportation

Key Takeaways1. Plug-in hybrid electric vehicles (PHEVs) have an important role in the electrifi cation of passenger transportation. Long-range PHEVs not only are a transitional technology. They also are an enabling technology that can encourage more consumers to adopt electric vehicles.2. The electric range of PHEVs has a signifi cant impact on electric vehicle miles traveled. PHEVs with electric range of at least 60km (37 miles (EPA Range)) have a similar ability to electrify travel as short-range battery electric vehicles (BEVs).3. Assuming the goal of policymakers is to increase electric vehicle miles traveled, policy support should correspond directly to electric driving range of both PHEVs and BEVs. Short-range PHEVs should receive less policy support; long-range PHEVs and BEVs should receive more policy support.4. Consumer research in several countries shows that mainstream consumers tend to be more attracted to PHEVs than to BEVs, however many consumers are unaware of how a PHEV diff ers from a BEV. Consumers and car dealerships need to be educated about PHEVs, their benefi ts, and the importance of charging the vehicles

Empirical recharging behavior of plug-in hybrid vehicles

In this paper, we investigated the recharging behavior of Chevy Volt (a plug-in hybrid electric vehicle) users. The dataset used is from volstats.net and contains data from 9,987 Chevrolet Volt driven with 3.7 million total driving days in the US and Canada, from April 2011 to May 2019. Results show that additional over-day recharging happens on average on 3-8 % of the days and no recharging overnight happens on average less often 3-6 % of the days. Furthermore, users with more than 30,000 annual vehicle kilometers traveled recharge over-day more than three times compared to the rest of the group

On the distribution of individual daily vehicle driving distances

The vehicle kilometres travelled (VKT) by individual passenger cars vary strongly between days. This is important for electric vehicles since trips larger than the electric range reduce their utility. Here we analyse different distribution functions for the variation in daily VKT with three sets of travel data. In contrast to the literature, no analysed distribution stands out best. We apply our findings for the distribution functions to estimate the number of days per year with driving distance larger than 100 km and find that the distributions differ in their predictions of the number of such days

On the distribution of individual daily vehicle driving distances

The vehicle kilometres travelled (VKT) by individual passenger cars vary strongly between days. This is important for electric vehicles since trips larger than the electric range reduce their utility. Here we analyse different distribution functions for the variation in daily VKT with three sets of travel data. In contrast to the literature, no analysed distribution stands out best. We apply our findings for the distribution functions to estimate the number of days per year with driving distance larger than 100 km and find that the distributions differ in their predictions of the number of such days

Are multi-car households better suited for battery electric vehicles? - Driving patterns and economics in Sweden and Germany

Battery electric vehicles (BEVs) could reduce CO2 emissions from the transport sector but their limited electric driving range diminishes their utility to users. The effect of the limited driving range can be reduced in multi-car households where users could choose between a BEV and a conventional car for long-distance travel. However, to what extent the driving patterns of different cars in a multi-car household’s suit the characteristics of a BEV needs further analysis. In this paper we analyse the probability of daily driving above a fixed threshold for conventional cars in current Swedish and German car driving data. We find second cars in multi-car households to require less adaptation and to be better suited for BEV adoption compared to first cars in multi-car households as well as to cars in single-car households. Specifically, the share of second cars that could fulfil all their driving is 20 percentage points higher compared to first cars and cars from single-car households. This result is stable against variation of driving range and of the tolerated number of days requiring adaptation. Furthermore, the range needed to cover all driving needs for about 70% of the vehicles is only 220 km for second cars compared to 390 km for the average car. We can further confirm that second cars have higher market viability from a total cost of ownership perspective. Here, the second cars achieve a 10 percentage points higher market share compared to first cars, and to cars in single-car households for Swedish economic conditions, while for Germany the corresponding figure is 2 percentage points. Our results are important for understanding the market viability of current and near-future BEVs

Are electric vehicles better suited for multi-car households?

Electric vehicles could reduce CO2 emissions from the transport sector but their limited electric driving range diminishes their utility to users. Two-car households could be better suited for EV adoption since one vehicle could be used for longer trips. However, the number of days requiring adaptation and the differences between the cars in a multi-car household have not been systematically analysed yet. Here, we estimate the probability of daily driving above a fixed threshold for Swedish and German car driving data. We find the vehicles from multi-car-households to require less adaptation and be better suited for EV adoption which we confirm with an economic analysis