• Energy Research
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Planning scholars have identified economic, safety, and social benefits of converting one-way streets to two-way. Less is known about how conversions could impact vehicular distances traveled—of growing relevance in an era of fleet automation, electrification, and ride-hailing. We simulate such a conversion in San Francisco, California. We find that its current street network’s average intra-city trip is about 1.7% longer than it would be with all two-way streets, corresponding to 27 million kilometers of annual surplus travel. As transportation technologies evolve, planners must consider different facets of network efficiency to align local policy and street design with sustainability and other societal goals.

China's road transportation contributed about 8% of the country’s GHG emissions in 2020. Chinese government has made the commitment of reaching “carbon peak in 2030 and carbon neutrality in 2060”. Among all the sectors, transportation is one of the most challenging and essential ones to mitigate GHG emissions. The experienced economic development and improvement in people's living standards have increased vehicle ownership for both passenger vehicles and freight trucks. For the road transportation sector, electrification of the fleet represents one of the most important measures to reduce criteria pollutants and GHG emissions.By modeling passenger and freight vehicle fleets, this study projects the vehicle growth based on economic projections and the changes in demographic characteristics of the population during 2010 to 2050. The study developed a stock and sales model considering vehicle survival rates by vehicle types to reflect the different vehicle retirement and replacement schedules. Moreover, the study designed three sets of fleet electrification scenarios considering different technology penetration and deployment levels for different vehicle type. The scenario analysis extensively explored the energy consumption and GHG emission trajectories for the different vehicle growth scenarios, electrification pathways and renewable energy penetration rates in the grid. The scenarios also considered, as mentioned, changes in the demographics. For instance, in aging society scenario (considering an aging and decreasing fertility demographic), fleet growth rates slow down in the following three decades. This scenario results in a reduction of energy consumption and GHG emission from the road transportation sector. The scenario analysis extensively explored the energy consumption and GHG emission trajectories of the different vehicle growth scenarios, electrification pathways, and renewable energy penetration rates in the grid. From the scenarios analysis, in the aging society vehicle growth scenario, the ...

Automated driving has attracted intense attention in the media and among the general public, based on extremely optimistic predictions from some industry participants, but these have started to become more realistic in the last couple of years, after the “hype cycle” for automation peaked. This paper explains the opportunities for Automated Driving System (ADS) technology to improve the urban transport of people and goods, together with the challenges that will limit the scope and timing of the deployment of urban ADS. The discussion emphasizes the diversity of ADS applications and services, each of which has its own opportunities, challenges, and uncertainties, leading to diverse deployment scopes and schedules. The associated challenges are sufficiently daunting that ADS deployment will lag behind electrification and connectivity, leaving more time for cities to prepare for it.

AbstractThis contribution to the RECCAP2 (REgional Carbon Cycle Assessment and Processes) assessment analyzes the processes that determine the global ocean carbon sink, and its trends and variability over the period 1985–2018, using a combination of models and observation‐based products. The mean sea‐air CO2 flux from 1985 to 2018 is −1.6 ± 0.2 PgC yr−1 based on an ensemble of reconstructions of the history of sea surface pCO2 (pCO2 products). Models indicate that the dominant component of this flux is the net oceanic uptake of anthropogenic CO2, which is estimated at −2.1 ± 0.3 PgC yr−1 by an ensemble of ocean biogeochemical models, and −2.4 ± 0.1 PgC yr−1 by two ocean circulation inverse models. The ocean also degasses about 0.65 ± 0.3 PgC yr−1 of terrestrially derived CO2, but this process is not fully resolved by any of the models used here. From 2001 to 2018, the pCO2 products reconstruct a trend in the ocean carbon sink of −0.61 ± 0.12 PgC yr−1 decade−1, while biogeochemical models and inverse models diagnose an anthropogenic CO2‐driven trend of −0.34 ± 0.06 and −0.41 ± 0.03 PgC yr−1 decade−1, respectively. This implies a climate‐forced acceleration of the ocean carbon sink in recent decades, but there are still large uncertainties on the magnitude and cause of this trend. The interannual to decadal variability of the global carbon sink is mainly driven by climate variability, with the climate‐driven variability exceeding the CO2‐forced variability by 2–3 times. These results suggest that anthropogenic CO2 dominates the ocean CO2 sink, while climate‐driven variability is potentially large but highly uncertain and not consistently captured across different methods.

Batteries stacks are made of cells in certain series-parallel arrangements. Unfortunately, cell performance degrades over time in terms of capacity, internal resistance, or self-discharge rate. In addition, degradation rates are heterogeneous, leading to cell-to-cell variations. Balancing systems can be used to equalize those differences. Dissipative or non-dissipative systems, so-called passive or active balancing, can be used to equalize either voltage at end-of-charge, or state-of-charge (SOC) at all times. While passive balancing is broadly adopted by industry, active balancing has been mostly studied in academia. Beyond that, an emerging research field is multi-functional balancing, i.e., active balancing systems that pursue additional goals on top of SOC equalization, such as equalization of temperature, power capability, degradation rates, or losses minimization. Regardless of their functionality, balancing circuits are based either on centralized or decentralized control systems. Centralized control entails difficult expandability and single point of failure issues, while decentralized control has severe controllability limitations. As a shift in this paradigm, here we present for the first time a distributed multi-objective control algorithm, based on a multi-agent consensus algorithm. We implement and validate the control in simulations, considering an electro-thermal lithium-ion battery model and an electric vehicle model parameterized with experimental data. Our results show that our novel multi-functional balancing can enhance the performance of batteries with substantial cell-to-cell differences under the most demanding operating conditions, i.e., aggressive driving and DC fast charging (2C). Driving times are extended (>10%), charging times are reduced (>20%), maximum cell temperatures are decreased (>10 °C), temperature differences are lowered (~3 °C rms), and the occurrence of low voltage violations during driving is reduced (>5×), minimizing the need for power derating and enhancing the user experience. The algorithm is effective, scalable, flexible, and requires low implementation and tuning effort, resulting in an ideal candidate for industry adoption.

Significance The surging demand for battery resources and energy from EVs signifies a need to reassess the real-world battery utilization and energy consumption of urban EVs. In this work, we incorporate unique and previously unavailable datasets of urban-scale EV operation to better understand the battery utilization and energy consumption of large-scale EV utilization. High-resolution operating data of EVs across multiple regions are collected and integrated with vehicle feature data as the input for modeling. Accordingly, we expose several issues that have nonnegligible impacts on battery resources and the urban power supply, such as low battery utilization and seasonal changes in the energy consumption of EVs. The provided models and data can be extensively utilized for further EV-related resource and energy investigations.

Author(s): Chakraborty, Debapriya; Bunch, David S.; Xu, Bingzheng; Brownstone, David; Tal, Gil | Abstract: The market for plug-in electric vehicles (PEVs) that primarily include battery electric vehicles (BEVs) and plug-in hybrid vehicles (PHEVs) has been rapidly growing in California for the past few years. Given the targets for PEV penetration in the state, it is important to have a better understanding of the pattern of technology diffusion and the factors that are driving the process. Using spatial analysis and Poisson count models, the researchers identify the importance of a neighborhood effect (at home locations) and workplace effect (at commute destinations) in supporting the diffusion of PEV technology in California. In the case of new BEV sales, they found that exposure to one additional BEV or PHEV within a 1-mile radius of a block group centroid is associated with a 0.2% increase in BEV sales in the block group. Interestingly, for new PHEV sales, the neighborhood effect of BEV sales is negative, suggesting that enhanced exposure to this type of technology (which is differentiated in distinctive ways from PHEVs) may impact new PHEV sales through a substitution effect. Specifically, higher BEV concentration in an area can have an overall negative effect on new PHEV sales. While the neighborhood effect at residential locations is important, the workplace effect also has a notably important effect on new PEV sales. Both effects work in combination with socioeconomic, demographic, policy, and built environment factors in encouraging PEV adoption. These results suggest that policymakers should consider targeted programs and investments that can boost the impact of neighborhood and peer effects on PEV salesView the NCST Project Webpage

This study aims to evaluate the potential of electric vehicle (EV) carsharing services to address social and environmental disparities in urban transportation through an evaluation of BlueLA, a one-way station-based carsharing service in Los Angeles, California. BlueLA provides a clean and affordable mobility option in underserved communities that face significant air quality burdens and have historically been excluded from environmental benefits. By incorporating BlueLA trip activity data from January 2021 to December 2022 (n = 59,112 trips) and an online user survey implemented in early December 2022 (n = 215 responses), we estimate the impacts of BlueLA on personal vehicle ownership patterns, vehicle miles traveled (VMT), and associated greenhouse gas (GHG) emissions. The results show an overall net reduction in VMT and GHG emissions of 463,845 miles and 656 metric tons, respectively, among the BlueLA user population (3074 registered users). When disaggregating impacts by BlueLA member type, our findings show a net reduction of 234 and 371 metric tons in GHG emissions for Standard (general population) and Community (low-income qualified) members, respectively. Additionally, our socio-demographic analysis highlights clear disparities between these two member groups, with Community members typically having lower incomes (i.e., 74% earning below USD 50,000 annually); lower educational attainment (i.e., 46% with at most an associate’s degree); and larger households (i.e., 23% living in households of four or more) compared to Standard members (i.e., 19% earning below USD 50,000, 24% with at most an associate’s degree, and 9% in households of four or more). Moreover, when comparing the VMT and associated GHG emissions due to BlueLA, we find that the presence of BlueLA reduces VMT and GHG emissions by 34% and 48% respectively, and each BlueLA vehicle replaces 16 personally owned vehicles (shed and postponed purchases). Last, when comparing the emissions produced by the electric fleet of BlueLA to those of a comparable fleet of internal combustion engine vehicles, we find that the use of an EV fleet reduces GHG emissions by 43% in comparison. The BlueLA carsharing service has led to notable net reductions in VMT and thus GHG emissions, with a major share of these reductions observed among Community members.