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This paper seeks to optimise fleet management for companies that utilise both internal combustion engine vehicles (ICEVs) and electric vehicles by considering various costs, including fixed costs, variable costs, time window penalty costs, fuel costs, and electricity consumption costs. Additionally, the study examines the influence of four types of regulations, i.e. carbon cap, carbon tax, carbon trading, and carbon offsetting, on carbon emissions and fleet configuration. The optimisation model was solved using a Clarke-Wright savings heuristic algorithm followed by an improved adaptive genetic algorithm (IAGA), and a sensitivity analysis was conducted under different regulatory policies. The results show that all four types of regulations can effectively reduce fleet emissions. While carbon prices have a greater impact on carbon regulations than carbon quota, carbon trading was more effective under similar circumstances. Therefore, governments should implement appropriate regulatory strategies to reduce energy consumption and encourage enterprises to reduce their emissions. [ABSTRACT FROM AUTHOR]

This study addresses the challenging real-time vehicle relocation and staff rebalancing (RT-VR&SR) problem in electric carsharing services. The complexity arises from ad-hoc demand, charging requirements of electric vehicles (EVs), and staff scheduling constraints. The problem aims to maximize the profit of carsharing operators by determining strategies for vehicle relocation, vehicle charging, and staff rebalancing in real-time. It considers the uncertainty of demand and the practical nonlinear charging profile of EVs. We formulate this problem as a Markov Decision Process (MDP), and propose an efficient concurrent-scheduler-based policy. Numerical experiments are conducted to demonstrate the effectiveness of the proposed policy and methodology. The results show that the proposed policy significantly improves service level and profitability compared to a benchmark policy. It is also found that ignoring staff rebalancing in decision making can lead to overestimation of service level and profitability. In conclusion, this study presents a real-time solution for vehicle relocation and staff rebalancing in one-way electric carsharing services. The proposed policy and methodology improve performance and highlight the importance of considering staff rebalancing in decision making. [ABSTRACT FROM AUTHOR]

The integration of a composite of porous medium with phase change material (PCM) offers significant advantages in thermal management systems, enhancing heat transfer efficiency and addressing various thermal regulation challenges. This approach utilizes the PCM's latent heat absorption and the enhanced thermal conductivity provided by the porous medium, resulting in optimized system performance. Its applicability spans across electronics cooling and building insulation systems. However, predicting the thermal behavior of this composite material is challenging, necessitating computational tools to anticipate its response under different conditions and evaluate its influence on cooling strategies. The objective of this study is to create a computational tool specifically tailored to evaluate constitutive parameters of this composite material, thereby providing a comprehensive description of its thermal behavior. To achieve this goal, the multiscale homogenization principle is employed to assess the composite's effective thermophysical material properties using the representative volume element approach. The repeating unit cell of the aluminum lattice is incorporated into the PCM to define a representative volume element. The finite element method (FEM) is utilized to solve the three-dimensional homogenization problem, yielding an orthotropic effective thermal conductivity due to the inherent symmetry of the repeating material cell. Moreover, the study leverages the apparent heat capacity method to effectively manage the phase transitions within the PCM domain, utilizing smooth and temperature-dependent functions to accurately describe the thermophysical properties of the PCM. Integrating the composite into battery pack thermal management, this study thoroughly examines thermal dynamics by comparing outcomes with and without PCM integration. The transient thermal problem is accurately tackled using the FEM, employing the evaluated effective constitutive parameters of the homogenized composite to minimize computational effort. The results indicate a notable decline in the highest temperatures of the battery pack, leading to a reduction of about 14 °C at the specific moment when the phase change material fully transitions into its liquid form. The obtained results emphasize the effectiveness and practical feasibility of the proposed thermal management strategy. The modeling approach presented provides a robust tool with significant efficiency in reducing computational time for analyzing the thermal behavior of large models, as the utilization of the homogenization technique notably decreases the computational time. [ABSTRACT FROM AUTHOR]

The modern quest for sustainable cities increasingly relies on using distributed energy resources (DERs), which requires new planning practices. This paper proposes an optimisation strategy to solve the fast charging station (FCS) allocation of electric vehicles (EVs). A mixed-integer programming (MIP) model minimises investment and operation costs, considering the building of FCSs with photovoltaic (PV) systems over carports and battery energy storage systems (BESSs) as planning alternatives. The embedded set covering problem has special aspects that allow the development of a novel approach to evaluate candidate sites to accommodate FCSs. A preprocessing strategy is developed to fine-tune the entire solution space. A multiobjective approach is used to obtain an optimal compromise solution for the MIP model when it is required to serve the maximum number of EV owners at the lowest possible cost. The combined strategies reduce the computational burden, allowing full-scale studies of EV charging system planning. The results of studies using a real-world Brazilian case certify the benefits of the proposed strategy in the FCS allocation problem and in optimising the operation when considering renewable alternatives. [ABSTRACT FROM AUTHOR]

High charging loads associated with fleets of commercial electric vehicles (EVs) are expected to significantly stress electric power distribution networks, leading to high costs seen by fleet operators. To address these challenges, this report presents a highly flexible smart charging (SC) algorithm for managing EV fleets that arrive and depart from a common depot on a schedule. The algorithm features (i) primary consideration of multiple fleet operator preferences (e.g. minimizing cost, using carbon-free energy), (ii) secondary consideration of grid impact that leverages the existence of multiple optimal (or near-optimal) ways to satisfy fleet operator preferences, and (iii) automatic detection and handling of infeasibility due to large energy demands (characteristic of fleet charging). Provided in this document are two numerical impact assessment studies in which the SC algorithm is shown to be superior to conventional rapid charging, and conventional ‘smart’ charging solutions on the market. These studies utilize a set of synthetic, but realistic fleet charging requirements, a physics-based model of a real feeder and one year of real, hourly load data for that feeder. The first numerical study shows that the proposed SC algorithm can lead to significant (up to 44%, but scenario-dependent) reductions in a fleet operator’s annual electricity bill. The second numerical study shows that significant transformer overloading and voltage drop issues can be associated with conventional fleet charging methods, and that the proposed SC algorithm eliminates these issues, thereby enabling higher EV penetration levels and offsetting infrastructure upgrades. View the NCST Project Webpage

This study delves into the energy and emissions impacts of Shared Autonomous and Electric Vehicles (SAEVs) on disadvantaged communities in California. It explores the intersection of evolving transportation technologies—electric, autonomous, and shared mobility—and their implications for equity, energy consumption, and emissions. Through high-resolution spatial and temporalanalyses, this research evaluates the distribution of benefits and costs of SAEVs across diverse populations, incorporatingenvironmental justice principles. Our quantitative findings reveal that electrification of the vehicle fleet leads to a 63% to 71% decrease in CO2 emissions even with the current grid mix, and up to 84%-87% under a decarbonized grid with regular charging. The introduction of smart charging further enhances these benefits, resulting in a 93.5% - 95% reduction in CO2 emissions. However, the distribution of these air quality benefits is uneven, with disadvantaged communities experiencing approximately 15% less benefits compared to more advantaged areas. The study emphasizes the critical role of vehicle electrification and grid decarbonization in emissions reduction, and highlights the need for policies ensuring equitable distribution of SAEV benefits to promote sustainable and inclusive mobility.View the NCST Project Webpage

The path to transportation decarbonization will rely heavily on electric vehicles (EVs) in the United States. EV diffusion forecasting tools are necessary to predict the impacts of EVs on local energy demand and environmental quality. Few EV adoption models operate at a fine spatial scale and those that do still rely on aggregated demographic information. This adoption model is one of the first attempts to employ a synthetic population to examine EV distribution at a fine spatial and demographic scale. Using a synthetic population at the Census-Tract-level, enriched with household fleet body types and home-charging access, the researchers consider the effect of vehicle body type on EV spatial distribution and home-charging access in California. The project examines two EV body type mixes in a high electrification scenario where 8 million EVs are distributed across 6 million households in California: a “Small Vehicles” scenario where 6 million EVs are passenger cars and 2 million EVs are trucks, sport utility vehicles (SUVs), or vans and a “Large Vehicles” scenario with 4 million of each category. The authors find that an electrification scenario with more electric trucks and SUVs serves to distribute electrified households more evenly throughout the state, shifting them from urban to rural counties, while there is little impact on home-charging access. View the NCST Project Webpage

Strong policies are needed to accelerate the zero-emission vehicle (ZEV) transition so that it occurs at a pace in line with international climate goals. The purchase price of new vehicles tends to be the variable that most affects consumer decisions. With urgency for a ZEV transition, fiscal pressure for governments can be high as rebates for consumers and incentives supporting manufacturers in the switch to ZEV technologies will be needed for a mass-market transition. Fees on high-polluting vehicles—and rebates on clean ones—have become an effective and increasingly common strategy in European countries. The feebate mechanism can raise the necessary capital for financing a ZEV transition in combination with other regulatory mechanisms. This paper reviews and assesses feebate design types, issues, and implementation strategies in France, Germany, Italy, Sweden, and the United Kingdom. These examples show that feebates can be designed in a variety of ways to meet unique policy objectives and that periodic adjustments are helpful in achieving goals. Among twelve design considerations for an effective feebate, the authors find that: (1) focusing on a single fee parameter, such as CO2 emissions, can be a simple yet effective mechanism; (2) a continuous functional form for the fee and a stepwise rebate are likely to be most effective in driving EV adoption; and (3) pure feebates, where fee revenue funds EV incentives by program design, provide certainty for manufacturers, regulators, and consumers. View the NCST Project Webpage

The United States (US), under the Biden Administration, has set a goal of reaching a 50% sales share for zero-emission vehicles by 2030. The administration is pursuing a combination of aggressive fuel economy and greenhouse gas performance standards along with tax credits for consumers who purchase electric vehicles (EVs). Given the anticipated high costs of the EV transition and limited public funds, policy mechanisms that generate extra-budgetary funding are enticing. Feebates—where a fee charged on some purchases is used to offer a rebate for others—can serve as a self-sustaining tool. Feebates have been attempted at the state and federal level in the US but did not pass legislatures due to a lack of political support for levying a fee on internal combustion engine (ICE) vehicles. However, as governments face increasing fiscal constraints, there is greater support for self- funding EV incentive programs. Feebate policies can provide certainty for both producers and consumers to facilitate a steady transition to sustainable transportation. This paper assesses the potential utility of feebates for shaping the US light-duty vehicle market. The analysis demonstrates that: (1) revenue-neutral incentive systems are possible and (2) revenue-neutrality can be achieved with relatively low fees on ICE vehicles to support economic equity among buyers. From an industry perspective, market certainty can be created by incorporating fuel economy targets into a fee schedule as pivot points and allocating fees to finance rebates. This would likely influence industry investment decisions in ways that increase EV production and model availability. View the NCST Project Webpage

The widespread adoption of electric vehicles (EV) is a centerpiece of California’s strategy to reach net-zero carbon emissions, but it is not fully known how and where EVs are being used, and how and where they are being charged. This report provides the first at-scale estimate of EV home charging. Previous estimates were based on conflicting surveys or extrapolated from a small, unrepresentative sample of households with dedicated EV meters. We combined billions of hourly electricity meter measurements with address-level EV registration records from California households, including roughly 40,000 EV owners. The average EV increases overall household load by 2.9 kilowatt-hours per day, well under half the amount assumed by state regulators. Results imply that EVs travel less than expected on electric power, raising questions about transportation electrification for climate policy.

The global demand for high energy density batteries, mostly for application in electric vehicles, offering increased durability, safety, and sustainability is growing rapidly. In the past, this demand has been met primarily by the development and/or improvement of new/established battery materials and technologies. The high-entropy design concept—aiming at increasing chemical complexity/occupational disorder—has recently been introduced into the field of electrochemical energy storage. Various high-entropy battery materials that are seemingly capable of outperforming low-entropy counterparts by offering desirable properties have been reported. However, future studies are required to explore if the concept is broadly applicable and can be extended to all types of battery materials, especially those that are of industrial relevance. Herein, we provide a brief overview of the existing high-entropy anodes, cathodes, and solid/liquid electrolytes for use in rechargeable Li- or Na-ion batteries and discuss potential research directions and opportunities. [ABSTRACT FROM AUTHOR]

High quality, safe, and reliable batteries are essential for widespread adoption of electric vehicles. Current Li-ion battery pack manufacturing processes rely on manual inspections to ensure electric vehicle battery quality. Such manual quality control is prone to errors, increasing the chances of defective batteries. This is likely to increase safety and reliability concerns in the public imagination, slowing down the adoption of electric vehicles. Furthermore, manual inspection is time-consuming and likely to become a bottleneck in scaling up electric vehicle battery production. A potential solution to address this need for fast and accurate inspection of batteries is the use of machine vision and robotics. In this study, we use digital twin design and simulation to develop a battery module inspection system that uses cobots and machine vision to inspect electric vehicle batteries for defects. Our proposed system can automate visual quality checks that are currently being done by human operators. The proposed cobotic system has been simulated and validated for a variety of battery defects to achieve fast and reliable detection. Since a digital twin of the cobotic inspection workcell has been used, the battery inspection system, as designed and validated, is ready for immediate implementation. [ABSTRACT FROM AUTHOR]

The new energy vehicle (NEV) is emerging as an important alternative in the automobile industry in its potential to alleviate environmental pollution and contribute to carbon neutrality. The rapid growth of NEVs has been reflected in the scaling up of electric vehicle battery production. The dramatic increase of retired batteries, however, exposes the technological limitations in current recycling operations, which will ultimately impede the sustainable development of the NEV supply chain. Blockchain technology (BT) adoption provides a solution by contributing to the construction of an efficient recycling network. Our research investigates the influence of carbon reduction instruments on the uptake of BT. The key findings are as follows. Under a carbon tax system, (1) carbon emission reduction encourages the battery supplier to adopt BT; (2) BT adoption increases the profits of NEV supply chain stakeholders. Under carbon cap-and-trade regulations, (1) the unit outsourcing fee and the performance of the BT impact the investment decision of the manufacturer; (2) the profit of the third-party enterprise is increased by introducing the BT. Under both policies, improving the efficiency of BT helps to upgrade the traceability level and contribute to carbon neutrality in the NEV supply chain. [ABSTRACT FROM AUTHOR]

To achieve California’s ambitious climate goals, a shift to hydrogen fuel for some transportation sectors may be essential.In this report, we explore the build-out of a hydrogen fuel distribution system including uptake of light-, medium-, and heavy-duty fuel cell electric vehicles. Our analysis of Base and High Case scenarios includes costs of building and operating a hydrogen vehicle and fuel system and estimates workforce impacts. We consider scenarios with about 125,000 vehicles by 2030 in the Base Case and 250,000 in the high case. This increases by an order of magnitude to 2045. Vehicle and station investment costs associated with the Base Case reach anywhere from $4 to 12 billion USD by 2030 and increase by a factor of eight by 2045. Costs per kg of hydrogen, including fuel transmission to stations and station costs delivered to vehicles, could be in the range of $4 to 8 per kg. This becomes $6 to 10/kg as a final delivered cost, if production of hydrogen were to cost $2/kg. Workforce impacts in the Base Case include 600 to 2,200 jobs created by 2030, rising rapidly thereafter. This report was prepared by the ITS-UC Davis Energy Futures Hydrogen Program in partnership with the UCLA Luskin Center for Innovation.

Under the Advanced Clean Cars II (ACC II) rule, California must move to 100% zero emission vehicle (ZEV) sales by 2035. Tomake this transition equitable, it is important to understand how we can support ZEV adoption in all communities–including rural communities. The aim of this study is to explore the experiences and perceptions of current rural plug-in electric vehicle (PEV) owners, identify barriers to charging and ownership, and suggest factors to guide the development of infrastructure in rural areas. (PEVs include battery-electric vehicles [BEVs] and plug-in hybrid vehicles.) Semi-structured interviews were conducted with rural PEV owners and included questions related to travel behavior, at-home and public charging experiences, and motivation for household vehicle purchase. Major themes were extracted from the interviews including that PHEV owners tend to have minimal at-home and public charging requirements, while BEV owners require access to Level 2 charging at home and reliable fast charging in public spaces. Additionally, the magnitude of public charging reliability and availability issues appear to be greater in rural than non-rural areas. Grid reliability issues and specific vehicle requirements were also points of discussion among rural PEV owners. The findings of this report could inform policy makers, car manufacturers, and PEV charging companies to better serve rural communities in the transition to 100% PEV sales.

As electric vehicle adoption accelerates and demand increases, the inability to produce batteries in sufficient quantities has emerged as a critical bottleneck in the electric vehicle supply chain. Given the impending climate change crisis, resolving this bottleneck is imperative to accelerate the transition to a zero-emission electric mobility future. One potential solution is the use of robotics for fast and cost-effective assembly of batteries at scale. This study proposes a three-stage digital twin design and analysis method to develop robotic workcells for fast and cost-effective assembly of electric vehicle battery modules. Using digital twin design and simulation, robotic assembly line configurations have been developed for battery module production at different scales. Digital twin analytics was used to evaluate and optimise the proposed robotic battery assembly system for speed and cost. Industrial automation experts were consulted to further improve robotic work cell layouts to minimise investment in robots. Because digital twins of robotic workcells have been used, the configurations of the battery assembly line, as designed and validated, are ready for immediate implementation. For practitioners, this study offers heuristic methods to determine the appropriate assembly line configuration, the required number of robots and humans, for a desired production volume. For researchers, this study outlines promising areas for future investigation. [ABSTRACT FROM AUTHOR]

This paper proposes an auction-based market trade mechanism for the electric vehicle battery recycling (EVBR) problem, which aims to realise the optimal resource allocation and pricing of EVBR. The main motivation of this paper is to attempt to explore an approach to achieving efficient battery recycling. We first consider an EVBR market with m buyers and n sellers, and develop the multi-unit trade reduction (MTR) mechanism in the EVBR market. According to the supply and demand relationship in the EVBR market, we consider three market scenarios of supply and demand balance, oversupply, and overdemand, and formulated corresponding auction allocation rules. Numerical study results show that the proposed MTR mechanism can achieve efficient resource allocation. We also observed that not all results increased with the number of sellers/buyers. Second, considering the distance between sellers and buyers, we developed a stochastic multiple MTR (SM-MTR) mechanism to enable sellers and buyers within the region to conduct transactions. Finally, we propose an integrated MTR, SM-MTR and one-sided Vickrey--Clarke--Groves auction mechanism that is feasible in both one-sided and bilateral environments. Furthermore, our work can provide novel managerial implications for EVBR market stakeholders in terms of practical application. [ABSTRACT FROM AUTHOR]

The primary metric for measuring electric vehicle (EV) adoption growth is new car sales. However, to enable mass market penetration, EV adoption in the used car market will play a crucial role. The used vehicle market is relatively under-studied or has been studied mostly for specific regions. This project analyzed US national consumer expenditure survey data that tracks households' expenditure on vehicle acquisition and operation. The study aim is to understand new versus used vehicle choice behavior and the consequent cost of vehicle ownership, with the larger aim of determining how much households who generally buy used vehicles can gain or lose if they transition from a used internal combustion engine vehicle (ICEV) to a used EV. A choice model and cluster analysis showed that ownership of used vehicles is influenced by family size, income, housing tenure, and age. For lower-income renters, current vehicle ownership and purchase costs tend to constitute a high fraction of their household income, raising concerns related to equity and suggesting that these households in particular should be considered in policies to encourage the EV transition. Moreover, while at present the average price paid for a used ICEV is approximately $18,000, the price of a comparable used EV can range between $14,000 (e.g., lower electric range Nissan Leaf) to $50,000 (high-range Tesla), suggesting the need for incentives to encourage the used EV market.

To mitigate climate change and air pollution, multiple US states and other countries have beensetting and adjusting goals and policies aimed at shifting sales from conventional, fossil-fuel–powered vehicles to plug-in electric vehicles (PEVs), defined as plug-in hybrid and battery electric (all-electric) vehicles. For example, US policies have offered federal tax credits for the purchase of PEVs, with limits set on how many PEVs from a single manufacturer, which PEVs, and which consumers qualify. A key to developing or adjusting these policies is understanding how financial incentives affect consumers’ decisions to purchase or lease PEVs. To better understand the impact of financial incentives on PEV leasing and purchasing, researchers at the University of California, Davis, analyzed survey responses from approximately 2,800 California PEV owners. The survey asked: If the federal tax credit were not available would you: purchase or lease the same PEV, switch to a different PEV, switch to a conventional or hybrid (non-plug in) vehicle, or not acquire a vehicle at all? This policy brief discusses findings from those survey responses and provides policy implications. View the NCST Project Webpage

Lithium-ion batteries (LIBs) are the enabling technology for modern electric vehicles (EVs), allowing them to reach driving ranges and costs comparable to internal combustion engine vehicles, an important development with EVs being integral to greenhouse gas mitigation efforts. However, LIB advancements include the use of rapidly evolving and chemically diverse batteries as well as larger battery packs, raising concerns about battery production sustainability as well as battery end-of-life (EoL). This study seeks to respond to these concerns by analyzing potential pathways for EoL EV batteries, quantifies flows of retiring EV battery materials, proposes economically and environmentally preferable LIB EoL strategies, and recommends pertinent policies with an emphasis on environmental justice. The researchers used a loosely coupled dynamic systems model that utilized life cycle assessment and material flow analysis and a mixed methods research approach. They find that the U.S. can make significant gains in securing supply chains for critical materials and decrease life cycle environmental impacts through the adoption of Recycled Content Standard policies similar to those found in the European Union. In addition, they examine the currently understood waste hierarchy in the context of LIB technology. Comparing immediate recycling to repurposing and reusing, they find that repurposing and reusing reduces life cycle environmental impacts relative to recycling. This project also includes an investigation of EoL battery collection and transportation and the vehicle afterlife ecosystem, as well as general stakeholders in the LiB life cycle, informed by expert interviews and a case study of a developing lithium industry in Imperial, California.View the NCST Project Webpage

This paper describes a model for developing highly resolved, time-of-day specific electric vehicle charging demand profiles from travel survey data. Since timing of vehicle charging is dependent on electric vehicle supply equipment (EVSE) availability, four EVSE scenarios are considered: 1) home only, 2) home and workplace only, 3) universal EVSE, and 4) a probabilistic scenario where EVSE availability varies by location. To illustrate the implications of differing demand profiles on power grid operation with high renewable generating capacity, the profiles are in a typical regional economic dispatch model. The results provide a valuable approach for understanding the interactions between vehicle electrification and renewable energy deployment while exploring an updated range of assumptions about EVSE availability and charging behaviors for New York and the six New England states. All scenarios result in increased peak demand and increased generation by non-renewable generating sources. This indicates that incentive mechanisms that influence charging decisions are necessary to attain lower emissions outcomes.View the NCST Project Webpage

Fuel cell technology emerges as a promising green solution, offering mitigation to global warming, air pollution, and energy crises. This eco-friendly approach is witnessing a surge in adoption within the automotive sector, with fuel cell buses, cars, scooters, forklifts, and more, becoming increasingly prevalent. The automobile industry has been rapidly advancing fuel cell technology, inching closer to the commercialization of fuel cell vehicles. As various technical hurdles are surmounted and costs are reduced, fuel cell vehicles are poised to become a competitive force in the automobile market, presenting an excellent solution for environmental sustainability and energy efficiency. This review paper delves into the fundamentals of fuel cells, their characteristics, and their applications in the automotive realm, exploring their prospects in comparison to traditional technologies. Furthermore, it sheds light on the existing research and industrial developments in hydrogen and fuel cell technologies. Additionally, a comprehensive comparison is provided between various fuel cell cars that have already been commercialized, enabling readers to understand the current market landscape. The review also analyses the advantages and challenges associated with fuel cell technology, offering insights into its future development trajectory. Through this comprehensive exploration, readers can gain a deeper understanding of fuel cell technology and its potential in revolutionizing the automotive industry. [ABSTRACT FROM AUTHOR]

The implementation of hydrogen fuel cell vehicle (HFCV) policies represents a crucial strategy in addressing global warming within the transportation sector. This study assesses the impact of these policies on HFCV-related stock returns from 2019 to 2023, utilizing static and dynamic contagion tests to construct a contagion network. The results indicate several key findings: (1) both fuel cell (FC)- and hydrogen-oriented policies exhibit significant contagion effects across the HFCV supply chain, particularly between FC/hydrogen sectors and their upstream, midstream, and downstream counterparts, with stronger contagion pre-2021 and a modest decline post-2022; (2) in 2020, FC-oriented policies dominated contagion dynamics, with a notable shift towards hydrogen-oriented policies after 2021; (3) prior to 2021, contagion rates reached as high as 80%, largely driven by higher-order co-moments rather than linear correlations, but declined to below 25% after 2021; (4) upstream sectors within the HFCV supply chain are more sensitive to policy contagion compared to midstream and downstream sectors; and (5) among the 10 policies analyzed, the 2021–2023 New Energy Vehicle Industry Development Plan had the most substantial impact, both driving and receiving policy shocks within the HFCV network. These findings offer critical insights into the energy-economic interactions shaping the HFCV market, providing valuable guidance for policymakers and industry stakeholders aiming to promote sustainable transport strategies. • To study policy impact on HFCV industrial chain stock returns. • Use the contagion test to judge the impact of policy shocks on related sectors. • Upstream HFCV sectors are more receptive to policy contagion. • New Energy Vehicle Industry Development Plan wields the strongest influence. [ABSTRACT FROM AUTHOR]

The increasing adoption of electric vehicles (EVs) presents both opportunities and challenges for power networks. While EVs have the potential to reduce carbon emissions, accommodating their growing power demand requires careful planning to prevent overloading and mitigate environmental impacts. This paper introduces an integrated hosting capacity model to facilitate higher EV penetration while maintaining environmental standards. In addition to EV charging stations, the model incorporates transmission lines, reactive power compensators, energy storage systems, and thyristor-controlled series compensators to ensure a reliable power supply. The model aims to maximize EV charging station deployment, minimize greenhouse gas emissions, and optimize net present value through hosting capacity strategies. Three hosting capacity plans are proposed to analyze the impact of prioritizing one of these objectives over the others in network configurations. Accurate EV demand forecasting is critical for this model, and a swarm intelligence forecasting algorithm is proposed to explore various forecasting approaches. The model is complex and involves nonlinear multi-objective optimization. To solve it, a new hybrid optimization algorithm is introduced, combining the features of the Marine Predators Algorithm and the Honey Badger Algorithm. Three hybridization schemes—Series Hybrid Scheme, Population Division Scheme, and Switching Strategy Scheme—are developed to address the optimization challenges effectively. The results show that the first and second hybridization schemes are the most effective for solving the EV load forecasting models, with a robustness of at least 90%. In contrast, the robustness of the third scheme reaches only 30% in some models. Simulation studies on the IEEE 9-bus network and the IEEE 30-bus system validate the model's effectiveness in integrating EVs while achieving environmental sustainability objectives. The findings show the superiority of the proposed hybrid schemes in solving the hosting capacity model in terms of finding optimal solutions. However, the third scheme required less computing time than the others, with its convergence time being at least 33.3% shorter. [ABSTRACT FROM AUTHOR]

We present a dynamic perspective to quantify the air quality–related health impacts of the electrification of light-duty vehicles in the United States between 2022 and 2050. Using a fleet turnover model and future electricity generation mix scenarios, we compare ambitious vehicle electrification to fleet renewal relying on newer internal combustion engine vehicles, without electric vehicles. The model includes vehicle-level pollutant emission factors and a reduced complexity air quality and valuation model and covers direct (tailpipe, brake wear, and tire wear) and indirect (production of electricity and liquid fuels) emissions of NOx, SO2, PM2.5, NH3, and VOCs, with a breakdown at the county level to identify geographical disparities in the distribution of health impacts. Short-term health benefits are mostly generated by reductions in NOx emissions from newer gasoline vehicles, while fleet electrification generates further benefits in the long term. The electricity mix plays a crucial role in the success of electrification policies. With continued grid decarbonization, electrification would reduce harmful air quality– related health impacts cumulatively by 84 to 188 billion USD over the study period, compared with fleet renewal without electric vehicles. In contrast, artificially freezing the 2022 grid would make electrification responsible for 32 to 71 billion USD additional health disbenefits compared with fleet renewal. Finally, we show that while fleet electrification achieves most of its benefits over fleet renewal in the long term, delaying the implementation of such policies would sacrifice meaningful cumulative benefits. [ABSTRACT FROM AUTHOR]

Disasters often require large-scale evacuations, and damage key infrastructure (e.g., power, transportation). With growing electric vehicle (EV) adoption and electrification of transportation, governments and utilities may face significant power challenges during disasters, especially during the evacuation stage. Low state-of-charge, sporadic charging infrastructure, or power outages could significantly hamper safe and effective evacuations. Yet, EVs also offer possible resilience benefits to emergency response by more easily charging electronics or sending power back to the grid through vehicle-to-grid (V2G) technology. This paper focuses on the opportunities, benefits, and drawbacks of EVs in disasters and evacuations through a systematic review of current literature, reports, and sources. Overall, this review discovered EVs show promise as modes of transportation and mobile energy supply units. However, crucial challenges such as charging infrastructure locations, upfront cost of resilience technologies, and user behavior necessitate more dedicated research to overcome shortcomings and guide more realistic implementation of benefits. [ABSTRACT FROM AUTHOR]

Bipolar plates (BPPs) and membrane electrode assemblies (MEAs) are the key components for proton exchange membrane fuel cells (PEMFCs), they are alternately arranged to construct a compact stack with high power generation. This stacking method may introduce several issues, such as the difficulties in maintenance, imprecise assembly and sealing. This paper presents a novel integrated packaged single fuel cell that employs titanium metal bipolar plates to construct a short stack with superior sealing performance and working reliability. To predict the performance of integrated packaged single cell, numerical model was developed to analyze the mass transfer of O 2 , H 2 and H 2 O within the cell, revealing a uniform distribution of reactants and current. A short stack was manufactured with 10 layers of single cells, it retains excellent sealing properties and consistent output across a range of pressure conditions, with a leakage rate deviation lower than 0.03 mL/(min·cell) and membrane current density variation less than 5%. Finally, the electrochemical performance of the integrated packaged short stack was tested, its maximum power is 886.67 mW/cm2. It can achieve a rated output power of 169.14 W and an energy density of 1684.97 mW/cm3. Thus, our developed short stack has high energy utilization efficiency for power generation, and is anticipated to provide a durable power source for drones, robots and new energy vehicles. • An integrated packaged single fuel cell short stack based on titanium metal polar plates was proposed. • Numerical model of single cell was established, simulation on gas molar concentration and current density distribution was conducted. • A 10-layer integrated short stack was fabricated, assembly stress and polarization tests verified its good sealing performance. [ABSTRACT FROM AUTHOR]

Conventional fossil fuel-powered vehicles are gradually being replaced by electric and hydrogen vehicles in the transportation sector. Even with all the recognized benefits and recent advancements in energy efficiency, decrease of noise, and environmental impact reduction, the market of electric and hydrogen mobility is still not up to par. Allocating charging stations in metropolitan areas for electric vehicles is considered as one of the most significant obstacles preventing electric and hydrogen vehicles from becoming more widely used. In this paper, an efficient approach aimed at finding optimal locations for electric vehicles (EV) charging stations in urban areas is proposed. Particle Swarm Optimization algorithm technique is utilized with the proposed approach. Various parameters were taken into consideration in this work, such as the horizontal distance that EVs travel to reach charging stations (CSs), and positive slope that EVs face to reach charging stations. The optimization problem is formulated as a Mixed-integer problem. The objective function works on minimizing the energy consumption of EVs to reach CSs in the investigated area. Difference constraints are incorporated with the proposed approach in order to increase the accuracy and efficiency of the proposed approach. The proposed approach is applied on real world datasets and is experimentally validated using through comparison with Genetic Algorithm and the greedy approach. The results demonstrate that the proposed approach saves energy about 22% and 43% compared to the genetic algorithm and greedy technique, respectively. [ABSTRACT FROM AUTHOR]

It has been widely suggested that the transition to battery electric vehicles will require 30% fewer assembly workers than those needed for internal combustion engine vehicles. Here, we use publicly available datasets on vehicle production and employment to show that labor intensity has increased at U.S. vehicle assembly plants that have fully transitioned to assembling battery electric vehicles. During the production ramp-up period, labor intensity increases by more than ten-fold compared to historic combustion vehicle assembly labor intensity. For one assembly site studied, labor intensity and total employment remained three times higher after a decade of electric vehicle production. Our study suggests that it may take longer than 15 years for electric vehicle assembly sites to achieve labor intensity parity with internal combustion vehicle assembly. Thus, rapid widespread loss of employment at vehicle assembly plants is a smaller risk than many fear. Moreover, our study calls for more regionally focused analyses of the transition's effects on labor using data-driven and macro-level surveying approaches. This study finds that U.S. vehicle assembly plants that have fully transitioned from gas engine to electric vehicle assembly have required higher labor intensity. It suggests that more, not fewer, workers are needed for electric vehicle assembly. [ABSTRACT FROM AUTHOR]

Developing of lightweight materials with extremely low thermal expansion is crucial across various sectors. While Invar exhibits a coefficient of thermal expansion (CTE) below 3 × 10−6 °C−1, its heavy nature limits its applicability in electric vehicles and aerospace fields. The present study introduces Al6061/SiC composites produced by the nitrogen-induced self-forming aluminum composite (NISFAC) process, wherein CTE is successfully tailored down to an unprecedented value of 2.12 × 10−6 °C−1 at 100 °C by changing the volume fraction of SiC from 0 to 65%. In-situ AlN, formed at the interface between Al6061 and SiC particles during the NISFAC process, plays a crucial role in minimizing the thermal expansion of the composites by improving crystallographic match and adhesion between SiC particles and the Al matrix. [ABSTRACT FROM AUTHOR]