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1. Copper Mining and Vehicle Electrication

   Cathles, LM; Simon, AC (May 2024, International Energy Forum)

   Electric vehicles (EVs) require substantially more copper and other metals than conventional internal combustion engine (ICE) vehicles. For example, manufacture of an ICE automobile requires 24 kg copper whereas manufacture of an EV requires 60 kg. Many have expressed concern that the lack of critical mineral resources may not allow full electrification of the global vehicle transportation fleet, and the vehicle electrification resource demand is just a small part of that needed for the transition. By displaying both demand and mine production in full historical context we show that copper resources are available, but 100% manufacture of EVs by 2035 requires unprecedented rates of mine production. The 100% EV target not only requires significant extra copper for battery manufacture, but also more copper for grid upgrades to support charging, while hybrid electric vehicles do not require extra grid capacity. Under today’s policy settings for copper mining, it is highly unlikely that there will be sufficient additional new mines to achieve 100% EV by 2035. Policymakers might consider changing the vehicle electrification goal from 100% EV to 100% hybrid manufacture by 2035. This would allow for future output of existing and new copper mines to be used for the developing world to catch up with the developed world in electrification. Life cycle emissions for battery electric vehicles compared with hybrid electric vehicles are comparable with each other. Mining must be recognized as essential, and exploration and responsible copper mine development strongly encouraged. 

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2. Electric Vehicle Adoption Behavior and Vehicle Transaction Decision: Estimating an Integrated Choice Model with Latent Variables on a Retrospective Vehicle Survey

   https://doi.org/10.1177/03611981231184875  

   Nazari, Fatemeh; Noruzoliaee, Mohamadhossein; Mohammadian, Abolfazl Kouros (April 2024, Transportation Research Record: Journal of the Transportation Research Board)

   Electric vehicles (EVs) promise a sustainable solution to mitigating negative emission externalities of transportation systems caused by fossil-fueled conventional vehicles (CVs). While recent developments in battery technology and charging infrastructure can help evolve the niche market of EVs into the mass market, EVs are yet to be widely adopted by the public. This calls for an in-depth understanding of public adoption behavior of EVs as one dimension of vehicle decision making, which itself may be intertwined with other vehicle decision-making dimensions, especially vehicle transaction. This study presents an integrated choice model with latent variables (ICLV) to investigate households’—as a decision-making unit—decisions on vehicle transaction type (i.e., no transaction, sell, add, and trade) and vehicle fuel type (i.e., CVs and all EV types, including hybrid EV, plug-in hybrid EV, and battery EV) choice. To analyze the ICLV model empirically, one of the first revealed preferences national vehicle survey involving CVs and all EV types was conducted, which retrospectively inquired about 1,691 American households’ dynamics of vehicle decision making and demographic attributes over a 10-year period as well as their attitudes/preferences. The model estimation results highlight that EV adoption and vehicle transaction choice is influenced mainly by (1) the dynamics of household demographic attributes and (2) four latent constructs explaining attentiveness to vehicle attributes, social influence, environmental consciousness, and technology savviness. Notably, EV adoption promotion policies are found to be likely most effective on socially influenced individuals, who tend to consider advertisement and social trend more when making vehicle decisions. 

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3. Leveraging Distributed EVs and PVs to Assess Networked Microgrids Resilience Against Extreme Weather Event

   https://doi.org/10.1109/PESGM48719.2022.9917224  

   Simental, Orlando Quezada; Mandal, Paras; Galvan, Eric; Wang, Zongjie (July 2022, 2022 IEEE Power & Energy Society General Meeting (PESGM))

   The development of new technologies is increasing transportation electrification and electric vehicles (EVs) are expected to become even more popular in coming years. High EV adoption rates can increase the potential to use EVs as an energy resource and operate in vehicle-to-grid (V2G) and vehicle-to-home (V2H). This paper focuses on the resilience analysis of using EVs and roof-top solar photovoltaic systems (PVs) to provide power support in network microgrids (MGs) experiencing an outage due to extreme weather conditions. To determine the effectiveness of using EVs and PVs as backup energy resources, a set of resilience metrics are evaluated for different cases and duration. Simulation results show that the management of EVs and PVs in residential networked MGs could provide power support for several hours during the restoration of a distribution system experiencing an outage. 

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4. PV to Vehicle, PV to Grid, Vehicle to Grid, and Grid to Vehicle Micro Grid System Using Level Three Charging Station

   https://doi.org/10.1109/GreenTech52845.2022.9772041  

   Balal, Afshin; Giesselmann, Michael (March 2022, 2022 IEEE Green Technologies Conference (GreenTech))

   This paper makes use of electric vehicles (EVs) that are simultaneously connected to the Photovoltaic Cells (PV) and the power grid. In micro-grids, batteries of the electric vehicles (EVs) used as a source of power to feed the power grid in the peak demands of electricity. EVs can help regulation of the power grid by storing excess solar energy and returning it to the grid during high demand hours. This paper proposes a new architecture of micro-grids by using a rooftop solar system, Battery Electric Vehicles (BEVs), grid connected inverters, a boost converter, a bidirectional half-bridge converter, output filter, including L, LC, or LCL, and transformers. The main parts of this micro-grid are illustrated and modeled, as well as a simulation of their operation. In addition, simulation results explore the charging and discharging scenarios of the BEVs. 

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5. Human-centered electric vehicle adoption framework for smart mobility: Modeling perceived range and charging anxiety as a psychological barrier

   https://doi.org/10.1177/27723577261447832  

   Nazari, Fatemeh; Mohammadian, Abolfazl Kouros (August 2026, Journal of Smart Cities and Society)

   Electric vehicles (EVs) offer a transformative pathway toward reducing the environmental, economic, and health-related externalities of internal combustion engine vehicles in urban settings. Despite substantial advances in battery technology, charging infrastructure expansion, and supportive policy incentives, EV penetration remains limited which poses challenges for smart and sustainable mobility planning. A critical yet insufficiently modeled barrier to adoption lies in the psychological perceptions surrounding electric driving range and charging reliability, which is commonly framed as “range anxiety,” but more broadly reflecting perceived range and charging anxiety. To address this gap, this study introduces a latent psychological construct capturing individuals’ perceived range and charging anxiety and integrates it into a two-level nested logit (NL) model of vehicle transaction and fuel type choice. The model jointly represents (a) vehicle transaction decisions (keep, sell, trade, and add) and (b) fuel technology choices (conventional vehicle, hybrid EV, plug-in hybrid EV (PHEV), and battery EV (BEV)), thereby providing a behaviorally realistic representation of household vehicle dynamics. Bootstrap-based inference is employed to ensure robust estimation of both measurement and structural parameters. Using the sample dataset from the State of California, the results show that perceived range and charging anxiety significantly reduces the likelihood of adopting BEVs, particularly in fleet-expansion (add) decisions, while exerting no significant effect on PHEV adoption. This distinction suggests that PHEVs may function as transitional technologies for consumers concerned about electric mobility reliability. The findings highlight the importance of smart mobility strategies that address not only technological performance and infrastructure deployment, but also psychological perceptions shaping consumer behavior. By embedding latent behavioral factors into the vehicle choice process, the proposed framework advances citizen-centered mobility modeling and provides a robust decision-support tool for urban planners and transportation policymakers seeking to accelerate sustainable vehicle transitions. 

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