The ambitious U.S. initiative to deploy public charging infrastructure for electric vehicles (EVs) is crucial for achieving climate targets. However, long charging times pose a challenge, particularly for long journeys. To address this, technologies like 350-kW DCFC, Battery Swapping (BSS), and Dynamic Wireless Power Transfer (DWPT) are being considered. DCFC offers scalability but presents grid challenges and consumer cost implications. BSS optimizes grid loads but depends on battery standardization and addresses social issues related to battery ownership and requires different sizes for various vehicle types. DWPT offers reduced dwell times but is capital intensive and may cause traffic disruptions. Despite understanding the individual performance of these technologies, a comprehensive analysis comparing their economic and environmental impacts across vehicle categories remains lacking. This study fills this gap by comparing the TCO and GHG intensity of EVs using these charging systems across the United States, considering various factors influencing their performance and adoption.

While many studies have assessed the charging costs and GHG intensity of EVs, a comprehensive comparison of different charging systems (DCFC, BSS, DWPT) and their implications across various vehicle categories (cars, light-duty trucks (LDTs), medium-duty vehicles (MDVs), heavy-duty vehicles (HDVs)) has been absent. This study addresses this gap by providing a nationwide analysis encompassing techno-economic and life cycle assessments of these charging systems.

The study employs an integrated techno-economic analysis (TEA) and life cycle assessment (LCA) to compare DCFC, BSS, and DWPT across the contiguous U.S. Four vehicle categories (cars, LDTs, MDVs, HDVs) were evaluated. The TCO and cradle-to-grave GHG intensity were determined for each EV charging system and compared to HEVs and ICEVs, using one vehicle kilometer traveled (VKT) as the functional unit. Infrastructure deployment was modeled for 2030, followed by a 20-year operational period (2031-2050). Public charging usage was assessed for each system: DWPT provided continuous in-motion charging, while DCFC and BSS provided energy during daytime trips. Vehicle energy efficiencies were defined for each vehicle category. Public charging usage for cars and LDTs was estimated based on existing data, while simulations were used for MDVs and HDVs, considering multiple operating ranges and battery sizes to minimize costs while ensuring sufficient range. The electrified roadway portion for DWPT was calculated based on speed limits, power ratings, number of receiving pads, vehicle efficiencies, and charging efficiency, considering potential system failures. Time-of-day usage was incorporated using data from the National Household Travel Survey and the National Renewable Energy Laboratory's Fleet DNA database, distinguishing in-route and dwell-period charging. Deployment scenarios considered optimistic, baseline, and conservative EV adoption rates, along with charging efficiencies and vehicle energy efficiencies. Potential charging site locations were identified and suitability assessed based on proximity to grid interconnections and minimum utilization. Charging site capacity constraints and minimum usage thresholds were implemented for DCFC and BSS. DWPT infrastructure was deployed on major roadways to maintain vehicle state-of-charge. The TEA used discounted cash flow rate of return (DCFROR) to evaluate charging costs and TCO, including capital costs, operational costs, electricity costs, and utilization, considering various scenarios for capital costs, electricity prices, and fuel prices. The LCA assessed GHG intensity, dividing emissions into charging emissions, embodied charging infrastructure emissions, and embodied vehicle emissions. Electricity mix scenarios (optimistic, baseline, conservative) were used to determine charging emissions, using data from Cambium (2022). Embodied vehicle emissions were determined using GREET (2022), considering battery types, sizes, and replacements. Equations (1-9) are provided for various calculations in the paper. Details on data sources for various parameters including costs, electricity prices, fuel prices, etc., are extensively described in the paper.

The study's findings reveal significant location-dependent variations in the economic and environmental impacts of EV adoption. **Cost Savings from EV Adoption:** Figure 1 shows the county-level change in TCO from switching from ICEVs to EVs for DCFC, BSS, and DWPT. The economic impacts are location-dependent, significantly influenced by local fuel and electricity prices, and traffic volumes. High-traffic areas show substantial TCO reductions, while low-traffic areas might see increases. DWPT shows the largest TCO variation due to its heavy dependence on infrastructure utilization. Figure 2 shows a national-level breakdown of 10-year TCO for different vehicle types and charging systems. Depreciation is a major cost component. EV maintenance costs are higher for HDVs due to battery replacements. DWPT-EVs for HDVs show cost advantages due to reduced battery size. Electric MDVs charged via DCFC or BSS show cost advantages only in high fuel price scenarios, while DWPT-MDVs have lower costs across all fuel price scenarios. **Reduction in Greenhouse Gas Emissions:** Figure 3 displays the county-level change in GHG emissions from EV adoption for the three charging systems. The results depend on the local electricity mix (for DCFC and BSS) and infrastructure utilization (for DWPT). In some locations, the scenarios for electricity mix and EV adoption influence whether EVs reduce or increase GHG emissions. High utilization and clean grid reduce emissions, while low utilization and high-carbon electricity mix increase emissions. Figure 4 provides a national-level breakdown of lifetime GHG intensity for various vehicle types and charging systems. Infrastructure emissions are minimal for DCFC-EVs but significant for BSS-EVs and DWPT-EVs. HEVs show emissions reductions compared to ICEVs but still higher than EVs. **Overall Impacts (2031-2050):** Compared to ICEVs, on-road transportation costs can change from -22% to +11%, and GHG emissions from -53% to -19%, depending on the scenarios. Annual average electricity generation would increase by 16% to 38%. Controlling charging loads from BSS and DWPT could reduce grid capacity upgrades. Total battery production needs range from 13 to 31 terawatt-hours, potentially straining production capacity. DWPT reduces battery production needs by 79% but requires substantially higher capital investment (134B to 1.7 trillion USD). DCFC is the most mature technology but has limited availability for MDVs and HDVs. BSS has seen deployment in China but faces social barriers in the U.S. DWPT faces challenges in technological readiness and consumer receptivity.

The study's findings highlight the complex interplay between technology choices, policy decisions, and location-specific factors in determining the economic and environmental benefits of EV adoption. The significant variations in TCO and GHG emissions across different regions underscore the need for location-specific strategies and policies. The results demonstrate that while EVs offer potential for significant GHG emission reductions nationally, the actual impact depends heavily on the electricity mix and the level of EV adoption. The findings also reveal the trade-offs associated with different charging technologies, emphasizing the importance of carefully considering the techno-economic and environmental aspects of each option. The high capital investment required for DWPT raises questions about financing strategies and the need for efficient resource allocation. The social acceptance and standardization challenges for BSS need addressing for successful large-scale deployment. Further research could focus on optimizing charging infrastructure deployment strategies based on region-specific characteristics, integrating user behavior models, and assessing the long-term impacts on the electricity grid and related industries.

This study provides a comprehensive analysis of the costs and climate impacts of different EV charging systems across the United States. The findings demonstrate that EV adoption offers significant potential for reducing GHG emissions and transportation costs, but the extent of these benefits is highly dependent on technological choices, deployment strategies, and the decarbonization of the electricity grid. Future research should explore optimized deployment strategies considering regional variations, and investigate the long-term impacts on the grid and related sectors.

The study focuses solely on public charging costs, excluding home, workplace, and fleet charging, which might influence the overall TCO and GHG intensity. The model's accuracy depends on the accuracy of input data, particularly regarding future EV adoption rates, electricity prices, fuel prices, and technological advancements. The LCA uses an attributional approach, which doesn't fully capture the dynamic nature of GHG emissions from electricity generation. The study also considers simplified assumptions about battery life and replacement costs.