Widespread Adoption Of Electric Vehicles Research Articles

Smart Slot Assignment for Urban EV Charging Using Folium API Integration

Abstract: Efficient management of electric vehicle (EV) charging distribution in urban areas is crucial amid increasing demand and varying traffic conditions. This study proposes a novel web-based solution that integrates Folium Map API for realtime location tracking and Python Flask backend with MySQL database storage to allocate charging demands. By leveraging real-time traffic information from the Folium Map API, the proposed model optimizes charging resource allocation across multiple stations and road networks. The web interface, built using HTML, CSS, and JavaScript, allows users to interact with the system seamlessly. Charging allocation is dynamically adjusted based on real-time data, prioritizing maxi- mum returns. Additionally, an emergency charge counter facility is introduced to cater to unforeseen charging needs, enhancing user flexibility. The system offers two interfaces and a dashboard for both station administrators and users, en- abling pre-booking services for travelers during their journey, facilitating access to nearby charging stations, and providing a facility for prebooking. These features contribute to improved station revenue and pile utilization, highlighting the efficacy of the proposed web-based approach. By leveraging advanced web technologies and APIs, this comprehensive strategy enhances charging infrastructure efficiency, fosters the widespread adoption of electric vehicles, and contributes to sustainable urban mobility management.

Smart allocation and sizing of fast charging stations: a metaheuristic solution

ABSTRACT The widespread adoption of electric vehicles (EVs) hinges significantly on effective network management, particularly the allocation and sizing of fast-charging stations (FCS) for EV users. Applying queuing theory based on M/M/c, the model seeks to identify the most effective number of chargers to minimise waiting time for electric vehicle users and ensure optimal utilisation of the FCS. The problem is formulated as a multi-optimisation problem where finding the optimal solution is done by implementing the non-dominated sorting genetic algorithm focusing on EV user satisfaction, voltage stability, and carbon dioxide emissions. Simulation results indicate that the model successfully enhances EV user satisfaction, environmental impact, and overall FCS utilisation. In a comparative analysis with state-of-the-art models, the proposed approach demonstrates a notable 40% improvement in EV user satisfaction and a significant 45% enhancement in FCS utilisation. This proves the effectiveness of the proposed model in optimising the performance of the network.

Clean energy synergy with electric vehicles: Insights into carbon footprint

This study empirically examines the impact of Electric Vehicles (EVs) and clean energy adoption on carbon footprints. With growing concerns over climate change and the need to reduce greenhouse gas emissions, the transition to electric vehicles and clean energy sources has gained significant attention as potential solutions. This research investigates the relationship between the adoption of EVs and clean energy technologies and their subsequent effect on carbon footprints. The study applied the Generalised Method Moments (GMM) on the data sourced from the International Energy Agency (IEA) and the World Development Indicators (WDI) for the period 2011–2021 covering 27 countries. The findings reveal a strong correlation between the adoption of EVs and reductions in carbon footprints. It shows that a 1 % increase in renewable electricity output would result in a 0.5 % decline in carbon footprints. This implies that, as EV sales increase, the overall carbon emissions from the transportation sector decrease, primarily due to the lower emissions associated with electric vehicles compared to conventional internal combustion engine vehicles. Additionally, the study finds that the integration of clean energy sources into the electricity grid further contributes to carbon footprint reductions. The use of renewable energy in charging EVs minimizes the indirect emissions associated with electricity generation. The research concludes that the widespread adoption of EVs and clean energy sources has the potential to significantly reduce carbon footprints and mitigate the impact of climate change. However, it emphasizes the importance of continued technological advancements, increased availability of charging infrastructure, and supportive government policies to accelerate the transition towards a low-carbon transportation and energy system. Therefore, the study highlights the need for collaborative efforts among governments, industry stakeholders, and individuals to foster sustainable practices and achieve a more environmentally friendly future.

Charging Ahead- Addressing Key Barriers to Electric Vehicle Market Penetration in India

The transition to electric vehicles (EVs) represents a pivotal step towards sustainable transportation, particularly in the context of India's burgeoning population and rapid urbanization. Despite significant potential, the widespread adoption of EVs in India is hampered by various barriers, including infrastructure limitations, policy gaps, high upfront costs, and consumer perceptions. This research paper aims to analyze these key barriers and propose strategies to accelerate the market penetration of EVs in India. Through a comprehensive literature review, policy analysis, and examination of case studies, this paper identifies the challenges hindering EV adoption and offers recommendations for addressing them. Proposed strategies include infrastructure development, policy interventions, consumer awareness initiatives, and technological innovations. By implementing these recommendations, India can overcome barriers to EV adoption and realize the environmental and economic benefits associated with clean mobility.

Wireless Charging of Electric Vehicle on Highways in Running Mode by Solar Energy

Abstract: The adoption of electric vehicles (EVs) is on the rise globally, driven by the need for sustainable transportation solutions to mitigate climate change and reduce dependence on fossil fuels. However, the infrastructure for charging EVs remains a significant challenge, hindering widespread adoption. In response, innovative approaches such as wireless charging technology, coupled with solar energy, have emerged to address these challenges. This paper presents an overview of wireless charging systems for electric vehicles, integrated with solar energy, aiming to provide a sustainable and convenient solution for EV owners. The integration of wireless charging and solar energy offers numerous benefits, including convenience, efficiency, and environmental sustainability. By eliminating the need for physical connections and harnessing the power of the sun, electric vehicles can be charged seamlessly and sustainably, reducing reliance on the grid and lowering carbon emissions. This paper discusses the principles behind wireless charging technology, the design considerations for integrating solar energy, and the potential impact on the future of sustainable transportation. Additionally, it addresses the challenges and opportunities associated with this innovative approach, highlighting the need for further research and development to realize its full potential. Overall, the convergence of wireless charging technology with solar energy represents a promising solution to the challenges facing the widespread adoption of electric vehicles, contributing to a cleaner and greener transportation ecosystem.

A FEASIBILITY ANALYSIS OF ZERO-CARBON EMISSION THROUGH ELECTRIC VEHICLE

The transition towards zero-carbon emissions represents a critical imperative in combating climate change and promoting sustainable development. This master thesis project explores the feasibility of achieving zero-carbon emissions through the widespread adoption of electric vehicles (EVs). Framed within the context of entrepreneurship and innovation, the study examines the current trends, challenges, and opportunities surrounding EVs and green energy initiatives. A comprehensive literature review highlights the environmental, performance, and cost-related disparities between EVs and traditional gasoline-powered vehicles, while also identifying key barriers to adoption such as range anxiety and infrastructure limitations. Employing a mixed-methods approach, the research synthesizes secondary and primary data sources to propose strategic interventions aimed at accelerating EV adoption, including the establishment of residential charging stations, mobile EV charging units, and discounted charging infrastructure. Furthermore, the study advocates for the development of a centralized application to streamline EV charging accessibility and utilization. By addressing these challenges and implementing targeted solutions, this thesis underscores the pivotal role of innovation and collaboration in realizing a future powered by zero-carbon emissions through electric mobility.

A novel approach to evaluating the accessibility of electric vehicle charging infrastructure via dynamic thresholding in machine learning

The spatial deployment of urban public electric vehicle charging stations (PEVCSs) plays a pivotal role in the widespread adoption of electric vehicles (EVs). However, with the rapid advancements in EV technology and battery capabilities, substantial improvements in both range and charging efficiency have emerged and are expected to continue experiencing sustained growth. This situation underscores the urgent necessity of establishing dynamic metrics to reconsider the existing static charging infrastructure, aiming to ameliorate the current severe spatial imbalances and supply–demand disparities encountered in the deployment of PEVCSs. In this study, we harnessed and analyzed 84,152 sets of authentic data, fine-tuned through geospatial-aggregation technology, and ensured anonymity. Our findings bridged users’ residential and occupational patterns with their charging propensities. Comparing these with the spatial distribution of current charging stations revealed that Beijing and Shenzhen’s infrastructure aligned with the cities' economic, educational, and residential zones, epitomizing a synergy in provisioning. However, certain areas experienced either a demand–supply imbalance or an oversupply. To address these challenges, we introduced the Charging Access Reachability Index (CARI) using machine learning techniques. This dynamic metric serves as a tool for quantifying the effective coverage range of charging facilities. Its adaptive threshold holds potential as a crucial indicator enabling the dynamic transition towards more efficient and resilient charging infrastructure.

Deciphering Determinants for Adoption of E-Mobility

lectric vehicles represent a paradigm shift in transportation, offering a clean, quiet, and environmentally friendly mode of travel. India, as a significant market for electric vehicles, aims to become a predominantly electric vehicle-driven nation by 2030, marking a remarkable endeavor toward sustainability. The global automotive landscape reflects a growing trend towards electric mobility, with nearly every major manufacturer incorporating electric vehicles into their product lineup. This widespread acceptance underscores the increasing demand for eco-friendly transportation options worldwide. Governments worldwide have implemented various policies to promote electric mobility, with encouraging results. However, achieving India's ambitious goal requires a comprehensive policy framework aimed at phasing out fuel run vehicles and incentivizing the adoption of electric vehicles. To expedite the transition, policies should discourage the further proliferation of traditional gas vehicles while introducing initiatives to facilitate the widespread acceptance of electric vehicles. This includes the implementation of schemes to make electric vehicles more accessible and appealing to consumers. While the journey towards widespread adoption of electric vehicles is ambitious and challenging, with concerted policy efforts, it is indeed achievable. The implementation of effective policies and incentives is crucial in realizing India's vision of becoming an electric vehicle-centric nation by 2030. This paper aims to provide a comprehensive review of the factors influencing consumer acceptance of electric vehicles. By synthesizing existing literature and empirical research, the study seeks to shed light on the socio-economic, psychological, and technological determinants that shape consumer attitudes and behaviors towards EV adoption. Key words: E-vehicle, e-mobility, Consumer Attitude, Psychological Factors, Charging infrastructure.

Programmable logic controlled lithium-ion battery management system using passive balancing method

Advancements in electric vehicle technologies and the widespread adoption of electric vehicles have brought energy storage systems to the forefront. However, efficient and secure utilization of energy storage systems requires Battery Management Systems (BMS).BMSs are typically designed with power electronics, electronic cards, integrated circuits, and auxiliary hardware components. Nevertheless, BMSs designed with such microcontrollers can only control a limited number of battery cells and constrained current values. Furthermore, employing a separate controller for each battery pack exacerbates these issues.In this study, a Programmable Logic Controller (PLC) - based BMS proposal for lithium-ion batteries has been presented, aiming to address the challenges in existing BMSs. The developed system is a passive balancing BMS comprised of controller PLC modules and auxiliary hardware. The Ladder Diagram (LD) programming language was employed for programming the PLC.In the conducted research, the voltage levels of the cells comprising the battery pack were monitored, and a passive balancing method was employed to equalize the cell voltages. Passive balancing has been applied to cells with voltage values of 2.70 V, 2.40 V, and 2.80 V using the minimum reference voltage cell balancing method to equalize the voltage levels. The output voltage has been balanced according to the maximum reference charge voltage set at 6 V through the maximum reference charge voltage balancing method. Additionally, a cooling circuit was integrated into the system to safeguard the Battery Management System (BMS) against thermal hazards. The developed PLC controller and algorithm can effectively control multiple battery packs with a single controller and operate at higher current values. This advantage allows the PLC-controlled BMS to have a broader control capacity. The presented test results indicate the successful performance of the PLC-based BMS.

Influence of charging stations accessibility on charging stations utilization

The widespread adoption of electric vehicles has become pivotal in attaining emissions reduction objectives, and the rationale behind designing and situating charging stations determines the unfurling of electric vehicles. This scholarly work fully mines the geographical situational particulars underlying the functioning statistics of charging stations in Beijing during the period from January to March 2016. By incorporating the urban road network, we construct a charging stations accessibility index to investigate the influence of stations accessibility on utilization rates. The findings reveal a substantial positive relationship between the overall accessibility of charging stations and their utilization rates. However, the limited number of charging stations hinders the agglomeration effect from significantly boosting utilization rates. Moreover, the impact of charging station accessibility on utilization rates varies significantly across regions with different levels of development, indicating pronounced heterogeneity. The research conclusions of this paper provide useful suggestions for promoting the rational layout of charging stations.

Techno-Economic and Sustainable Challenges for EV Adoption in India: Analysis of the Impact of EV Usage Patterns and Policy Recommendations for Facilitating Seamless Integration

This paper explores the intricate challenges that are impeding the widespread adoption of Electric Vehicles (EVs) and explores the concerted efforts of the research community towards addressing these obstacles. The surge in interest surrounding EVs as a sustainable transportation alternative is undeniable, yet several hurdles persist in hindering their mass acceptance. From limitations in battery technology and charging infrastructure to concerns over range anxiety and manufacturing sustainability, these challenges form a multifaceted barrier. However, the research community has been actively engaged in tackling each issue with innovative solutions. Advancements in battery chemistry and energy storage, coupled with improvements in charging networks and smart grid integration, are poised to reshape the EV landscape. Moreover, studies on user behavior, public policy, and lifecycle analysis are contributing to the development of holistic strategies for enhancing EV adoption. By delving into these challenges and the ongoing research endeavors, this paper sheds light on the evolving pathway towards a future where EVs can thrive as a mainstream mode of transportation. Also, an analysis is conducted to evaluate the economic viability of EVs based on daily range considerations, with the objective of determining which category of users would benefit most from adopting EVs. Furthermore, policies are proposed that are aimed at establishing a harmonious and balanced EV ecosystem.

Innovative Compact Twin Whirly Bird-based Wind Turbine: A Sustainable Solution for EV Charging Infrastructure

The global adoption of whirly bird vent roofs across various industries underscores their utility in harnessing wind energy for cooling purposes within warehouses and similar environments. The innovation proposed in the current study builds upon this established technology by integrating semi-perpetual motion principles into a compact twin whirly bird-inspired wind turbine design. This novel approach aims to enhance power generation efficiency, thereby offering a sustainable solution for energy production. The compact twin whirly bird turbine concept represents a significant advancement, particularly in the context of powering electric vehicle (EV) chargers. As the demand for EVs continues to surge, concerns persist regarding the availability of charging infrastructure. By integrating the proposed innovative wind turbine technology into the EV charging ecosystem, we address this critical issue while simultaneously promoting the adoption of renewable energy sources. The key to our proposal is the deployment of small-scale wind turbines in diverse public locations, thereby democratizing access to clean energy generation. Unlike conventional large-scale wind turbines, our whirly bird-inspired turbines boast versatility in installation, akin to streetlamps, facilitating widespread deployment across urban landscapes. While these turbines may yield comparatively modest power outputs relative to megawatt-scale counterparts, their strategic placement ensures a decentralized network capable of powering EV charging stations. In summary, our research presents a compelling solution that bridges the gap between EV charging infrastructure availability and the utilization of renewable energy sources. By leveraging the inherent advantages of whirly bird-inspired wind turbines, we offer a practical pathway towards sustainable energy provision in public spaces, thereby facilitating the widespread adoption of electric vehicles.

Multi-objective optimization for multi-stage constant current charging for Li-ion batteries

Fast charging is a key challenge for the widespread adoption of electric vehicles (EVs), as it can make EVs more convenient and appealing to consumers. Therefore, different charging methods are proposed to enhance the performance of lithium-ion batteries (LIBs). Multi-stage constant current (MSCC) charging can improve LIB's performance in several aspects, including charging time, charged capacity, temperature rise, average temperature rise, and charging energy efficiency. However, achieving a multi-objective performance during LIB charging is challenging. In this paper, the Taguchi method is used to determine the multi-objective optimal (MOO) charging profile for the MSCC charging strategy. The Orthogonal experiments are designed and conducted to find the optimal solutions for each performance parameter for a five-stage constant current (5SCC) charging profile. A comparison is conducted among the performance-based selective charging profiles to validate the optimal charging profile. Furthermore, a comparison is made between the obtained MOO charging profile and the classical equivalent constant current constant voltage (CCCV) method. Experimental results demonstrated that the MOO charging profile reduces the charging time with comparable temperature rise to the CCCV, making it promising for the future alternative efficient EV charging. These findings highlight the effectiveness of the MSCC approach in improving LIB performance.

Combined K-Means Clustering with Neural Networks Methods for PV Short-Term Generation Load Forecasting in Electric Utilities

The power system has undergone significant growth and faced considerable challenges in recent decades, marked by the surge in energy demand and advancements in smart grid technologies, including solar and wind energies, as well as the widespread adoption of electric vehicles. These developments have introduced a level of complexity for utilities, compounded by the rapid expansion of behind-the-meter (BTM) photovoltaic (PV) systems, each with its own unique design and characteristics, thereby impacting power grid stability and reliability. In response to these intricate challenges, this research focused on the development of a robust forecasting model for load generation. This precision forecasting is crucial for optimal planning, mitigating the adverse effects of PV systems, and reducing operational and maintenance costs. By addressing these key aspects, the goal is to enhance the overall resilience and efficiency of the power grid amidst the evolving landscape of energy and technological advancements. The authors propose a solution leveraging LSTM (long short-term memory) model for a forecasting horizon up to 168 hours. This approach incorporates combinations of K-means clustering, automated meter infrastructure (AMI) real-world PV load generation, weather data, and calculated solar positions to forecast the generation load at customer locations to achieve a 5.7% mean absolute error between the actual and the predicted generation load.

Maximizing EV profit and grid stability through Virtual Power Plant considering V2G

The electrification of transportation through the widespread adoption of electric vehicles (EVs) has raised substantial concerns within the realm of power grid operations. This concern predominantly stems from the elevated electricity demand brought about by the surging population of EVs, consequently exerting strain on the power grid infrastructure which can be reduced with vehicle-to-grid (V2G) technology integration. To address this issue, this paper delves further into the realm of grid integration by introducing a Virtual Power Plant (VPP) concept to enhance the synergy between EVs and power grid. This study aims to compare different realistic objectives, ranging from total active power loss and voltage drop minimization to EV profit maximization and then optimize the balance between the distribution grid power quality and VPP profit through bi-level modeling. The presented model is devised as mixed-integer quadratically constrained programming (MIQCP) and incorporates Temporal Convolutional Network (TCN) based forecasting to handle the uncertain behavior of the residential loads using historical data. The experiments are conducted in IEEE 33-Bus and real-world 240-Bus distribution networks. The results indicate that enabling bidirectional power flow between the grid and VPP can yield significant profits for EV users while only marginally impacting the active power loss, approximately around 5%. This validation underscores how V2G not only presents various advantages for power system operators but also benefits EV users simultaneously.

Exploring Electric Vehicle Battery Lifespan: Implications and Strategies for Sustainable Mobility

The global transition towards electric vehicles (EVs) represents a profound evolution in consumer behavior, driven by a growing awareness of environmental sustainability and the imperative to reduce carbon emissions. The lifespan of EV batteries is central to the success and widespread adoption of EVs. This critical factor influences not only EVs' operational efficiency and reliability but also the automotive industry's overall sustainability. This research paper delves deeply into the intricate web of factors that impact EV battery lifespan, ranging from the fundamental principles of battery chemistry to the practical considerations of user behavior and maintenance practices. By dissecting these complexities, we aim to provide a comprehensive understanding of the mechanisms underlying battery degradation and longevity. Moreover, we explore manufacturers' innovative strategies and technological advancements to optimize battery performance, enhance lifespan, and mitigate environmental impact. Through this exploration, we seek to offer valuable insights and practical recommendations for industry stakeholders, policymakers, and consumers to accelerate the transition toward a more sustainable transportation ecosystem. By empowering stakeholders with knowledge and tools to maximize the potential of EVs, we can pave the way for a future characterized by cleaner air, reduced greenhouse gas emissions, and greater energy independence.

Transforming the transportation sector: Mitigating greenhouse gas emissions through electric vehicles (EVs) and exploring sustainable pathways

Transportation-related emissions in Pakistan have been rapidly increasing in recent years. This study aims to determine how important it is to electrify road transportation in Pakistan to reduce greenhouse gas (GHG) emissions from the transportation sector. Motivated by the need to tackle the growing environmental issues related to conventional fuel-powered automobiles, this research explores the application of electrification techniques in the context of Pakistan’s transportation system. During the 2019 fiscal year, the transportation industry in Pakistan consumed 23 × 106 tonnes of energy from the burning of fossil fuels and produced 52.9 × 106 metric tons of CO2, which made up 31% of the country’s total carbon emissions. In this research, different scenarios, such as business as usual, low carbon, strengthen low carbon, and Pakistan National Electric Vehicle Policy 2040, are evaluated for the transportation sector of the country. Using the LEAP model, this study projects the effects of electrification on Pakistan road transportation over 30 years. When estimating how electrification will affect road transportation in Pakistan over the next 30 years, several factors were taken into account, including policy frameworks, changing consumer behavior, technology advancements, and infrastructure improvements. The analysis covered the emission levels, adoption hurdles, and possible advantages of transitioning to electric vehicles (EVs). The outcomes illustrate that adopting EVs can produce substantial drops in fuel consumption and environmental emissions, providing a sustainable solution to mitigate global warming. This work is directly associated with various Sustainable Development Goals, including SDG3 (good health and well-being), SDG7 (affordable and clean energy), and SDG13 (climate action). The results of this study highlight the considerable potential for GHG reduction associated with the widespread adoption of EVs, offering crucial insights to stakeholders and policymakers.

Fast-Charging Li4Ti5O12 Anode Driven by Light

Lithium-ion batteries with fast charging capabilities are crucial for widespread adoption of electric vehicles, as they will increase acceptance of the technology and reduce range anxiety for drivers. To achieve this, advanced fast charging technologies and alternative methods to enhance the slow electrochemical processes are desperately required. This study applied light-emitting diode (LED) photo-assisted fast charging to Li4Ti5O12 (LTO), a large bandgap cubic spinel material, to enhance charging speed through electronic-structure coupling. UV LED-generated light irradiation on to the electrode interface boosted the ion diffusion and lithium cation addition by a factor of 1.3 during electrochemical lithiation, resulting in a 30% decrease in charging time under ambient conditions. Red LED light was not effective in accelerating the reaction as it does not provide sufficient energy. The first-principles calculations support the concept that UV illumination generates charges by overcoming the material’s bandgap and effectively reducing it through the introduction of additional titanium defect states.

Targeting the low-temperature performance degradation of lithium-ion batteries: A non-destructive bidirectional pulse current heating framework

The poor low-temperature performance of lithium-ion batteries (LIBs) significantly impedes the widespread adoption of electric vehicles (EVs) and energy storage systems (ESSs) in cold regions. In this paper, a non-destructive bidirectional pulse current (BPC) heating framework considering different BPC parameters is proposed. To determine the lithium plating boundary of graphite anode, a three-electrode battery is first fabricated. Then, an electro-thermal coupled model is established and the model parameters consider not only the effects of temperature and heating frequency but also the effect of current amplitude. Subsequently, a novel lithium plating criterion is derived based on the thermodynamic theory and the graphite anode model. Finally, leveraging the electro-thermal coupled model and considering the constraints of lithium plating and terminal voltage, the effects of different BPC heating parameters on battery heat generation are discussed and a novel BPC heating strategy is designed. The results show that the heat generation power is highest when the ratio of discharge time to charge time is 0.55. Additionally, the BPC heating strategy proposed in this paper is 45 s faster than the traditional BPC heating strategy when the battery is heated from -15 °C to 10 °C at 100 Hz. The heating rate of the new BPC strategy is 3.51 °C/min and there is no observed capacity degradation after 100 heating cycles. The BPC heating framework proposed in this paper effectively improves the low-temperature performance of the battery and contributes positively to the promotion of EVs and ESSs in cold regions.

Electric and gasoline vehicle total cost of ownership across US cities

AbstractVehicle electrification can significantly decarbonize the transportation sector. Widespread adoption of electric vehicles (EVs) depends on their cost relative to conventional alternatives. Here we compare the total cost of ownership (TCO) of gasoline, hybrid, and electric vehicles. First, we review previous TCO studies, showing that the components (e.g., purchase price, financing, taxes, fees, insurance, refueling, maintenance, repair, and home charging equipment for EVs), parameters (e.g., vehicle miles traveled, discount rate, and lifetime), and methods differ greatly. Then, we develop a comprehensive TCO model comparing across five vehicle classes, three powertrains, and three EV ranges. Using 14 cities in the United States and multiple charging scenarios, we investigate TCO variability based on location and use pattern. We include adjustments for local gasoline prices, electricity rate plans, home charging access, and the impact of local temperatures and drive cycles on fuel economy, among other factors. We show that for a 300‐mile range midsize electric SUV, TCO varies by $52,000, or nearly 40%, across locations. Home charging access reduces the lifetime cost by approximately $10,000 on average, and up to $26,000. EVs are more competitive in cities with high gasoline prices, low electricity prices, moderate climates, and direct purchase incentives, and for users with home charging access, time‐of‐use electricity pricing, and high annual mileage. In general, we find that small and low‐range EVs are less expensive than gasoline vehicles. Larger, long‐range EVs are currently more expensive than their gasoline counterparts. And midsize EVs can reach cost parity in some cities if incentives are applied.