Mass Adoption Of Electric Vehicles Research Articles

A fast-charging/discharging and long-term stable artificial electrode enabled by space charge storage mechanism

Lithium‐ion batteries with fast-charging/discharging properties are urgently needed for the mass adoption of electric vehicles. Here, we show that fast charging/discharging, long-term stable and high energy charge-storage properties can be realized in an artificial electrode made from a mixed electronic/ionic conductor material (Fe/LixM, where M = O, F, S, N) enabled by a space charge principle. Particularly, the Fe/Li2O electrode is able to be charged/discharged to 126 mAh g−1 in 6 s at a high current density of up to 50 A g−1, and it also shows stable cycling performance for 30,000 cycles at a current density of 10 A g−1, with a mass-loading of ~2.5 mg cm−2 of the electrode materials. This study demonstrates the critical role of the space charge storage mechanism in advancing electrochemical energy storage and provides an unconventional perspective for designing high-performance anode materials for lithium-ion batteries.

Complete Metal Recycling from Lithium-Ion Batteries Enabled by Hydrogen Evolution Catalyst Reconstruction.

Mass adoption of electric vehicles and the depletion of finite metal resources make it imperative to recycle lithium-ion batteries (LIBs). However, current recycling routes of pyrometallurgy and hydrometallurgy are mainly developed for LiCoO2 and suffer from great energy inputs and extensive processing; thus, alternative versatile and green approaches are in urgent demand. Here, we report an ingenious and versatile strategy for recycling LIBs via catalyst reconstruction, using hydrogen evolution reaction as a proof of concept. Layered, spinel, and polyanion oxide cathode materials, as catalysts, are structurally transformed into hydroxides assisted by protons or hydroxide ions, facilitating complete metal extraction (e.g., Li, Co, Ni, Mn, Fe) with high leaching efficiencies approaching 100%. This recycling method is generally applicable to almost all commercial cathode systems and extended to actual spent pouch cells. Such a green hydrogen coupling approach provides a versatile and sustainable alternative to conventional approaches and has a broad impact beyond battery recycling.

Common DC-Link Capacitor Lifetime Extension in Modular DC/DC Converters for Electric Vehicle Fast Chargers via Variable-Angle Interleaved Operation

The global shift towards the electrified transportation as a means of achieving decarbonized economy has led to an increase in the demand of electric vehicles. In order to enhance the transition, there is a need to develop fast and ultra-fast charging substations. Hence, power converters play an inherently vital role in the mass adoption of electric vehicles. However, the reliability and active maintenance scheduling of these converters are becoming prominent issues for manufacturers and operators. As a result, optimization of the operation of an interleaved dc/dc converter present in the charging poles plays a significant role. This paper proposes an alternative modulation technique for interleaved dc/dc power converters of fast chargers aiming to improve the harmonic performance of the common dc-link capacitor current. This technique leads to an extension of lifetime of the capacitor, which is one of the most critical component of the power system. Experimental results are shown in order to validate the effectiveness of the proposed method.

Providing implications for electric vehicle applications through experimental exploration on temperature distribution and heat flow for a high Ni content battery module thermal management system under multi-operating scenarios

Recently, there has been an increase in accidents due to thermal runaway issues with the mass adoption of electric vehicles in China. Avoiding thermal runaway incidents has become an essential need for electric vehicle development. Controlling abnormal temperatures is a key scientific study in battery thermal safety research. Therefore, this study provides a comprehensive analysis of module temperature distribution in the high Ni content commercial lithium-ion battery module for electric vehicles by three experimental groups. The results of the tests show that the wrap-full insulation keeps heat and mitigates the temperature non-uniformity better, but the bottom-only insulation reduces temperature faster. Active cooling can reduce the non-working module temperature from 45 °C to 27 °C in 2160 s, but natural convection keeps the temperature at about 45 °C. Under complex operating, the maximum temperature difference of the module reaches 9–10 °C. After adding active cooling, the maximum temperature difference on the module is reduced by 1 °C, and the cooling speed is accelerated by 35 %. In short, a thermal gap exists between the total positive and negative and other, which is one of the primary causes of the large temperature difference within the module. The heat transfer direction inside the module is from the middle to the sides, but it is the opposite under natural cooling. We hope to provide a useful analysis of module temperature distribution that guides the cooling layout design/application.

Electric vehicle charging infrastructure investment strategy analysis: State-owned versus private parking lots

This paper analytically studies the optimal charging infrastructure investment decisions in parking lots with state-owned firms and private firms, which aims to alleviate range anxiety and facilitate the mass adoption of electric vehicles. The investment decisions are made based on the rational choice in the short term and are assumed to be static. However, the investment in charging infrastructure is a long-term strategy and the decisions might evolve over time. As a result, an evolutionary game theoretic approach is proposed to analytically explore the instability of the investment decisions and derive the optimal investment strategies. We first construct a basic model with a payoff matrix of public and private parking lots and formulate the dynamic replicator equations to find the equilibrium points. We further explore the evolutionary stable strategy (ESS) with its conditions, and analyze the impact of key factors on the strategy evolution. In the basic model, we find that the investment ratio of the state-owned firms and private firms is crucial to the ESS and its original parking revenue has no impact on the investment decisions. To discover the impact of the uncertainty of investments, we next reformulate the model and extend the original payoff matrix by incorporating the perceived value function based on prospect theory. The ESS and its relevant conditions are also derived. We observe that two models have the same ESS in most cases when there is a marked difference in their profitability. When the difference in their profitability is small, the perceived return on investment plays a pivotal role in their investment decisions. Finally, managerial implications are discussed.

Extreme fast charging of commercial Li-ion batteries via combined thermal switching and self-heating approaches

The mass adoption of electric vehicles is hindered by the inadequate extreme fast charging (XFC) performance (i.e., less than 15 min charging time to reach 80% state of charge) of commercial high-specific-energy (i.e., >200 Wh/kg) lithium-ion batteries (LIBs). Here, to enable the XFC of commercial LIBs, we propose the regulation of the battery’s self-generated heat via active thermal switching. We demonstrate that retaining the heat during XFC with the switch OFF boosts the cell’s kinetics while dissipating the heat after XFC with the switch ON reduces detrimental reactions in the battery. Without modifying cell materials or structures, the proposed XFC approach enables reliable battery operation by applying <15 min of charge and 1 h of discharge. These results are almost identical regarding operativity for the same battery type tested applying a 1 h of charge and 1 h of discharge, thus, meeting the XFC targets set by the United States Department of Energy. Finally, we also demonstrate the feasibility of integrating the XFC approach in a commercial battery thermal management system.

Electric Vehicles: An Assessment of Consumer Perceptions Using Importance-Performance Analysis

The electrification of vehicles represents a promising measure for decarbonizing the transport sector. Several countries worldwide have created incentives to promote the mass adoption of electric vehicles (EVs) to mitigate the environmental and energy effects caused by the increased road transport demand; however, many consumers remain skeptical about EVs.&#x0D; Consumer perceptions and concerns are critical for evaluating a product’s market position, identifying opportunities for improvement, and guiding strategic planning. The importance-performance analysis (IPA) represents a simple and effective technique for assessing consumer acceptance of product attributes that have been used in diverse fields.&#x0D; This study aimed at identifying the key EV attributes that require more attention from policymakers and manufacturers to improve consumer satisfaction. It analyzed survey data of 278 Norwegian EV owners and identified that instrumental aspects (i.e., driving range, battery recharging time, safety function, energy efficiency), winter driving quality, and environmental effects of EVs, are the most decisive factors when considering what car to buy. The results showed that EVs perform best with respect to environmental aspects, winter driving quality, and interior and exterior design. Finally, based on the IPA results, policymakers and car manufacturers should focus on the instrumental aspects, cost aspects, and winter driving quality of EVs to make EVs more attractive to consumers.&#x0D; Our findings provide policymakers and EV manufacturers with a deeper understanding of the needs and perceptions of EV owners with respect to EV attributes, thus helping them develop and implement better strategies for improving the attractiveness of EVs.

Optimal dispatching of electric vehicles for providing charging on-demand service leveraging charging-on-the-move technology

Range anxiety and charging infrastructure scarcity have been the main challenges for the mass adoption of electric vehicles (EVs). The emerging mobile electric-vehicle-to-electric-vehicle (mE2) charging technology offers a promising solution, which combines battery-to-battery and connected and autonomous vehicle technologies to enable an EV with an extra battery to charge another EV on the move. This paper focuses on the efficient pairing and routing of electricity providers (EPs) to demand (EDs) by extending the existing Charging-as-a-Service (CaaS) strategy to the mE2 charging service (referred to as CaaS+). We investigate the EP fleet management problem, which is mathematically modeled as a vehicle routing problem (i.e., mE2-VRP), aiming to optimally dispatch the minimum number of EPs to approach and serve the EDs. To adapt mE2 charging strategy to the online service involving large-scale EDs in practice, we develop a Clustering-aid Decomposition and Merging (c-DM) algorithm. It clusters the EDs according to their coalition potential so that we can decompose a large-scale mE2-VRP into smaller subproblems which can be efficiently solved by parallel computing. Our numerical experiments built upon citywide (Chicago) and statewide (Florida) case studies confirm the efficiency of the proposed c-DM algorithm. It enables us to investigate the performance of CaaS+ under a realistic large-scale setup. The results show that CaaS+ will be applied in different proportions of EV flows to save EDs’ travel time and mitigate traffic congestion to different extents in different network congestion and charging station coverage scenarios. The sensitivity analyses of EDs’ energy inventory and range anxiety also provide some hints and suggestions for improving the service efficiency of CaaS+.

Breaking it down: A techno-economic assessment of the impact of battery pack design on disassembly costs

The electrification of the transport sector is a critical part of the net-zero transition. The mass adoption of electric vehicles (EVs) powered by lithium-ion batteries in the coming decade will inevitably lead to a large amount of battery waste, which needs handling in a safe and environmentally friendly manner. Battery recycling is a sustainable treatment option at the battery end-of-life that supports a circular economy. However, heterogeneity in pack designs across battery manufacturers are hampering the establishment of an efficient disassembly process, hence making recycling less viable. A comprehensive techno-economic assessment of the disassembly process was conducted, which identified cost hotspots in battery pack designs and to guide design optimisation strategies that help save time and cost for end-of-life treatment. The analyses include six commercially available EV battery packs: Renault Zoe, Nissan Leaf, Tesla Model 3, Peugeot 208, BAIC and BYD Han. The BAIC and BYD battery packs exhibit lower disassembly costs (US$50.45 and US$47.41 per pack, respectively), compared to the Peugeot 208 and Nissan Leaf (US$186.35 and US$194.11 per pack, respectively). This variation in disassembly cost is due mostly to the substantial differences in number of modules and fasteners. The economic assessment suggests that full automation is required to make disassembly viable by 2040, as it could boost disassembly capacity by up to 600 %, while substantially achieving cost savings of up to US$190 M per year.

Fostering the Mass Adoption of Electric Vehicles: A Network-Based Approach

Mobility will surely be at the core of the smart cities of the future. As such, it must be planned based on novel mobility models, smart enough to answer the multifaceted needs of users, while being sustainable and energy efficient. In this evolution, electric vehicles (EVs) will be crucial, as confirmed by the fact that many governments are already actively sustaining their spread in place of common internal combustion engine (ICE) ones. Nonetheless, for their adoption to be actually widespread, one must be able to govern the mass adoption mechanisms, by designing policies that are cost-effective and successful in making the mobility transition a reality in due time. In this work, we propose a novel framework that can represent a valuable control-oriented tool to serve this ambitious goal. Our framework lays its foundation on a quantitative description of the inclination of traditional car owners toward EVs, which is retrieved by relying on data-driven insights on their mobility habits only. This information is further exploited to construct a proximity-based network, that is combined with the individual characterization into a cascade model describing the adoption dynamics. To show the potential of the introduced framework, we exploit it to assess the unforced spread of EVs starting from a set of known EV owners, and to test and quantitatively evaluate the cost and benefits of policies enacted to foster adoption.

Enhancing the Charging Performance of Lithium-Ion Batteries by Reducing SEI and Charge Transfer Resistances.

To enable the mass adoption of electric vehicles, the charging performance of Li-ion batteries needs to be significantly enhanced. The development of electrolytes with enhanced transport properties and faster interfacial reaction is one critical approach to realize fast charging within 10 min. Most current electrolyte studies are focusing on ester-based electrolytes. In this work, an ether-based electrolyte is reported, which shows remarkably better charging performance than commercial carbonate electrolytes and other reported ester-based electrolytes in both half and full cells. Electrochemical and spectroscopic characterization shows that the superior charging performance of the reported electrolyte is due to significantly reduced SEI resistance and charge transfer resistance. Cycling tests show remarkable stability in Li||graphite (gr) half cells, suggesting the potential of the electrolytes to enhance battery charging performance. LiFePO4 (LFP)||gr full cells were further tested, and it is found that the resistance of cells builds up during cycling due to gelation of the electrolyte, which limits the cycling performance of full cells. Potential strategies to address this limitation are discussed.

Improving High-Nickel Cathode Active Material Performance in Lithium-Ion Batteries with Functionalized Binder Chemistry

As the lithium-ion battery (LIB) market expands, driven mostly by the mass adoption of electric vehicles, LIB development is continually being pushed in the direction of higher energy density and lower cost. Both of these trends are leading to widespread development of LIB formulations using high-nickel cathode active materials, such as NMC811. In these materials, the high nickel content increases the amount of electrochemically accessible lithium in the cathode, increasing the cell energy density, while decreasing the amount of cobalt used, which decreases the cost of the cathode material. However, these materials also have drawbacks. First, NMC811 suffers from lower cycle life than higher-Co NMC materials such as NMC111 or NMC622. Second, NMC811 has poorer safety characteristics than lower energy density materials. Finally, NMC811 cathodes are known to experience gassing issues during cycling, which creates challenges in commercialization, especially for pouch cell battery designs.Many approaches have been explored in the industry to address these shortcomings, including active material modification, electrolyte design, etc. In this presentation, binder functionalization will be presented as an alternative pathway to improve high-Ni cathode performance. LIB cathode binder is commonly high molecular weight PVDF, which provides good mechanical properties at low weight fractions as well as high electrochemical stability, but it is predominantly inert. Here, approaches of introducing novel binders tailored for high-Ni cathode systems will be discussed. Effectiveness of modifications, specifically their impact on LIB cycle life and safety, will be discussed.

Development and Performance Examination of Switch Mode Power Supply based Battery Charger for Electric Vehicle.

Objectives: The study’s primary goal is to investigate a Switch Mode Power Supply (SMPS)-based battery charger for electric vehicles (EV) and compare the use of various charging techniques. Methods: This study provides ideas for the requirements of an SMPS-based battery charger; design and development of the charger; and operation of the charger with different charging techniques. Further, the development of the proposed charger, its testing and performance examination are carried out. This study also gives details about circuit components; circuit selection criteria of an SMPS-based battery charger; charging methods; and technical specifications of the charger. Verification and testing of the proposed charger is also done with the help of a 24 V battery. Findings: It is found that the proposed battery charger can be more advantageous than conventional battery chargers in a variety of ways, including improved efficiency (nearly 88%), light weight, better protection (reverse battery connection, short circuit, overload), and reliable operation (no need to monitor, automatic cut off, and so on). Novelty: Work was done for the development of an SMPS-based battery charger to eliminate existing issues as mentioned in the findings with traditional charger systems. The proposed charger helps to eliminate the sulfation effect on lead acid batteries to improve battery life (50–100 cycles). It helps to not only promote the ”Made in India” scheme but also mass adoption of electric vehicles. Keywords: SMPS based charging system; microcontroller; IGBT; sulfation; lead acid battery

Resource efficiency for UK cars from 1960 to 2015: From stocks and flows to service provision

The transport sector is supported by the continuous provision of energy and material flows and material stocks. However, most resource accounting methods do not assess the role of material accumulation in the delivery of mobility, as a service. Using a UK-based case study, we evaluate the service contribution of both resource stocks and flows in the provision of the passenger-kilometres (pkm) travelled nationally by UK-registered cars between 1960 and 2015. For flows we considered diesel and petrol. For stocks we considered steel, aluminium, and plastics, among others. We used six indicators to analyse the interactions between stocks, flows and service. Our results show that the fuel efficiency of cars increased from 0.46 to 0.69 pkm/MJ over the period. However, there was a decrease in stock efficiency from 24.9 to 17.1 pkm/kg-year. Resource productivity increased from 0.42 to 0.61 pkm/MJ. Stock expansion rate decreased from 0.16 to 0.03 year−1 while the specific CO2 embodied impact reduced from 2.4 to 2.0 tCO2/tonne of resource flow. Consumer preferences for heavier larger vehicles and sociodemographic changes linked to workplace expectations, commuting and urbanisation patterns are key factors influencing UK car stock efficiency. While fuel efficiency has improved and will continue to do so via the mass adoption of electric vehicles, due to policy and legislative developments, there are still sustainability concerns linked to their heavier weight and the environmental impact of their increased material complexity.

The role of artificial intelligence in the mass adoption of electric vehicles

<h2>Summary</h2> The electrification of mass transportation is hailed as a solution for reducing global greenhouse-gas emissions and dependence on unsustainable energy sources. The annual sales of electric vehicles (EVs) has continued to rise since 2011, with a global sale of EVs of 2.1 million in 2019. This increase in sales is mainly due to continued improvement in the cost and performance of commercial EVs, increased EV options available to consumers, and environmental awareness. However, despite the positive outlook, EVs still face major challenges that hinder their rapid and widespread adoption: limited driving range, long charging times, and a lack of sufficient charging infrastructure. This review outlines the recent advances in EVs and related infrastructure, mainly from artificial intelligence (AI), which makes EVs a more attractive consumer option. The application of AI in improving EVs, facilitating EV charging stations, and EV integration with the smart grid is critically analyzed and reviewed. Finally, future trends and prospects in the area are discussed.

Frvcpy: An Open-Source Solver for the Fixed Route Vehicle Charging Problem

Electric vehicles offer a pathway to more sustainable transportation, but their adoption entails new challenges not faced by their petroleum-based counterparts. A difficult task in vehicle routing problems addressing these challenges is determining how to make good charging decisions for an electric vehicle traveling a given route. This is known as the fixed route vehicle charging problem. An exact and efficient algorithm for this task exists, but its implementation is sufficiently complex to deter researchers from adopting it. In this work we introduce frvcpy, an open-source Python package implementing this algorithm. Our aim with the package is to make it easier for researchers to solve electric vehicle routing problems, facilitating the development of optimization tools that may ultimately enable the mass adoption of electric vehicles. Summary of Contribution: This work describes a novel software tool for the vehicle routing community. The tool, frvcpy, addresses one of the primary challenges faced by the vehicle routing community when considering problems involving the adoption of electric vehicles (EVs): how to make optimal charging decisions. The state-of-the-art algorithm for solving these problems is sufficiently complex to deter researchers from using it, leading them to adopt less robust methods. frvcpy offers an easy-to-use, lightweight implementation of this algorithm, providing optimal solutions in low (∼5 ms) runtime. It is designed to be easily embedded in larger solution schemes for general EV routing problems, requiring minimal input, offering compatibility with the community standard file types, and offering access both through the command line and a Python API. The tool has thus far proven adaptable, having been used by researchers studying EV routing problems with novel constraints. Our aim with frvcpy is to make it easier for researchers to solve EV routing problems, facilitating the development of optimization tools that may contribute toward the mass adoption of electric vehicles.

Graphite Lithiation Under Fast Charging Conditions: Atomistic Modeling Insights

Charging lithium ion batteries in a fast and safe manner is critical for promoting mass adoption of electric vehicles. Li intercalation in graphite electrodes is known to be one of the bottlenecks during the fast charging process. The mechanism of Li diffusion in highly polarized graphite anode at high current rates remains, however not well understood. Herein, Density Functional Theory (DFT) calculations are used to gain insights into the Li diffusion process in graphite when far from equilibrium under fast charging conditions. The effect of uncompensated charges on Li mobility is determined in the highly polarized regions of the anode close to the interfaces. The extra charge was found to increase the interlayer spacing in the diffusion layer and adjacent channels, increasing the diffusivity, altering the staging mechanism, and promoting the formation of Li clusters. A concerted diffusion mechanism at the edge of high-concentration Li domains is proposed to enhance the diffusion of Li.

On-Board Single-Phase Integrated Electric Vehicle Charger With V2G Functionality

Mass adoption of electric vehicles (EVs) is contingent on the availability of charging infrastructure. One solution to this issue is the introduction of on-board fast chargers, but such solutions typically require the installation of additional magnetic components that increase EV mass. An alternative approach is the dynamic redeployment of drivetrain components for charging when the vehicle is stationary. This article proposes an on-board single-phase charger that reuses the traction inverter and motor. The system consists of a dual-inverter drivetrain, which affords higher voltage charging compared to conventional systems. In addition, the system is able to operate bidirectionally and operate at any power factor for grid support services with real and reactive power exchange without subjecting the motor to low frequency harmonic currents. Experimental tests demonstrated operation at 19.2 kW using a 110-kW EV motor and a full-scale, state-of-the-art, dual-inverter drive prototype. Measured peak efficiencies of over 97% demonstrate the viability of integrated charging in a real-world scenario.

The EV revolution: The road ahead for critical raw materials demand

Mass adoption of electric vehicles (EVs) is anticipated in the years ahead, driven primarily by policy incentives, rising incomes, and technological advancements. However, mass adoption is predicated on the availability and affordability of the raw materials required to facilitate this transformation. The implications of material shortages are currently not well understood and previous research tends to be limited by weak representation of technological change, a lack of regional disaggregation, often inflexible and opaque assumptions and drivers, and a failure to place insights in the broader context of the raw materials industries. This paper proposes a CoMIT (Cost, Macro, Infrastructure, Technology) model that can be used to analyse the impact of mass EV adoption on critical raw materials demand and forecasts that, by 2030, demand for vehicles will increase by 27.4%, of which 13.3% will be EVs. The model also predicts large increases in demand for certain base metals, including a 37 and 18-fold increase in demand for cobalt and lithium (relative to 2015 levels), respectively. Without major changes in certain technologies, the cobalt and lithium supply chains could seriously constrain the widespread deployment of EVs. Significant demand increases are also predicted for copper, chrome and aluminium. The results also highlight the importance of China in driving demand for EVs and the critical materials needed to produce them.

Effects of Charging Infrastructure Characteristics on Electric Vehicle Preferences of New and Used Car Buyers in the United States

The used car market is a critical element for the mass adoption of electric vehicles (EVs). However, most previous studies on EV adoption have focused only on new car markets. This article examines and compares the effects of charging infrastructure characteristics on the preferences for EVs among both new and used car buyers. This study is based on an online stated preference choice experiment among private car owners in the U.S., and the results of comparable binomial logistic models show that new and used car buyers generally share similar patterns in preferences for EVs, with exceptions for sensitivity toward fast charging time, and home charging solutions. Respondents’ stated willingness to adopt an EV increases considerably with improvements in driving range, and the effects on new and used car buyers are similar. The study also finds that better availability of charging infrastructure largely increases preference for EVs. The results further reveal that slow and fast charging have complementary effects on encouraging EV adoption as the combination of public slow and fast charging can compensate for the unavailability of home charging.