Diffusion Of Electric Vehicles Research Articles

Effects of mixed policies on the cooperative and noncooperative strategies of auto manufacturers and charging infrastructure operators considering consumer preferences

ABSTRACT The dual-credit policy for auto manufacturers and the subsidy policy for charging infrastructure operators have become important policies to guide and promote the development of the automotive industry. However, few studies consider the impact of mixed policies on the market strategies of auto manufacturers and charging infrastructure operators considering consumer green preferences. To fill the gap, this article establishes optimization models to analyze and compare the effects of mixed policies on the decision-making of auto manufacturers and charging infrastructure operators under the cooperative and noncooperative modes considering consumer preference. The results reveal four main insights: (1) Two types of policies all have direct positive effects on the market diffusion of electric vehicles. Under the noncooperative mode, the dual-credit policy has no spillover effect. Under cooperative mode, two types of policies all have spillover effects. The dual-credit policy and charging infrastructure subsidy policy have positive superposition effects on the optimal number of charging piles, and the optimal demands for electric vehicles. (2) When the credit price is less than a certain threshold, there is a substitutive effect between the charging infrastructure subsidy policy and the dual-credit policy on promoting the market diffusion of electric vehicles. (3) There is a substitutive effect between high-level consumers’ green preference and policies on promoting the market diffusion of electric vehicles. (4) Under the cooperative mode, the direct and spillover effects of policies are more than that are under the noncooperative mode. These insights demonstrate the effectiveness and limitations of policies and the importance of providing complementary policies for consumers. The government should encourage market cooperation between auto manufacturers and charging infrastructure operators, maintain a stable price level for credits, and introduce incentive policies for green consumption.

Production and decarbonisation of conventional gasoline vehicle automakers under subsidy and regulation policies

ABSTRACT Decarbonising the transportation sector through electrification is critical to reducing greenhouse gas emissions. To explore the decarbonisation of conventional gasoline vehicle (GV) automakers in GV and/or electric vehicle (EV) production, we develop analytical models under pure subsidy, pure regulation, and hybrid subsidy-regulation policies. We first examine the monopoly GV automaker’s EV market entry intention in each policy and find that it always increases with consumer range sensitivity and subsidy/regulation parameters, but decreases with product substitutability between the two vehicles. Then, we analyse the implication of policy changes on equilibrium outcomes. Our results show that although introducing regulations and removing subsidies have opposite effects on optimal production and driving range decisions, both might stimulate or restrict the GV automaker to decarbonise, depending on the unit carbon emissions of GVs and EVs. Finally, we extend the monopoly model to the duopoly case, showing that while entering the EV market hurts the EV automaker, it allows the GV automaker’s carbon emissions to always decrease with GV credit coefficients. Together with sensitivity analyses on key parameters, our findings provide insights not only for GV automakers to respond to policy changes but also for governments to design incentives for EV diffusion.

An MV-Connected Ultra-Fast Charging Station Based on MMC and Dual Active Bridge with Multiple dc Buses

The diffusion of electric vehicles will be strongly related to the capacity to charge them in short times. To do so, the necessity of widespread fast charging stations arises. However, their intermittent demand represents a challenging load for grid operators. In order to relieve their impact on the electrical grid operation, integrating storage systems in the charging stations represents a potential solution, although it complicates the overall system management. Moreover, standard converter architectures for the MV grid interface require the installation of bulky transformers and filters. In order to cope with the mentioned problems, this paper proposes an ultra-fast charging station topology based on a modular multilevel converter (MMC) structure and dual-active bridge (DAB) converters. Thanks to the multilevel converter properties, the proposed charging station can be directly interfaced with the MV grid without requiring transformers or filters. Additionally, exploiting the degree of freedom in the converter control system, such as circulating components, offers uneven power distribution among the converter submodules that can be managed. Along with the MMC control strategy, the article addresses a straightforward methodology to select the main parameters of the DAB converter as a function of the involved grid power and circulating power contributions, with the primary goal of obtaining a trade-off between internal balancing performances and a broad soft-switching region without incurring in converter oversizing. The effectiveness of the proposed charging station is finally discussed through numerical simulations, where its behavior during a power demand cycle is analyzed.

Trends in Automotive Battery Cell Design: A Statistical Analysis of Empirical Data

Lithium-ion (Li-ion) batteries have become the preferred power source for electric vehicles (EVs) due to their high energy density, low self-discharge rate, and long cycle life. Over the past decade, technological enhancements accompanied by massive cost reductions have enabled the growing market diffusion of EVs. This diffusion has resulted in customized and cost-effective Li-ion battery cell designs tailored to automotive requirements. This study describes design trends in Li-ion batteries from the pack to the electrode level based on empirical data, including pack energy, cell capacity, outer cell dimensions and formats, energy density, specific energy, and electrode properties, such as active material selection, porosities, and component thicknesses. Market share-weighted findings imply several trends, such as (1) increasing cell dimensions, with the longest cells reaching 500 mm (pouch) and almost 1000 mm (prismatic) in 2021, (2) increasing differentiation between either high-energy or low-cost cathode and anode materials, and (3) increasing cell energy, equivalent to gaining about 100% (energy density) and 70% (specific energy) compared to the 2010 and 2021 averages. Despite these improvements, this study finds that the widespread market diffusion of the latest cell technologies proceeds slower than industry announcements suggest and that several well-known, literature-proofed potentials are not yet fully exploited.

Estimating charging demand by modelling EV drivers' parking patterns and habits

The diffusion of battery electric vehicles (BEVs) requires a proper charging infrastructure to supply users the chance to charge their vehicles according to energy, time, and space needs. Thus, city planners and stakeholders need decision support tools to estimate the impacts of potential charging activities and compare alternative scenarios. The paper proposes a modelling approach to represent parking activities in urban areas and obtain key indicators of the electric energy required. The agent-based model reproduces the dynamics of user parking and assesses the impacts on the electricity grid during the day. Since the focus is on parking activities, no detailed data on vehicle trips are required to apply the standard demand modelling approach, which would require Origin-Destination matrices to simulate traffic flows on the road network. Preliminary results concerning the city of Turin are presented for simulated scenarios to identify zones where charging demand can be critical and peak events in electric power over the day. The model is designed to be scalable for all European cities because, as the case study shows, it uses available data. The results obtained can be used for the design of charging infrastructure (power and type) by zones.

Exploring the role of electrification and modal shift in decarbonizing the road passenger transport in British Columbia

The possibility of the modal shift to public transport and active mobility while considering transport electrification and fuel efficiency improvement has yet to be adequately investigated. This paper explores transition pathways toward an environmentally sustainable road passenger transportation system in the province of British Columbia (BC), Canada. MESSAGE, as a bottom-up energy systems optimization model, is used to find the cost-optimal fuel and technology mix in the transport and power sector. Multiple scenarios mainly assess the influence of modal shift and electric vehicle (EV) diffusion on greenhouse gas emissions by 2050. Besides, the effects of scenarios on the power sector configuration are examined. The results show that BC would not achieve the 80% emissions reduction target in the Climate Change Accountability Act unless by a radical expansion of transport electrification. The target could be met by a minimum diffusion of 70% EVs in the total car stock as well as 35% public transport contribution in total passenger kilometers. The findings also indicate that fully electrified light-duty vehicles coupled with active transport would lead to almost a zero-emission level. Nevertheless, 100% electrification would impose an extra 5.6 TWh burden on the power supply system relative to the business-as-usual scenario.

Wrought and cast aluminum flows in China in the context of electric vehicle diffusion and automotive lightweighting

Electrification and vehicle weight reduction (lightweighting) trends are driving demand for wrought aluminum alloys. Given that aluminum scrap is currently downgraded as it is recycled into cast aluminum alloys, an imbalance in aluminum cycles is predicted to occur. We identified secondary aluminum flows by distinguishing alloy type in China with material flow analysis. Considering the adoption of advanced recovery techniques and the trends towards greater use of electric vehicles and vehicle lightweighting, we also estimated changes in the automotive demand for wrought and cast alloys along with aluminum scrap generation, as well as the reduced amount of primary aluminum used in automobiles. The results revealed the potential to recycle about 87−183 kt of wrought alloys in 2019 and about 1,054−7,152 kt in 2050 within a well-managed vehicle recycling system, thereby reducing the amount of primary aluminum ingot required for automobile production by 10−37% between 2019 to 2050.

Portfolio Analysis of Clean Energy Vehicles in Japan Considering Copper Recycling

Several countries are moving toward carbon neutrality to mitigate climate change. The introduction of clean energy vehicles (CEVs) is a measure to offset the adverse effects of global warming. However, each CEV has its strengths and weaknesses. An optimal CEV portfolio must be formulated to create effective policies that promote innovative technologies and introduce them into the market. CEVs also consume more copper than gasoline vehicles. Copper is associated with supply risks, which most previous conventional studies have failed to address. Therefore, this study proposes a novel CEV optimization model for sustainable consumption of copper resources through recycling along with reduction of CO2 emissions. This study aims to analyze the optimal portfolio for domestic passenger vehicles and the assumed effects of copper recycling and usage reduction. For this analysis, this study set up scenarios for the recycling rate of copper contained in end-of-life vehicles and the reduction rate of copper used in newly sold vehicles. Our simulation results showed that increased recycling rates and reduced use of copper are necessary for the diffusion of battery electric vehicles. Furthermore, the simulation results indicated that if these improvements are not implemented, the deployment of fuel cell vehicles needs to be accelerated.

Impact of electric cars deployment on the Italian energy system

Electric vehicles are supposed to play a leading role in the transition towards a low carbon society since they allow to substitute oil products with electricity as the main energy source for transportation. On the other hand, the diffusion of electric vehicles determines an increase in power demand with a consequent variation in the power supply mix. In accordance with this, it is mandatory to analyse how the supply mix changes, since the introduction of electric vehicles is significant from the sustainability point of view only if there is a reduction in emissions. To assess this condition for the Italian energy system, the present paper proposes a model developed in EnergyPLAN. Three different scenarios are tested in terms of the penetration of electric vehicles to understand which is the optimal trajectory for their diffusion. The analysis demonstrates that the Italian energy system can accommodate 7 million electric cars, namely about 25% of the total in 2040. A higher amount would determine an increase in carbon emissions.

Mind the goal: Trade-offs between flexibility goals for controlled electric vehicle charging strategies

Electrification is one of the main decarbonization strategies for transportation. While uncontrolled electric vehicle (EV) charging can challenge the electricity system, controlled EV charging can offer flexibility. Using an agent-based model, we simulate combinations of two elements of EV charging, plug-in behaviors and controlled-charging processes, and measure flexibility goals with four metrics: total load shift, increase in midday load, peak reduction, and flatness of the load curve. We reveal trade-offs between these flexibility goals, which indicate that the most beneficial combinations are specific to spatial areas and their flexibility goals. Furthermore, we find that controlled-charging processes show higher impact on the flexibility metrics than plug-in behaviors, particularly with high EV and charging-station diffusion, but less so in rural areas. Incentivizing beneficial combinations can increase the flexibility potential of EV charging and potentially avoid grid reinforcements.

Adaptive Integrated Planning of Electricity Networks and Fast Charging Stations Under Electric Vehicle Diffusion

The proliferation of electric vehicles (EVs) is an inevitable trend to realize transportation electrification. However, the increasing charging demand of EVs also brings challenges to future smart grids. To cope with the EV diffusion, this paper presents an adaptive fast charging station (FCS) strategy that considers the integrated network planning and quality of service (QoS) guarantee. First, based on the EV diffusion model and the proposed EV-integrated traffic assignment model, the charging demands at different regions and stages are forecasted. Based on the predicted spatial and temporal EV charging demand, a multistage stochastic distribution expansion planning model is presented, where the distribution network assets and FCSs are jointly considered. To guarantee the quality of the fast-charging services under EV diffusion, a QoS assessment is conducted based on the average waiting time and the average number of dissatisfied leaves. Finally, the proposed planning model allows several alternatives at both the distribution and transmission levels. The cost of electricity network expansion planning is considered as the adaptive cost arisen from the EV diffusion and the increase of the other electrical loads. We aim to find a planning strategy that can adapt to different penetration levels of EVs. The proposed framework and methodology are verified on the IEEE 24-bus power system encompassing 6 IEEE 33-bus distribution networks. It is found out that the proposed strategy shows superiority in both QoS and total costs.

Development of a methodology to determine NOx-saving-potentials through the buildup of public charging infrastructure for electric vehicles

Nitrogen oxide (NOx) pollution in urban areas is increasingly becoming a problem for human health. Approximately 43% of NOx emissions in Germany are caused by road traffic. Especially in cities, road traffic is the main source of critical NOx concentrations. As a result of high traffic densities and the poor ventilation of streets due to narrow streetscapes, there often is insufficient diffusion of the NOx gas. The current market ramp-up of electric vehicles represents an opportunity to limit the negative effects of road traffic on the pollution especially in urban spaces. In order to further promote the market diffusion of electric vehicles, appropriate charging infrastructure for battery electric vehicles (BEV) and plug-in hybrid electric vehicles (PHEV) in the public road space is required. Mapping the impact of the development of public charging infrastructure on the local NOx-emission of the vehicle fleet is the aim of the developed methodology.

Vehicle-to-Grid and ancillary services: a profitability analysis under uncertainty*

The rapid and massive diffusion of electric vehicles poses new challenges to the electric system, which must be able to supply these new loads, but at the same time opens up new opportunities thanks to the possible provision of ancillary services. Indeed, in the so-called Vehicle-to-Grid (V2G) set-up, the charging power can be modulated throughout the day so that a fleet of vehicles can absorb an excess of power from the grid or provide extra power during a shortage. To this end, many works in the literature focus on the optimization of each vehicle daily charging profiles to offer the requested ancillary services while guaranteeing a charged battery for each vehicle at the end of the day. However, the size of the economic benefits related to the provision of ancillary services varies significantly with the modeling approaches, different assumptions, and considered scenarios. In this paper we propose a profitability analysis with reference to a recently proposed framework for V2G optimal operation in presence of uncertainty. We provide necessary and sufficient conditions for profitability in a simplified case and we show via simulation that they also hold for the general case.

Electric Vehicle Charging Pricing Design for Agent-Based Traffic Microsimulation

Over the past few years, electric vehicles (EVs) have become a popular mode of individual transportation due to their significant benefits over internal combustion engine vehicles, resulting in significant growth in their penetration rate. However, the current flat electricity charging pricing and rapid diffusion of EVs may impose challenges to both transportation systems and power grids. It is well-accepted that the implementation of charging pricing schemes is a promising solution for changing and controlling EV users’ charging behavior. Nevertheless, in most research studies that have examined pricing schemes, the charging logic is defined in a way that agents will charge their vehicles while performing their daily activities. This will make the application of pricing schemes unfeasible, as agents will not have the freedom to unplug their EVs whenever they want, to reduce their billing costs. Accordingly, this paper provides an agent and activity-based framework for charging pricing schemes by decoupling activity and charging start and end times. Following this, three different charging pricing schemes have been introduced, including time of use (TOU), non-linear and zonal pricing and tested on the Montreal scenario.

A charge management algorithm for an unscheduled EV load demand

Electric vehicles (EVs) are an environmental and energy-efficient choice for commuting. The increased diffusion of EVs implies an increased impact on the electric grid during recharging requests. However, intelligent charge management could alleviate the instantaneous load on the network, mitigating the problems of power peaks. This work presents a simple charging scheme that applies in cases where the charge requests have not been scheduled in advance. The algorithms are built on fuzzy logic and manage the charges based only on the instantaneous energy demand and dwell time of EVs present at a charging station. The algorithms are able to reduce substantially the peak in power demand by modulating the charging profiles, taking into account users’ settings on extra parking time.

Predictive Assessment of the Potential Electric Vehicle Market and the Effects of Reducing Greenhouse Gas Emissions in Russia

In recent decades, the global adoption of alternative fuel vehicles, which may contribute to carbon emission reduction due to the use of alternative energy sources has stirred particular interest. Despite a significant body of scientific literature in Russia about electric vehicle adoption, the approaches used in papers lack quantitative estimates of the Russian market's potential. This paper aims to fill this gap as it provides a long-term electric vehicle market forecast in Russia as well as assesses the environmental effects. The following hypotheses are tested: (1) the Bass model is applicable to predict the long-term electric vehicle diffusion process in Russia; (2) the transition to electric cars will have a significant impact on greenhouse gas emission reduction. The Bass model, a widely used tool for predicting the innovation diffusion process, serves as a methodological base for the research. The long-term forecast of the Russian electric car fleet includes several scenarios. The most realistic scenario suggests that the Russian electric vehicle market is estimated to grow, reaching 5.62 million units by 2060. Furthermore, the environmental effects associated with electric vehicle adoption were identified. Two scenarios for changes in the energy generation structure were taken into consideration. The expected carbon emission reduction is estimated to reach 14.08 million tons in CO2-eq. if an accelerated transition to low-carbon energy sources is implemented, the baseline scenario suggests 12.86 million tons in CO2-eq. carbon emission reduction. The estimates of the transport diffusion in Russia as well as of environmental effects associated with this process form the theoretical value of the study. The practical significance of the study suggests developing electric vehicle demand forecasts that might be utilized while implementing measures to achieve goals stated in the Strategy of Social and Economic Development with a Low Level of Greenhouse Gas Emissions until 2050 in the Russian Federation.

Understanding Business Models for the Adoption of Electric Vehicles and Charging Stations: Challenges and Opportunities in Brazil

Although electric vehicle (EV) sales have been increasing over the years, worldwide EV adoption is still low. In Brazil, the key factors influencing this are the EV high acquisition cost and the reduced charging infrastructure. Therefore, traditional business models may not be adequate for Brazil and stagnate EV diffusion. Thus, designing innovative business models can be crucial to accelerate the transition to electric mobility in the region. In this way, this article aims to critically review business models for EV adoption and charging stations worldwide and discuss its application in Brazil. Then, the challenges and opportunities for some business model options are highlighted through the SWOT matrix. One can conclude that EV sharing is a promising business model for Brazil, given the series of advantages such as access to cutting-edge technology at an affordable price, reduction of vehicles on the streets, and given convenience for users (no concern with charging, EV degradation, and parking). However, public policies, subsidies, and coordination between different agents are crucial for the proliferation of this model. On the other hand, for the proposed CS models, the more traditional option is the less risky for investors in Brazil until the number of EVs increase.

The new electric SUV market under battery supply constraints: Might they increase CO2 emissions?

Two trends have shaped the European car market over the past decade: electrification and SUVisation. Recently, they have merged in a new product: the electric sport utility vehicle. This paper contrasts the view that regards this innovation as a technological solution to mitigate road transport emissions with a broader view that takes into account the battery requirement and profitability of such type of electric car. This broad view is formalised in a system dynamics model that captures the potential effects of supply side constraints. Four scenarios are simulated. The results show that the levels of CO2 emissions of new cars are substantially reduced only in the one that assumes lower motorisation. Based on these simulations, the conclusion that the diffusion of electric sport utility vehicles does not necessarily contribute to mitigating car emissions in Europe is drawn. Less reliance on technology fixes, downsizing and reduced motorisation are identified as solutions worth investigating to meet ambitious climate goals. Further research on how vehicle manufacturers distribute batteries is needed.

Roadblocks to fuel-cell electric vehicle diffusion: Evidence from Germany, Japan and California

• We examine systemic barriers hampering the diffusion of fuel cell electric vehicles in three influential markets. • Common barriers occur in vehicle production, refuelling infrastructure, vehicle demand and institutions. • Unique barriers are station reliability in California, their profitability in Germany and Japan and political support in Germany and California. • Barriers are frequently perceived in relation to the faster diffusion of battery electric vehicles. • We suggest implications for theory and practice based on findings. Fuel cell electric vehicles (FCEV) are diffusing slowly, well below historical expectations and government targets. To elucidate key factors that may explain this sluggish growth, we identify barriers in three influential markets: Germany, Japan and California. Combining data from 59 interviews and secondary documents, we examine each market from four dimensions: (i) vehicle production, (ii) supporting infrastructure, (iii) vehicle demand, and (iv) institutions. Findings reveal a web of systemic and self-reinforcing barriers hampering market formation in all four dimensions. We also find that stakeholders perceive FCEV market barriers in relation to competing technologies; namely battery electric vehicles (BEVs). Faster market growth and lower hurdles for BEVs are thereby raising the relative barriers for FCEVs, further hampering the latter’s deployment potential. Findings thus reveal the importance of considering interactions between different technological systems when studying diffusion. They also provide valuable hints for industry and government to confront these systemic barriers.

New technology product introduction strategy with considerations for consumer-targeted policy intervention and new market entrant

The emergence of new technology products brings systematic changes to the market, and appropriate responses to such changes are essential for the survival and success of firms. This study investigated producers' optimal new product introduction (and positioning) strategies in various situations that require different sets of decisions. Specifically, we considered the diffusion of hybrid electric vehicles and battery electric vehicles (BEVs) in the South Korean automotive market. A model incorporating the strategic, forward-looking behaviors of both producers and consumers was used to derive producer's optimal new product introduction plan based on long-term market forecasting. Then, we conducted simulation analyses to investigate the benefit of forward-looking planning and how optimal strategies change depending on the policy interventions and market entrance of the new producer. The results show that a forward-looking strategy could improve the market performance of new products by up to 40 % compared to the myopic strategy, and the plan adjustment of the incumbent in response to competition could reduce competition-related losses by up to 9 %. Finally, stronger policy intervention and new market competition will motivate producers to introduce more, less-expensive BEVs in their product portfolio. Such responses significantly expand the BEV market, which is also a socially desirable outcome.