Electric Vehicle Charging Pricing Design for Agent-Based Traffic Microsimulation

Eco-driving is a key strategy for reducing energy consumption and emissions in electric vehicles (EVs) and internal combustion engine (ICE) vehicles. However, research gaps remain regarding its effectiveness across different driving environments, vehicle types, transmission systems, and contexts. This research evaluates eco-driving efficiency in urban and interurban settings, comparing small (Caceres) and large (Madrid) cities and assessing EVs ICE with direct, manual, and automatic transmissions. The authors conducted a large-scale driving experiment in Spain, with over 500 test runs across different road types. Results in the large city show that eco-driving reduces energy consumption by 30.4% in EVs on urban roads, benefiting from regenerative braking, compared to 10.75% in manual ICE vehicles. Automatic ICE vehicles also performed well, with 29.55% savings in local streets. In interurban settings, manual ICE vehicles achieved the highest savings (20.31%), while EVs showed more minor improvements (11.79%) due to already optimized efficiency at steady speeds. The small city showed higher savings due to smoother traffic flow, while single-speed transmissions in EVs enhanced efficiency across conditions. These findings provide valuable insights for optimizing eco-driving strategies and vehicle design. Future research should explore AI-driven eco-driving applications and real-time optimization to improve sustainable mobility.

Impacts of charging pricing schemes on cost-optimal logistics electric vehicle fleet operation

Greenhouse gas emissions-related issues have been extensively discussed in the past years, with over 70 countries already committed to a carbon-neutral economy by 2050. The electrification of transportation modals has increased following these goals, where Electric Vehicles (EVs) are starting to take Internal Combustion Engine Vehicles (ICEV) market share all over the globe. Besides the particular complexity in comparing EVs and ICEVs, challenges involving the nature of EVs and their integration with cities, such as the lack of public locals for charging, are also critical and interfere with their development. In this context, this work aims at studying the problem of a Battery Swapping Station (BSS), a structure where the EVs users swap their depleted batteries for fully or partially charged ones. In order to simulate the BSS daily operations and batteries charging schedule, a novel Mixed Integer Linear Programming (MILP) model is proposed, taking into account battery heterogeneity, the use of local photovoltaic (PV) production and battery degradation based on charging profile. A collection of BSS operation metrics are designed to evaluate the solution quality of the proposed scheduling model. A numerical experiment comprising four case studies based on real data from the US power and transportation systems is presented, with insights and analyses on the PV and grid power use, as well as a BSS financial comparison against close-related benchmark scheduling approaches, together with sensitivities on BSS sizing plan and costumers attendance.

A distributed charging pricing strategy for highway microgrid considering carbon trading: A Stackelberg evolutionary joint game approach

Power systems have been undergoing radical changes in recent years, and their planning and operation will be surely undertaken according to the Smart Grid (SG) vision in the near future. The SG initiatives aim at introducing new technologies and services in power systems, to make the electrical networks more reliable, efficient, secure and environmentally-friendly. In particular, it is expected that communication technologies, computational intelligence and distributed energy sources will be widely used for the whole power system in an integrated fashion. In particular, nowadays, unprecedented challenges like as stringent regulations, environmental concerns, growing demand for high quality, reliable electricity and rising customer expectations are forcing utilities to rethink about electricity generation and delivery from the bottom up. Moreover, the availability of low cost computing and telecommunications technologies, new generation options, and scalable, modular automation systems push utilities to be dynamic, innovative and ambitious enough to take advantage of them. Driven by the dynamics of the new energy environment, leading utilities, technology vendors and government organizations have created a vision of the next generation of energy delivery systems: the Smart Grid. Operational changes of the grid, caused by restructuring of the electric utility industry and electricity storage technology advancements, have created an opportunity for storage systems to provide unique services to the evolving grid. Especially Battery Energy Storage Systems (BESSs), thanks to the large number and variety of services they can provide, are powerful tools for the solution of some challenges that future grids will face. This consideration makes BESSs critical components of the future grids. The BESS can be applied for different services into the different levels of power system chain to satisfy technical challenges and provide financial benefits. In the context of the application of BESSs in SGs, there are two main problems that need to be addressed in a way that exploits the BESS potential, that are linked to their operation and sizing. This thesis focuses on both these aspects, proposing new strategies that allow optimizing the BESS adoption. When dealing with BESSs, sizing and operation are strictly linked. The correct sizing of a BESS, in fact, needs to take into account its operation which in turn will be effected with the aim of optimizing the whole system where it is included. In the first part of this research study, advanced optimal operating strategies were proposed for BESSs by considering both the distribution system operator perspective and the end user. Thus, the proposed operating strategies were performed with the aim of (i) leveling the active power requested by the loads connected to a distribution system (distribution system operator service), (ii) reducing the electricity costs sustained by an end-use costumer that provides demand response (DR) (end user service) and (iii) scheduling a microgrid (µG) with DR resources such as Plug-in Electric Vehicles (PEVs) and Data Centers (DCs) (both the two section service). The proposed strategies also satisfied technical constraints of BESSs and other components of the µG. The second part of the thesis presented the optimal sizing of BESSs aimed at maximizing the benefits related to their use. In the thesis, the sizing, which is performed by considering the end user point of view with reference to both the industrial and residential customers, is effected by adopting both deterministic and probabilistic approaches. With reference to the deterministic approach, a simple and quick closed form procedure for the sizing of BESSs in residential and industrial applications was proposed. In case of probabilistic approach, the case of a BESS installed in an industrial facility was considered and the sizing was performed based on the decision theory. Technical improvements and economic benefits of optimal operation and optimal sizing of BESSs in SG are demonstrated by the obtained results which are reported in the numerical applications. More specifically, it was clearly determined that BESSs can offer technical supports into the distribution operator section of the grid in terms of load management and security challenges. Moreover optimal integration of BESSs into the grid was also appealing for end users thanks to valuable amounts of electricity bill cost reduction. Regarding the original contribution of the thesis, the following considerations can be done. With reference to the load leveling service, an innovative two-step procedure (day-ahead scheduling and very short time predictive control) was proposed which optimally controls a BESS connected to a distribution substation in order to perform load leveling. In case of DR, a proper control of the BESS was proposed in order to perform DR under different price schemes, such as Real Time Pricing (RTP) and Time of Use (TOU) without modifying the daily work cycle of the industrial loads. The control procedure allows achieving contemporaneously two important goals that are the reduction of the bill costs and the prolonging the battery's lifetime so further reducing the costs sustained by the customer. With reference to the scheduling of microgrids, the original contribution of the thesis is focused on the proposal of optimization strategies aimed at managing and coordinating, simultaneously, batteries on board of vehicles or equipping data centers' Uninterruptable Power Supply (UPS) and Distributed Generation (DG) units. Also comparisons among different single-objective based strategies are made in order to highlight the most convenient. With reference to the sizing based on deterministic approach, unlike the other relating literature, the innovative contribution is that the closed form procedure takes into account both the technical constraints of the battery and contractual agreements between the customer and the utility. Moreover, in the economical analysis performed for the sizing, which is applied with reference to both residential and small industrial customers and is based on actual TOU tariffs, a wide sensitivity analysis to consider different perspectives in terms of life span and future costs was performed. Some aspects that affect the profitability of the battery, such as technological limitations (e.g. the battery and converter efficiency), economic barriers (e.g. capital cost and the rate of change of the cost) and variation of the load profile along the years were deeply analyzed. In case of sizing based on probabilistic approach, the original contributions of the thesis are mainly referred to the proposal of a new method that uses a decision theory-based process to obtain the best sizing alternative considering the various uncertainties affecting the sizing procedure. The thesis is organized in three chapters which are dealing with integration of BESSs in SGs. The first chapter reports basic concepts and characteristics of BESSs, fundamental components and features of SGs and different services that BESSs can provide. The optimal operation strategies of BESS are considered in second chapter which includes their problem formulation, solving procedures and results. The third chapter deals with the optimal sizing problem of BESSs for which the problem formulation, solving procedures and results are reported. Finally, the conclusions are presented in the last part of thesis.

Reflecting government policy to restrict internal combustion engine vehicles (ICEVs), automakers are promoting the transition, or shift, from ICEVs to electric vehicles (EVs). Mass adoption of EVs will have a significant impact on the entire value chain of the electric industry, which contain power generation, power grid and consumer facilities. In order to further improve the competitiveness of EVs and achieve a full-scale EV shift, it is necessary to anticipate the influence of the trend on each component of the value chain and to establish appropriate hardware installation and operation procedures to minimize cost. By adopting such an approach, it is possible to reduce greenhouse gas emissions by economically shifting to EVs, and also to have positive environmental impacts on other components of the value chain such as reduction of the usage of peak power generation facilities and promotion of variable renewable energy such as photovoltaic and wind power. Ennet Corporation is an electricity retailer established in 2000 when electricity deregulation started in Japan, and is one of the leading companies among the new entrants. In this paper, we will describe the requirements for achieving an economical EV shift and introduce our smart charging service "EnneEV", developed using our unique technologies based on our advantages as an electricity retailer and the advanced EV charging and energy management platform of Driivz Ltd.

This paper concentrates on the pricing design in electric vehicle (EV) platoon charging networks with hybrid traffic flows, where there exist different sizes of EV platoons, and charging stations have different amounts of available renewable energy. Two pricing schemes are proposed in terms of behavior awareness and congestion awareness to strike a balance between network revenue, renewable energy utilization, and overloading avoidance. Specifically, the proposed behavior-aware pricing scheme is a probabilistic approach to address the effects of driving preferences, which determines the targeted charging stations based on the charging costs. Therefore, the charging price is optimized to maximize the network revenue while improving renewable energy utilization. The proposed congestion-aware pricing scheme seeks to mitigate the overloading at each charging station by introducing the piecewise pricing mechanism, where the charging price at the charging station depends on the charging demand. The results demonstrate that our pricing schemes can boost network revenue and renewable energy utilization well. The behavior-aware pricing scheme can achieve larger network revenue than the congestion-aware pricing counterpart, and the congestion-aware pricing scheme is a better option for overcoming the load imbalance.

The environmental impact of electric vehicles: A novel life cycle-based evaluation framework and its applications to multi-country scenarios

Author(s): Muehlegger, Erich; Rapson, David | Abstract: This research project explores the plug-in electric vehicle (PEV) market, including both Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs), and the sociodemographic characteristics of purchasing households. The authors use detailed micro-level data on PEV purchase records to answer two primary research questions. Their results confirm that low-income households exhibit a lower share of PEV purchases than they do for conventional, internal combustion engine (ICE) vehicles. Households with annual income less than $50,000 comprise 33 percent of ICE purchases and only 14 percent of PEVS. By comparison, high-income households earning more than $150,000 annually comprise only 12 percent of ICE purchases and 35 percent of PEV purchases over their sample period. Similarly, unsurprising patterns can be seen across ethnicities. For example, non-Hispanic Whites represent 41 percent of ICE purchases but 55 percent of PEV purchases, as compared to Hispanics (38 percent of ICE and 10 percent of PEVs) and African Americans (3 percent of ICEs and 2 percent of PEVS). These differences naturally raise questions about barriers to PEV adoption among low-income and minority ethnic populations. By comparing outcomes in the ICE, hybrid, and PEV markets across income and ethnic groups, the authors are able to test whether price discrimination and barriers to market access are higher in PEV markets for low-income and minority ethnic groups. The authors find that, overall, they are not, although there are mixed results for the used PEV market. In general, non-white, low-income populations face higher prices in the used PEV market, relative to a baseline, than they do in the new PEV market. While some people travel farther to buy used PEVs than they do to buy used ICE vehicles, there is not a pattern that would indicate systematic discrimination (e.g. Hispanics travel farther to buy used PHEVs but less far to buy used BEVs). While the authors admit that their empirical approach cannot control for all potential vehicle composition effects, the authors view their results as being most consistent with a market that provides access to all ethnicities and income groups.View the NCST Project Webpage

Li-ion battery safety in electric buses is critically affected by rollover accidents, which can cause severe deformation of the bus superstructure. Such deformation may cause internal short circuits and trigger thermal runaway. In this context, this work investigates how different propulsion modes affect the safety of a bus superstructure under a rollover scenario in accordance with UNECE Regulation No. R66.02. This work studied an internal combustion engine (ICE) and electric propulsion systems, using the ICE chassis as the base for the electric bus. The study defines worst-case scenarios for both vehicle types, determines the center of gravity (CoG), and performs numerical simulations using the finite element method. The ICE and electric buses have CoGs of 5397.5 × 13.0 × 1617.4 and 4474.1 × 20.9 × 1682.2 mm, respectively. The ICE vehicle had a total weight of 15,836 kg and a reference energy of 5.0580 × 10 5 kg·m 2 /s 2 , while the electric vehicle had a total weight of 18,118 kg and a reference energy of 5.1145 × 10 5 kg·m 2 /s. For the rollover simulations, the unstable positions before tilting were set to 33.7° and 35° for the ICE and electric vehicles, respectively, and the models were rotated to ground contact at angular velocities of 1.75 and 1.79 rad/s. The results indicate that the ICE vehicle satisfied the regulatory requirements. However, the electric vehicle exhibited intrusion of up to 32 mm into the residual space when the same ICE structural concept and passenger configuration were applied. Therefore, some modifications were proposed, including capacity adjustments and alternative battery systems, to preserve the residual space during the rollover scenario. These results highlight the need to account for electric bus specific characteristics rather than directly converting ICE chassis designs.

Electric vehicles (EVs) are viewed as a key pathway to reducing greenhouse gas emissions. However, their environmental benefits depend on whether their vehicle kilometers traveled (VKT) substitute for travel by internal combustion engine vehicles (ICEVs) rather than generating additional travel demand. This review synthesizes evidence from 34 empirical studies examining VKT by battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), comparing them with ICEVs and identifying the factors that shape EV usage. Across studies, BEVs and PHEVs generally travel fewer kilometers per day than ICEVs, with BEVs showing the lowest VKT levels. Regional differences are evident: BEVs in Europe typically record higher VKTs than those in the US. VKT patterns are influenced by a combination of socio-demographic, spatial, and vehicle-related factors, as well as EV-specific elements such as charging access and ownership type. Leased and company EVs typically travel more kilometers than privately owned vehicles, and greater access to charging is generally associated with higher electric VKT. Most studies included in this review draw on data from the early phases of EV adoption and focus on a limited set of regions. As a result, current findings may not fully capture emerging VKT patterns as EV markets scale and diversify. Future research should incorporate more recent and geographically varied datasets to track evolving travel behaviors and better assess how EVs are reshaping mobility and sustainability outcomes.

Energy and environmental costs for electric vehicles using CO 2-neutral electricity in Sweden

<div>Life cycle analyses suggest that electric vehicles are more efficient than gasoline internal combustion engine vehicles (ICEVs). Although the latest available data reveal that electric vehicle (EV) life cycle operational efficiency is only 17% (3 percentage points) higher than a gasoline ICEV, overall life cycle efficiencies including manufacturing for EVs are 2 percentage points lower than for ICEVs. Greenhouse gas (GHG) emissions of EVs are only 4% lower than ICEVs, but <i>criteria</i> emissions of NOx and PM are approaching or exceeding two times those of gasoline ICEVs. Significant reductions in electric grid emissions are required to realize EV’s anticipated emission benefits. In contrast, hybrid electric vehicles (HEVs) have over 70% higher efficiency and 28% lower GHG emissions than today’s EVs. For heavy-duty trucks using today’s <i>gray</i> hydrogen, produced by steam–methane reforming, overall life cycle efficiencies of ICEs and fuel cells are 63% higher than electric powertrains using today’s electric grid, but 25% lower than diesel-fueled ICEs. GHG emissions of ICEs and fuel cells using <i>gray</i> hydrogen are 34% lower than electric powertrains using today’s grid, but are over 50% higher than diesel-fueled ICEs. Only 1% of today’s hydrogen is <i>green</i>, derived by electrolysis using renewable energy. Using <i>green</i> hydrogen, life cycle efficiencies of ICEs or fuel cells are 36% lower than with <i>gray</i> hydrogen. GHG emissions of <i>green</i> hydrogen-fueled ICE or fuel cell powertrains, although reduced by 69% relative to <i>gray</i> hydrogen, are nearly twice those of an electric powertrain using renewable electricity.</div>

<div>The transportation sector faces heightened scrutiny to implement sustainable technologies due to market trends, escalating climate change and dwindling fossil fuel reserves. Given the decarbonization efforts underway in the sector, there are now rising concerns over the sustainability challenges in electric vehicle (EV) adoption. This study leverages ISO 14040 Lifecycle Assessment methodology to evaluate EVs, internal combustion engine vehicles (ICEVs), and hybrid electric vehicles (HEVs) spanning cradle-to-grave lifecycle phases. To accomplish this an enhanced triadic sustainability metric (TSM) is introduced that integrates greenhouse gas emissions (GHG), energy consumption, and resource depletion. Results indicate EVs emit approximately 29% fewer GHG emissions than ICEVs but about 4% more than HEVs on the current the US grid, with breakeven sustainability achieved within a moderate mileage range compared to ICEVs. Renewable energy integration on the grid significantly enhances EV performance, reducing emissions up to 31% with full renewable adoption, thereby lowering breakeven mileage substantially. The TSM framework clearly highlights optimal EV sustainability under 50%–70% renewable scenarios versus ICEVs and HEVs, offering policy makers a balanced metric for decision-making. These findings provide actionable frameworks for automotive engineers and policy makers to advance sustainable transportation through renewable grid upgrades and optimized battery design.</div>

Globally, with the rapid growth of the population, the use of cars is also increasing. Although there is an increase in the use of electric vehicles, the vast majority of the vehicles used are internal combustion engine vehicles. Fossil fuel vehicles have disadvantages such as damaging the environment due to their high emission values, using non-renewable energy sources as fuel, high maintenance costs, and complex vehicle structures. Electric vehicles have many advantages such as being sensitive to the environment with a near-zero emission value, simple structures, low maintenance costs, and the use of renewable energy sources as fuel. Today, the reserve ratios of fossil fuels are rapidly depleting. Consumers tend to buy electric vehicles because of the environmental damage caused by fossil fuel vehicles due to the high emissions they emit, and because of the danger of depletion of non-renewable energy sources. The purchase of electric vehicles from the factory is difficult due to the few product varieties and the high prices in the market. It is possible for consumers to have electric vehicles with the features, colors, and models they want at much more affordable prices, by converting internal combustion engine vehicles to electric vehicles. Each country has its own regulations for the conversion process. Transformation operations in our country are carried out in accordance with the Regulations of the Ministry of Science, Industry, and Technology. There are ready-made conversion kits of different brands on the market that contain the components necessary for the conversion of internal combustion engine vehicles to electric vehicles. In this study, the advantages and disadvantages of internal combustion engine vehicles and electric vehicles, why conversion is necessary, and how conversion should be carried out will be discussed. Thanks to the conversion to an internal combustion engine, there will be a decrease in the emission of harmful gases to the environment, an economic contribution will be made to the country, and consumers will be able to have the vehicle they want at affordable prices.