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Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Vehicle energy demand"

1

Shi, Jian, Bin Liu, Yong He Huang, and Hua Liang Hou. "Forecast on China's New Energy Vehicle Market Demand." Applied Mechanics and Materials 496-500 (January 2014): 2822–26. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2822.

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Анотація:
With the rapid development of new energy vehicle in China, the volume has been the hot topic in the fields of automotive industry. A series of subsidy and financial policies has been released by the government. Peoples in this industry care about the effective of the policies especially the new energy vehicles volume and market share in China. In this paper, we analysis the development experience of developed countries such as the US and Japan, and calculate the new energy vehicles volume and market share in China from 2015 to 2020 by model. Its more effective to the government department to draw a plan of new energy vehicle development blue print.
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2

Jardin, Philippe, Arved Esser, Stefano Givone, Tobias Eichenlaub, Jean-Eric Schleiffer, and Stephan Rinderknecht. "The Sensitivity in Consumption of Different Vehicle Drivetrain Concepts Under Varying Operating Conditions: A Simulative Data Driven Approach." Vehicles 1, no. 1 (March 14, 2019): 69–87. http://dx.doi.org/10.3390/vehicles1010005.

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Анотація:
As an important aspect of today’s efforts to reduce greenhouse gas emissions, the energy demand of passenger cars is a subject of research. Different drivetrain concepts like plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV) are introduced into the market in addition to conventional internal combustion engine vehicles (ICEV) to address this issue. However, the consumption highly depends on individual usage profiles and external operating conditions, especially when considering secondary energy demands like heating, ventilation and air conditioning (HVAC). The approach presented in this work aims to estimate vehicle consumptions based on real world driving profiles and weather data under consideration of secondary demands. For this purpose, a primary and a secondary consumption model are developed that interact with each other to estimate realistic vehicle consumptions for different drivetrain concepts. The models are parametrized by referring to state of the art contributions and the results are made plausible by comparison to literature. The sensitivities of the consumptions are then analysed as a function of trip distance and ambient temperature to assess the influence of the operating conditions on the consumption. The results show that especially in the case of the BEV and PHEV, the trip distance and the ambient temperature are a first-order influencing factor on the total vehicle energy demand. Thus, it is not sufficient to evaluate new vehicle concepts solely on one-dimensional driving cycles to assess their energy demand. Instead, the external conditions must be taken into account for a proper assessment of the vehicle’s real world consumption.
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3

Chen, Yuche, Ruixiao Sun, and Xuanke Wu. "Estimating Bounds of Aerodynamic, Mass, and Auxiliary Load Impacts on Autonomous Vehicles: A Powertrain Simulation Approach." Sustainability 13, no. 22 (November 10, 2021): 12405. http://dx.doi.org/10.3390/su132212405.

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Анотація:
Vehicle automation requires new onboard sensors, communication equipment, and/or data processing units, and may encourage modifications to existing onboard components (such as the steering wheel). These changes impact the vehicle’s mass, auxiliary load, coefficient of drag, and frontal area, which then change vehicle performance. This paper uses the powertrain simulation model FASTSim to quantify the impact of autonomy-related design changes on a vehicle’s fuel consumption. Levels 0, 2, and 5 autonomous vehicles are modeled for two battery-electric vehicles (2017 Chevrolet Bolt and 2017 Nissan Leaf) and a gasoline powered vehicle (2017 Toyota Corolla). Additionally, a level 5 vehicle is divided into pessimistic and optimistic scenarios which assume different electronic equipment integration format. The results show that 4–8% reductions in energy economy can be achieved in a L5 optimistic scenario and an 10–15% increase in energy economy will be the result in a L5 pessimistic scenario. When looking at impacts on different power demand sources, inertial power is the major power demand in urban driving conditions and aerodynamic power demand is the major demand in highway driving conditions.
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4

Pan, Xiaoming, Yong Wu, and Gao Chong. "Multipoint Distribution Vehicle Routing Optimization Problem considering Random Demand and Changing Load." Security and Communication Networks 2022 (July 8, 2022): 1–10. http://dx.doi.org/10.1155/2022/8199991.

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Анотація:
In the distribution scenario, the using cost of vehicles is closely related to energy consumption, and the energy consumption rate of a vehicle is closely related to the size of its load. The traditional vehicle routing optimization model takes the shortest distance as the optimization goal when the customer demand is determined, while the influence of the random demand and the changing load on the energy consumption and cost of vehicles in the process of distribution is ignored. Therefore, in this paper, load varying vehicle routing problem with stochastic demands (LVGVRPSD) model is proposed with the goal of minimizing transportation energy consumption and considering the load variability and the randomness of customer demand. K-means clustering algorithm is combined with ant colony optimization (ACO) to solve the problem, and the constraint of risk probability is introduced to describe the vehicle overload problem. Examples in the standard vehicle routing problem test data set are provided and analyzed. LVGVRPSD is also compared with the traditional capacitated vehicle routing problem (CVRP) model. The case study results show that the vehicle energy consumption can be reduced by 2% in the model that considers changing load compared to the model that does not consider changing load. The results illustrate that the method of path optimization is more advantageous and reasonable in the pursuit of reducing energy consumption, when the changing load and the random demand of customer are considered.
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5

Waldron, Julie, Lucelia Rodrigues, Mark Gillott, Sophie Naylor, and Rob Shipman. "The Role of Electric Vehicle Charging Technologies in the Decarbonisation of the Energy Grid." Energies 15, no. 7 (March 26, 2022): 2447. http://dx.doi.org/10.3390/en15072447.

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Анотація:
Vehicle-to-grid (V2G) has been identified as a key technology to help reduce carbon emissions from the transport and energy sectors. However, the benefits of this technology are best achieved when multiple variables are considered in the process of charging and discharging an electric vehicle. These variables include vehicle behaviour, building energy demand, renewable energy generation, and grid carbon intensity. It is expected that the transition to electric mobility will add pressure to the energy grid. Using the batteries of electric vehicles as energy storage to send energy back to the grid during high-demand, carbon-intensive periods will help to reduce the impact of introducing electric vehicles and minimise carbon emissions of the system. In this paper, the authors present a method and propose a V2G control scheme integrating one year of historical vehicle and energy datasets, aiming towards carbon emissions reduction through increased local consumption of renewable energy, offset of vehicle charging demand to low carbon intensity periods, and offset of local building demand from peak and carbon-intensive periods through storage in the vehicle battery. The study included assessment of strategic location and the number of chargers to support a fleet of five vehicles to make the transition to electric mobility and integrate vehicle-to-grid without impacting current service provision. The authors found that the proposed V2G scheme helped to reduce the average carbon intensity per kilowatt (gCO2/kWh) in simulation scenarios, despite the increased energy demand from electric vehicles charging. For instance, in one of the tested scenarios V2G reduced the average carbon intensity per kilowatt from 223.8 gCO2/kWh with unmanaged charging to 218.9 gCO2/kWh using V2G.
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6

Feng, Ziru, Tian Cai, Kangli Xiang, Chenxi Xiang, and Lei Hou. "Evaluating the Impact of Fossil Fuel Vehicle Exit on the Oil Demand in China." Energies 12, no. 14 (July 19, 2019): 2771. http://dx.doi.org/10.3390/en12142771.

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Анотація:
Vehicle ownership is one of the most important factors affecting fuel demand. Based on the forecast of China’s vehicle ownership, this paper estimates China’s fuel demand in 2035 and explores the impact of new energy vehicles replacing fossil fuel vehicles. The paper contributes to the existing literature by taking into account the heterogeneity of provinces when using the Gompertz model to forecast future vehicle ownership. On that basis, the fuel demand of each province in 2035 is calculated. The results show that: (1) The vehicle ownership rate of each province conforms to the S-shape trend with the growth of real GDP per capita. At present, most provinces are at a stage of accelerating growth. However, the time for the vehicle ownership rate of each province to reach the inflection point is quite different. (2) Without considering the replacement of new energy vehicles, China’s auto fuel demand is expected to be 746.69 million tonnes (Mt) in 2035. Guangdong, Henan, and Shandong are the top three provinces with the highest fuel demand due to economic and demographic factors. The fuel demand is expected to be 76.76, 64.91, and 63.95 Mt, respectively. (3) Considering the replacement of new energy vehicles, China’s fuel demand in 2035 will be 709.35, 634.68, and 560.02 Mt, respectively, under the scenarios of slow, medium, and fast substitution—and the replacement levels are 37.34, 112.01, and 186.67 Mt, respectively. Under the scenario of rapid substitution, the reduction in fuel demand will reach 52.2% of China’s net oil imports in 2016. Therefore, the withdrawal of fuel vehicles will greatly reduce the oil demand and the dependence on foreign oil of China. Faced with the dual pressure of environmental crisis and energy crisis, the forecast results of this paper provide practical reference for policy makers to rationally design the future fuel vehicle exit plan and solve related environmental issues.
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7

Wang, Junmin. "Energy Consumption and Tailpipe Emission Reductions by Personalized Control of Connected Vehicles." Mechanical Engineering 139, no. 09 (September 1, 2017): S5—S11. http://dx.doi.org/10.1115/1.2017-sep-4.

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Анотація:
This article demonstrates several approaches to the vehicle energy consumption and tailpipe emission reduction opportunities. The article leverages the vehicle storage dynamics through smart and personalized optimization and control approaches in the context of connected vehicles. Recent advances in vehicle connectivity and automation have brought unprecedented information richness and new degrees of freedom that can be synergized with insightful understanding of vehicle powertrain and aftertreatment physical systems. Vehicle automation also provides new degrees of freedom that can be further leveraged by the vehicle control systems to improve vehicle energy efficiency and reduce tailpipe emissions. While vehicle automation levels probably will keep increasing, humans will still be involved in vehicle operations at various levels for the foreseeable future. The prediction of future vehicle’s power demand based on vehicle connectivity can significantly benefit tailpipe emission reductions and fuel economy.
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8

Khan Ankur, Atiquzzaman, Stefan Kraus, Thomas Grube, Rui Castro, and Detlef Stolten. "A Versatile Model for Estimating the Fuel Consumption of a Wide Range of Transport Modes." Energies 15, no. 6 (March 18, 2022): 2232. http://dx.doi.org/10.3390/en15062232.

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Анотація:
The importance of a flexible and comprehensive vehicle fuel consumption model cannot be understated for understanding the implications of the modal changes currently occurring in the transportation sector. In this study, a model is developed to determine the tank-to-wheel energy demand for passenger and freight transportation within Germany for different modes of transport. These modes include light-duty vehicles (LDVs), heavy-duty vehicles (HDVs), airplanes, trains, ships, and unmanned aviation. The model further estimates future development through 2050. Utilizing standard driving cycles, backward-looking longitudinal vehicle models are employed to determine the energy demand for all on-road vehicle modes. For non-road vehicle modes, energy demand from the literature is drawn upon to develop the model. It is found that various vehicle parameters exert different effects on vehicle energy demand, depending on the driving scenario. Public transportation offers the most energy-efficient means of travel in the forms of battery electric buses (33.9 MJ/100 pkm), battery electric coaches (21.3 MJ/100 pkm), fuel cell electric coaches (32.9 MJ/100 pkm), trams (43.3 MJ/100 pkm), and long-distance electric trains (31.8 MJ/100 pkm). International shipping (9.9 MJ/100 tkm) is the most energy-efficient means of freight transport. The electrification of drivetrains and the implementation of regenerative braking show large potential for fuel consumption reduction, especially in urban areas. Occupancy and loading rates for vehicles play a critical role in determining the energy demand per passenger-kilometer for passenger modes, and tonne-kilometer for freight modes.
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9

Kubendran, V., Y. Mohamed Shuaib, and J. Preetha Roselyn. "Modelling of Vehicle Dynamics and Determination of Energy Demand for Electric Vehicle." Journal of Physics: Conference Series 2335, no. 1 (September 1, 2022): 012049. http://dx.doi.org/10.1088/1742-6596/2335/1/012049.

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Анотація:
Abstract The WLTP Class 3 driving cycle is used in this article for the design of a battery and super-capacitor for electric vehicles. The energy demand for electric vehicle is calculated using WLTP drive cycle and the total power required for electric vehicle is calculated by calculating tractive force. A hybrid energy storage system (HESS) overcomes numerous shortcomings of a battery energy storage system (BESS), including reduced battery life, limited power density, etc. In a proposed system, a Li-Ion battery is coupled with a super-capacitor/Ultra-capacitor as a bidirectional converter, where the Li-Ion battery is the primary energy source, while the Super Capacitor/Ultra-capacitor is an auxiliary energy source. The range of battery and Super Capacitor/ultra-capacitor sizes for Tata Nixon 2020 are calculated and simulated using the MATLAB/SIMULINK environment to verify the efficiency and effectiveness of the proposed model.
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10

Qu, Lu, and Yanwei Li. "Research on Industrial Policy from the Perspective of Demand-Side Open Innovation—A Case Study of Shenzhen New Energy Vehicle Industry." Journal of Open Innovation: Technology, Market, and Complexity 5, no. 2 (May 28, 2019): 31. http://dx.doi.org/10.3390/joitmc5020031.

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Анотація:
Nowadays, new energy vehicles play an important role in the transformation and upgrade of China’s energy security, energy conservation and other industries. At present, there are 26 pilot cities for the demonstration of new energy vehicles in China; however, the operation effect and experience of the pilot cities have been summarized less. This paper takes Shenzhen’s new energy vehicle industry policy as the object of research, in order to explore the impact of demand innovation on the development of new energy vehicles. This paper summarizes the three stages of Shenzhen’s new energy vehicle industry promotion, and further analyzes the policy and market environments of each stage by using the demand-side innovation policy theory. By reflecting on the concept of policy design, this paper proposes that decision makers need to cultivate open innovative thinking, and transform their production-oriented policy design into a demand-oriented policy design. This conclusion is helpful for pilot cities in order to adjust their policies over time according to the different stages of industrial development, and further improve the innovation and competitiveness of China’s new energy vehicle industry.
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Більше джерел

Дисертації з теми "Vehicle energy demand"

1

PILLA, SIRISH. "DEMAND V/S SUPPLY OF ENERGY FOR ELECTRIC VEHICLE." OpenSIUC, 2021. https://opensiuc.lib.siu.edu/theses/2826.

Повний текст джерела
Анотація:
The ongoing ascent in electric vehicle (EV) selection is commonly observed as certain, as EVs conceivably give a more clean option in contrast to conventional vehicles. However for EVs to understand this potential, singular purchasers don't just need to embrace EVs, they likewise need to utilize the advancements and foundation in a feasible manner EVs are a spotless method of transport when accused of energy from sustainable sources, for example, wind energy and photovoltaic (PV) sun oriented energy. As of now, EVs are commonly charged in the early night, when power interest of families is high and inexhaustible energy creation is low .EV clients should along these lines be urged to act in a more economical manner, by effectively or latently shifting charging request or to participate in brilliant charging or vehicle-to-framework plans worked by gatherings, for example, aggregators.
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2

Whitehead, Jake. "Energy Efficient Vehicle Policy: Lessons Learnt : An analysis of the effects of incentive policies on the demand, usage and pricing of energy efficient vehicles." Doctoral thesis, KTH, Transport- och lokaliseringsanalys, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-185933.

Повний текст джерела
Анотація:
Encouraging the uptake of energy efficient vehicles (EEVs) is an aspiration of critical importance in a day and age in which we are confronted with the increasingly dire consequences of human behaviour on our planet, and on the planet for generations to come. The transport sector is one of the highest contributors of anthropogenic greenhouse gas emissions, whilst pollution from this sector is responsible for a large proportion of human deaths each and every year. Given the severity of these issues, it is more important than ever for policy-makers, and researchers alike, to encourage a transition within the community towards more sustainable lifestyles. Transportation is key to this change. As a service that every human being uses, almost every day of his or her life, the transport sector presents a unique opportunity for behavioural change. Through efficient and targeted policies, consumers can be incentivised to make more sustainable transport choices and to consider the consequences of their own actions. Foremost amongst these initiatives is that of encouraging a transition towards energy efficient vehicles. This thesis has been produced in order to shed further light on issues affecting this transition. In particular for policy-makers, this document includes a series of recommendations based on prevailing findings in the current literature, in addition to the novel and significant findings of this research effort. These include the various lessons learnt from government policies that have already been implemented in regions around the globe. As a thesis by publication, this document consists of four research articles that investigate factors affecting the EEV market, specifically in terms of: consumer demand, vehicle usage and product pricing. A number of other demographic and economic factors have also been examined, including the role of economies-of-scale.
Att uppmuntra ökad användningen av energieffektiva fordon (EEVs) är en strävan av avgörande betydelse i en tid då vi konfronteras med de allt mer ödesdigra konsekvenserna av människors påverkan på vår planet, i dag och för kommande generationer. Transportsektorn är en av de sektorer som bidrar mest till utsläppen av antropogena växthusgaser. Utsläpp från transportsektorn bidrar även till ett stort antal dödsfall varje år. Med tanke på vikten av dessa frågor är det viktigare än någonsin för beslutsfattare och forskare att bidra till en samhällsövergång mot mer hållbara livsstilar. Transporter är avgörande i denna omvandling. Eftersom transporter är en tjänst som alla människor utnyttjar i stort sett varje dag, erbjuder transportsektorn en unik möjlighet till beteendeförändringar. Genom effektiva och målinriktade åtgärder kan konsumenter ges incitament att göra mer hållbara transportval och överväga konsekvenserna av sina handlingar. Främst bland dessa initiativ är en uppmuntran till en övergång mot mer energieffektiva fordon. Denna avhandling har tagits fram i syfte att belysa frågeställningar som berör denna övergång. För framför allt beslutsfattare innehåller avhandlingen en rad rekommendationer baserade på såväl rådande forskningsresultat från aktuell forskningslitteratur som nya resultat från denna forskningsinsats. Dessa inkluderar erfarenheter från redan implementerade politiska åtgärder från regioner runt om i världen. Denna sammanläggningsavhandling består av fyra forskningsartiklar som undersöker faktorer som påverkar EEV-marknaden vad gäller konsumentefterfrågan, fordonsanvändning och produktprissättning. Utöver dessa har även ett antal andra demografiska och ekonomiska faktorer, inklusive betydelsen av stordriftsfördelar, undersökts.

QC 20160503

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3

Hsu, Edward Hsuan-Wei. "ELECTRIFICATION OF THE SWEDISH VEHICLE FLEET: CHARGING DEMAND AND THE POWER SYSTEM." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448286.

Повний текст джерела
Анотація:
With the transport sector switching to electric energy to reduce greenhouse gas emission, the supply and demand in the energy system are impacted by this transition. Meanwhile, there are not a lot of studies focus on the electrification of the vehicle fleet in Sweden. To fill up the knowledge gap, the paper aims to identify the total required electrical energy and power for the electrification of the vehicle fleet in Sweden. This includes switching passenger vehicles, light and heavy trucks, and buses to battery electric vehicles. An Electric Vehicle Power Demand Model is designed to answer the research question. It is a simplified model that can calculate energy consumption and power demand from an electric vehicle fleet. To simulate the charging schedule, four scenarios are created with differences in charge speed and the use of smart or unregulated charging. Based on the model, the electric vehicle fleet consumes 20.4 TWh of electricity per year, accounting for 14.7% of total demand in Sweden. Combing the vehicle fleet with other energy services, an average hourly peak load of 16.2 GW in summer and 24.3 in winter can be seen, while the available capacity in Sweden is around 27.1. The result indicates that the current Swedish energy system is capable of handling demand from charging the electric vehicle fleet in terms of power capacity for most times. However, undersupply may happen in some extreme condition during the winter due to higher consumption from other energy services. Furthermore, with the increasing share of renewable power in the system, the availability of these power plants can have a direct impact on the supply. This requires smart charging to shift the charging events to prevent peak hours, which can potentially decrease the peak loads up to 2 GW in EV charging demand during peak hours. However, the actual effect of it still requires more study. Lastly, the model created for the research can be used as a research or decision-making tool to estimate the impact of a group of electric vehicles in the future, therefore, contribute to the development of the sustainable energy transition.
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4

Howerter, Sarah E. "Modeling Electric Vehicle Energy Demand and Regional Electricity Generation Dispatch for New England and New York." ScholarWorks @ UVM, 2019. https://scholarworks.uvm.edu/graddis/1133.

Повний текст джерела
Анотація:
The transportation sector is a largest emitter of greenhouse gases in the U.S., accounting for 28.6% of all 2016 emissions, the majority of which come from the passenger vehicle fleet [1,2]. One major technology that is being investigated by researchers, planners, and policy makers to help lower the emissions from the transportation sector is the plug-in electric vehicle (PEV). The focus of this work is to investigate and model the impacts of increased levels of PEVs on the regional electric power grid and on the net change in CO2 emissions due to the decrease tailpipe emissions and the increase in electricity generation under current emissions caps. The study scope includes all of New England and New York state, modeled as one system of electricity supply and demand, which includes the estimated 2030 baseline demand and the cur- rent generation capacity plus increased renewable capacity to meet state Renewable Portfolio Standard targets for 2030. The models presented here include fully electric vehicles and plug-in hybrids, public charging infrastructure scenarios, hourly charging demand, solar and wind generation and capacity factors, and real-world travel derived from the 2016-2017 National Household Travel Survey. We make certain assumptions, informed by the literature, with the goal of creating a modeling methodology to improve the estimation of hourly PEV charging demand for input into regional electric sector dispatch models. The methodology included novel stochastic processes, considered seasonal and weekday versus weekend differences in travel, and did not force the PEV battery state-of-charge to be full at any specific time of day. The results support the need for public charging infrastructure, specifically at workplaces, with the “work” infrastructure scenario shifting more of the unmanaged charging demand to daylight hours when solar generation could be utilized. Workplace charging accounted for 40% of all non-home charging demand in the scenario where charging infrastructure was “universally” available. Under the increased renewable fuel portfolio, the reduction in average CO2 emissions ranged from 90 to 92% for the vehicles converted from ICEV to PEV. The total emissions reduced for 15% PEV penetration and universally available charging infrastructure was 5.85 million metric tons, 5.27% of system-wide emissions. The results support the premise of plug-in electric vehicles being an important strategy for the reduction of CO2 emissions in our study region. Future investigation into the extent of reductions possible with both the optimization of charging schedules through pricing or other mechanisms and the modeling of grid level energy storage is warranted. Additional model development should include a sensitivity analysis of the PEV charging demand model parameters, and better data on the charging behavior of PEV owners as they continue to penetrate the market at higher rates.
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5

Rey, Diana. "A Gasoline Demand Model for the United States Light Vehicle Fleet." Master's thesis, University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2351.

Повний текст джерела
Анотація:
The United States is the world's largest oil consumer demanding about twenty five percent of the total world oil production. Whenever there are difficulties to supply the increasing quantities of oil demanded by the market, the price of oil escalates leading to what is known as oil price spikes or oil price shocks. The last oil price shock which was the longest sustained oil price run up in history, began its course in year 2004, and ended in 2008. This last oil price shock initiated recognizable changes in transportation dynamics: transit operators realized that commuters switched to transit as a way to save gasoline costs, consumers began to search the market for more efficient vehicles leading car manufactures to close 'gas guzzlers' plants, and the government enacted a new law entitled the Energy Independence Act of 2007, which called for the progressive improvement of the fuel efficiency indicator of the light vehicle fleet up to 35 miles per gallon in year 2020. The past trend of gasoline consumption will probably change; so in the context of the problem a gasoline consumption model was developed in this thesis to ascertain how some of the changes will impact future gasoline demand. Gasoline demand was expressed in oil equivalent million barrels per day, in a two steps Ordinary Least Square (OLS) explanatory variable model. In the first step, vehicle miles traveled expressed in trillion vehicle miles was regressed on the independent variables: vehicles expressed in million vehicles, and price of oil expressed in dollars per barrel. In the second step, the fuel consumption in million barrels per day was regressed on vehicle miles traveled, and on the fuel efficiency indicator expressed in miles per gallon. The explanatory model was run in EVIEWS that allows checking for normality, heteroskedasticty, and serial correlation. Serial correlation was addressed by inclusion of autoregressive or moving average error correction terms. Multicollinearity was solved by first differencing. The 36 year sample series set (1970-2006) was divided into a 30 years sub-period for calibration and a 6 year "hold-out" sub-period for validation. The Root Mean Square Error or RMSE criterion was adopted to select the "best model" among other possible choices, although other criteria were also recorded. Three scenarios for the size of the light vehicle fleet in a forecasting period up to 2020 were created. These scenarios were equivalent to growth rates of 2.1, 1.28, and about 1 per cent per year. The last or more optimistic vehicle growth scenario, from the gasoline consumption perspective, appeared consistent with the theory of vehicle saturation. One scenario for the average miles per gallon indicator was created for each one of the size of fleet indicators by distributing the fleet every year assuming a 7 percent replacement rate. Three scenarios for the price of oil were also created: the first one used the average price of oil in the sample since 1970, the second was obtained by extending the price trend by exponential smoothing, and the third one used a longtime forecast supplied by the Energy Information Administration. The three scenarios created for the price of oil covered a range between a low of about 42 dollars per barrel to highs in the low 100's. The 1970-2006 gasoline consumption trend was extended to year 2020 by ARIMA Box-Jenkins time series analysis, leading to a gasoline consumption value of about 10 millions barrels per day in year 2020. This trend line was taken as the reference or baseline of gasoline consumption. The savings that resulted by application of the explanatory variable OLS model were measured against such a baseline of gasoline consumption. Even on the most pessimistic scenario the savings obtained by the progressive improvement of the fuel efficiency indicator seem enough to offset the increase in consumption that otherwise would have occurred by extension of the trend, leaving consumption at the 2006 levels or about 9 million barrels per day. The most optimistic scenario led to savings up to about 2 million barrels per day below the 2006 level or about 3 millions barrels per day below the baseline in 2020. The "expected" or average consumption in 2020 is about 8 million barrels per day, 2 million barrels below the baseline or 1 million below the 2006 consumption level. More savings are possible if technologies such as plug-in hybrids that have been already implemented in other countries take over soon, are efficiently promoted, or are given incentives or subsidies such as tax credits. The savings in gasoline consumption may in the future contribute to stabilize the price of oil as worldwide demand is tamed by oil saving policy changes implemented in the United States.
M.S.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering MS
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6

Whitehead, Jake Elliott. "The expected and unexpected consequences of implementing energy efficient vehicle incentives." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/84928/12/84928%20Jake%20Whitehead%20Thesis.pdf.

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Анотація:
Completed as part of a Joint PhD program between Queensland University of Technology and the Royal Institute of Technology in Stockholm, Sweden, this thesis examines the effects of different government incentive policies on the demand, usage and pricing of energy efficient vehicles. This study outlines recommendations for policy makers aiming to increase the uptake of energy efficient vehicles. The study finds that whilst many government incentives have been successful in encouraging the uptake of energy efficient vehicles, policy makers need to both recognise and attempt to minimise the potential unintended consequences of such initiatives.
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7

Han, Xue. "Quantitative Analysis of Distributed Energy Resources in Future Distribution Networks." Thesis, KTH, Industriella informations- och styrsystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-98484.

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There has been a large body of statements claiming that the large scale deployment of Distributed Energy Resources (DERs) will eventually reshape the future distribution grid operation in numerous ways. However, there is a lack of evidence specifying to what extent the power system operation will be alternated. In this project, quantitative results in terms of how the future distribution grid will be changed by the deployment of distributed generation, active demand and electric vehicles, are presented. The quantitative analysis is based on the conditions for both a radial and a meshed distribution network. The input parameters are on the basis of the current and envisioned DER deployment scenarios proposed for Sweden. The simulation results indicate that the deployment of DERs can significantly reduce the power losses and voltage drops by compensating power from the local energy resources, and limiting the power transmitted from the external grid. However, it is notable that the opposite results (e.g., severe voltage uctuations, larger power losses) can be obtained due to the intermittent characteristics of DERs and the irrational management of different types of DERs in the DNs. Subsequently, this will lead to challenges for the Distribution System Operator (DSO).
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8

Dini, Alina L. "Influence of new car buyers' purchase experience on plug-in electric vehicle demand." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/116541/1/Alina_Dini_Thesis.pdf.

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Plug-in electric vehicles (PEVs) are one new technology which offers promise for transport sustainability and improving energy efficiency. Global enthusiasm for PEVs has spurred broad-reaching interest, but for jurisdictions where PEV policies are absent, as in Australia, consumer adoption continues to be low. Research into the barriers of adoption for PEVs often identifies cost and lack of infrastructure as key barriers, but consumer's purchase experience plays a pivotal role in technology adoption. This research will help the PEV industry and governments to understand how critical the consumer purchase experience is to overall market success.
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9

Sehar, Fakeha. "An Approach to Mitigate Electric Vehicle Penetration Challenges through Demand Response, Solar Photovoltaics and Energy Storage Applications in Commercial Buildings." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/86654.

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Electric Vehicles (EVs) are active loads as they increase the demand for electricity and introduce several challenges to electrical distribution feeders during charging. Demand Response (DR) or performing load control in commercial buildings along with the deployment of solar photovoltaic (PV) and ice storage systems at the building level can improve the efficiency of electricity grids and mitigate expensive peak demand/energy charges for buildings. This research aims to provide such a solution to make EV penetration transparent to the grid. Firstly, this research contributes to the development of an integrated control of major loads, i.e., Heating Ventilation and Air Conditioning (HVAC), lighting and plug loads while maintaining occupant environmental preferences in small- and medium-sized commercial buildings which are an untapped DR resource. Secondly, this research contributes to improvement in functionalities of EnergyPlus by incorporating a 1-minute resolution data set at the individual plug load level. The research evaluates total building power consumption performance taking into account interactions among lighting, plug load, HVAC and control systems in a realistic manner. Third, this research presents a model to study integrated control of PV and ice storage on improving building operation in demand responsive buildings. The research presents the impact of deploying various combinations of PV and ice storage to generate additional benefits, including clean energy generation from PV and valley filling from ice storage, in commercial buildings. Fourth, this research presents a coordinated load control strategy, among participating commercial buildings in a distribution feeder to optimally control buildings' major loads without sacrificing occupant comfort and ice storage discharge, along with strategically deployed PV to absorb EV penetration. Demand responsive commercial building load profiles and field recorded EV charging profiles have been added to a real world distribution circuit to analyze the effects of EV penetration, together with real-world PV output profiles. Instead of focusing on individual building's economic benefits, the developed approach considers both technical and economic benefits of the whole distribution feeder, including maintaining distribution-level load factor within acceptable ranges and reducing feeder losses.
Ph. D.
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10

Rue, Timothy James. "Modular Vehicle Design Concept." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/51219.

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Outlined herein is the Modular Vehicle [MODV] concept as a cost effective, utilitarian, and highly functional vehicle concept for the changing demands placed on a MAGTF [Marine Air-Ground Task Force] or SP-MAGTF [Special Purpose Marine Air-Ground Task Force] in the 21st century. A large focus is put on the importance of modularity and cost effectiveness of having a 24 hour configurable vehicle to a specific mission and area of operation. Off-road vehicle progression through history is presented and successful design features are noted in order to develop underlying goals for the modular vehicle. The thesis emphasizes recent technology advancements that can shift the foundations of vehicle design including wheel hub motors, high capacity batteries, solid oxide fuel cells, autonomy, structural health monitoring, energy harvesting shock absorbers, non-pneumatic tires, and drive-by-wire options. Predictions on the outlook for the technology progressions is discussed to give insight into the viability of basing a vehicle concept on these technologies. Finally, physical design bounds are presented to provide a foundation for the future design of such a vehicle.
Master of Science
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Книги з теми "Vehicle energy demand"

1

National Research Council (U.S.). Transportation Research Board. Meeting, ed. Energy demand analysis and alternative fuels. Washington, D.C: Transportation Research Board, National Research Council, 1986.

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2

Office, General Accounting. Air pollution: Meeting future electricity demand will increase emissions of some harmful substances : report to congressional committees. Washington, D.C: U.S. General Accounting Office, 2002.

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Частини книг з теми "Vehicle energy demand"

1

Zeng, Xiaohua, and Jixin Wang. "Energy Consumption Analysis and Vehicle Power Demand." In Analysis and Design of the Power-Split Device for Hybrid Systems, 1–24. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4272-0_1.

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2

Ma, Tai-Yu. "Dynamic Charging Management for Electric Vehicle Demand Responsive Transport." In Smart Energy for Smart Transport, 171–82. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-23721-8_14.

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3

Ryan, Paul. "Electricity Demand and Implications of Electric Vehicle and Battery Storage Adoption." In Transition Towards 100% Renewable Energy, 391–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69844-1_35.

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4

Gutiérrez-García, Francisco José, and Ángel Arcos-Vargas. "Forecast of EV Derived Electrical Demand. The Spanish Case." In The Role of the Electric Vehicle in the Energy Transition, 25–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50633-9_2.

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5

Wang, Limian, Du Chen, Shumao Wang, Zhenghe Song, Dihua Yi, Yueyuan Wei, Zhenyu Zhang, and Jinlong Zhou. "Range-extended electrical vehicle performance simulation research based on power demand prediction." In Advances in Energy Science and Equipment Engineering II, 1681–84. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2017. http://dx.doi.org/10.1201/9781315116174-161.

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6

Teske, Sven, and Sarah Niklas. "Decarbonisation Pathways for Transport." In Achieving the Paris Climate Agreement Goals, 187–222. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99177-7_8.

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AbstractAn overview of the main drivers of the transport energy demand and the assumed socio-economic development (population and GDP) until 2050 for ten world regions are given. The countries in each world region are tabulated. Detailed documentation of projected shifts in transport modes for all world regions, including technological assumptions and energy intensities, by vehicle type is presented. This section contains the OECM 1.5 °C transport scenarios for aviation, shipping, road, and rail, each broken down into passenger and freight transport. The calculated energy demands and energy-related carbon emissions for all transport modes are provided.
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7

Luo, Simin, Yan Tian, Wei Zheng, Xiaoheng Zhang, Jingxia Zhang, and Bowen Zhou. "Large-Scale Electric Vehicle Energy Demand Considering Weather Conditions and Onboard Technology." In Communications in Computer and Information Science, 81–93. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2381-2_8.

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8

Gorges, Tobias, Claudia Weißmann, and Sebastian Bothor. "Small Electric Vehicles (SEV)—Impacts of an Increasing SEV Fleet on the Electric Load and Grid." In Small Electric Vehicles, 115–25. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65843-4_9.

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AbstractHeading towards climate neutrality, the electrification of the transport sector has significant impact on the electric grid infrastructure. Among other vehicles, the increasing number of new technologies, mobility offers, and services has an impact on the grid infrastructure. The purpose of this case study therefore is to examine and highlight the small electric vehicle (SEV) impact on the electric load and grid. A data-based analysis model with high charging demand in an energy network is developed that includes renewable energy production and a charging process of a whole SEV fleet during the daily electricity demand peak for the city of Stuttgart (Germany). Key figures are gathered and analysed from official statistics and open data sources. The resulting load increase due to the SEV development is determined and the impact on the electric grid in comparison to battery electric vehicles (BEV) is assessed for two district types. The case study shows that if SEVs replace BEVs, the effects on the grid peak load are considered significant. However, the implementation of a load management system may have an even higher influence on peak load reduction. Finally, recommendations for the future national and international development of SEV fleets are summarized.
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9

Amini, M. Hadi. "A Multi-layer Physic-based Model for Electric Vehicle Energy Demand Estimation in Interdependent Transportation Networks and Power Systems." In Optimization in Large Scale Problems, 243–53. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28565-4_21.

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10

Yazdandoust, Maedeh, and Masoud Aliakbar Golkar. "Participation of Aggregated Electric Vehicles in Demand Response Programs." In Electric Vehicles in Energy Systems, 327–57. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34448-1_14.

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Тези доповідей конференцій з теми "Vehicle energy demand"

1

Yi, Zonggen, and Peter H. Bauer. "Spatio-Temporal Energy Demand Models for Electric Vehicles." In 2014 IEEE Vehicle Power and Propulsion Conference (VPPC). IEEE, 2014. http://dx.doi.org/10.1109/vppc.2014.7007134.

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2

Tarzia, Antonio. "Energy Management for Electric Vehicle: Energy Demand for Cabin Comfort." In CO2 Reduction for Transportation Systems Conference. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2020. http://dx.doi.org/10.4271/2020-37-0031.

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3

Baglione, Melody, Mark Duty, and Greg Pannone. "Vehicle System Energy Analysis Methodology and Tool for Determining Vehicle Subsystem Energy Supply and Demand." In SAE World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2007. http://dx.doi.org/10.4271/2007-01-0398.

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4

Pang, Chengzong, Mladen Kezunovic, and Mehrdad Ehsani. "Demand side management by using electric vehicles as Distributed Energy Resources." In 2012 IEEE International Electric Vehicle Conference (IEVC). IEEE, 2012. http://dx.doi.org/10.1109/ievc.2012.6183273.

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5

Fanti, Maria Pia, Agostino Marcello Mangini, and Michele Roccotelli. "An Innovative Service for Electric Vehicle Energy Demand Prediction." In 2020 7th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2020. http://dx.doi.org/10.1109/codit49905.2020.9263804.

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6

Fink, Daniel, Sean Shugar, Zygimantas Ziaukas, Christoph Schweers, Ahmed Trabelsi, and Hans-Georg Jacob. "Energy Demand Prediction in Hybrid Electrical Vehicles for Speed Optimization." In 8th International Conference on Vehicle Technology and Intelligent Transport Systems. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0011075600003191.

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7

Xu, Zhenbo, Wenlong Shi, Jianbin Wu, Huiwen Qi, Xiangyu Zhang, and Jiawei Wang. "Smart Grid Dispatching Strategy Considering the Difference of Electric Vehicle Demand." In 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2020. http://dx.doi.org/10.1109/ei250167.2020.9347357.

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8

Marra, F., Guang Ya Yang, E. Larsen, C. N. Rasmussen, and Shi You. "Demand profile study of battery electric vehicle under different charging options." In 2012 IEEE Power & Energy Society General Meeting. New Energy Horizons - Opportunities and Challenges. IEEE, 2012. http://dx.doi.org/10.1109/pesgm.2012.6345063.

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9

Saputra, Yuris Mulya, Dinh Thai Hoang, Diep N. Nguyen, Eryk Dutkiewicz, Markus Dominik Mueck, and Srikathyayani Srikanteswara. "Energy Demand Prediction with Federated Learning for Electric Vehicle Networks." In GLOBECOM 2019 - 2019 IEEE Global Communications Conference. IEEE, 2019. http://dx.doi.org/10.1109/globecom38437.2019.9013587.

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10

Zhong, Weifeng, Rong Yu, Yan Zhang, Jiawen Kang, Haochuan Zhang, and Shengli Xie. "Dynamic demand balance in vehicle-to-grid mobile energy networks." In 2015 IEEE International Conference on Signal Processing for Communications (ICC). IEEE, 2015. http://dx.doi.org/10.1109/icc.2015.7249213.

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Звіти організацій з теми "Vehicle energy demand"

1

Francfort, Jim. Characterize the Demand and Energy Characteristics of Residential Electric Vehicle Supply Equipment. Office of Scientific and Technical Information (OSTI), June 2018. http://dx.doi.org/10.2172/1483581.

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2

Chernyakhovskiy, Ilya, Mohit Joshi, Sika Gadzanku, Sarah Inskeep, and Amy Rose. Opportunities for Renewable Energy, Storage, Vehicle Electrification, and Demand Response in Rajasthan's Power Sector. Office of Scientific and Technical Information (OSTI), September 2022. http://dx.doi.org/10.2172/1891214.

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3

Author, Not Given. Demand and Energy Characteristics of Non-Residential Alternating Current Level 2 Electric Vehicle Supply Equipment. Office of Scientific and Technical Information (OSTI), June 2015. http://dx.doi.org/10.2172/1483601.

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4

Muelaner, Jody. The Challenges of Vehicle Decarbonization. SAE International, April 2022. http://dx.doi.org/10.4271/epr2022se1.

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A narrow focus on electrification and elimination of tailpipe emissions is unlikely to achieve decarbonization objectives. Renewable power generation is unlikely to keep up with increased demand for electricity. A focus on tailpipe emissions ignores the significant particulate pollution that “zero emission” vehicles still cause. It is therefore vital that energy efficiency is improved. Active travel is the key to green economic growth, clean cities, and unlocking the energy saving potential of public transport. The Challenges of Vehicle Decarbonization reviews the urgent need to prioritize active travel infrastructure, create compelling mass-market cycling options, and switch to hybrid powertrains and catenary electrification for long-haul heavy trucks. The report also warns of the potential increase in miles travelled with the advent of personal automated vehicles as well as the pitfalls of fossil-fuel derived hydrogen power.
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5

Sheppard, Colin, Rashid Waraich, Andrew Campbell, Alexei Pozdnukov, and Anand R. Gopal. Modeling plug-in electric vehicle charging demand with BEAM: the framework for behavior energy autonomy mobility. Office of Scientific and Technical Information (OSTI), May 2017. http://dx.doi.org/10.2172/1398472.

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6

Konstantinou, Theodora, Donghui Chen, Konstantinos Flaris, Kyubyung Kang, Dan Daehyun Koo, Jonathon Sinton, Konstantina Gkritza, and Samuel Labi. A Strategic Assessment of Needs and Opportunities for the Wider Adoption of Electric Vehicles in Indiana. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317376.

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The primary objective of this study was to assess the challenges and opportunities associated with the provision of appropriate infrastructure to support electric vehicle (EV) operations and electrification across Indiana. A secondary objective of this study was to develop a strategic plan for INDOT that outlines new business opportunities for developing EV charging stations. To achieve these objectives, the project team assessed current and emerging trends in EV operations, particularly EV charging infrastructure and EV demand forecasting. They also examined opportunities for the strategic deployment of EV charging stations by identifying EV infrastructure deficit areas; investigated the impact of EV adoption on highway revenue and the feasibility of new revenue structures; and evaluated strategic partnerships and business models. The agent-based simulation model developed for future long distance EV trip scenarios enables INDOT to identify EV energy deficient areas for current and future energy charging demand scenarios, and it can support Indiana’s strategic plans for EV charging infrastructure development. The results of the revenue impact analysis can inform INDOT’s revenue model. The estimations of the recovery EV fee, the VMT fee, and pay-as-you-charge fee that break-even the fuel tax revenue loss can be used by INDOT in pilot programs to capture users’ perspectives and estimate appropriate fee rates and structures. The insights obtained from the stakeholder interviews can be used to enhance preparedness for increasing EV adoption rates across vehicle classes and to strengthen the engagement of different entities in the provision of charging infrastructure.
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7

Adams, Sophie, Lisa Diamond, Tara Esterl, Peter Fröhlich, Rishabh Ghotge, Regina Hemm, Ida Marie Henriksen, et al. Social License to Automate: Emerging Approaches to Demand Side Management. IEA User-Centred Energy Systems Technology Collaboration Programme, October 2021. http://dx.doi.org/10.47568/4xr122.

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The Social License to Automate Task has investigated the social dimensions of user engagement with automated technologies in energy systems to understand how end-user trust to automate is built and maintained in different jurisdictions and cultural settings. The rapid uptake of renewable energy systems will require new automated technologies to balance energy supplies. Some developers are looking to locate these in households where energy is being used. This saves moving the energy from centralised generation sites (remote hydro, solar or wind). This report details the findings from a 2 year project with 16 researchers in 6 countries, 26 Case studies spanning electric vehicles, home and precinct batteries, air conditioners and other heat pumps.
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Muelaner, Jody Emlyn. Unsettled Issues in Electrical Demand for Automotive Electrification Pathways. SAE International, January 2021. http://dx.doi.org/10.4271/epr2021004.

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Анотація:
With the current state of automotive electrification, predicting which electrification pathway is likely to be the most economical over a 10- to 30-year outlook is wrought with uncertainty. The development of a range of technologies should continue, including statically charged battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), plug-in hybrid electric vehicles (PHEVs), and EVs designed for a combination of plug-in and electric road system (ERS) supply. The most significant uncertainties are for the costs related to hydrogen supply, electrical supply, and battery life. This greatly is dependent on electrolyzers, fuel-cell costs, life spans and efficiencies, distribution and storage, and the price of renewable electricity. Green hydrogen will also be required as an industrial feedstock for difficult-to-decarbonize areas such as aviation and steel production, and for seasonal energy buffering in the grid. For ERSs, it is critical to understand how battery life will be affected by frequent cycling and the extent to which battery technology from hybrid vehicles can be applied. Unsettled Issues in Electrical Demand for Automotive Electrification Pathways dives into the most critical issues the mobility industry is facing.
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9

Muhsen, Abdelrahman, and Abu Toasin Oakil. Sustainable Transport in Riyadh: Potential Trip Coverage of the Proposed Public Transport Network. King Abdullah Petroleum Studies and Research Center, October 2021. http://dx.doi.org/10.30573/ks--2021-dp17.

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Анотація:
The transport sector has always had high energy demand and is a significant contributor to greenhouse gas (GHG) emissions and climate change. To improve energy efficiency and reduce GHG emissions, Riyadh is introducing an integrated public transport system. Per capita energy consumption is much lower for public transport than for private vehicles, such as cars and taxis. This study investigates the potential impact of Riyadh’s proposed public transport system on car and taxi trips.
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10

Muhsen, Abdelrahman, and Abu Toasin Oakil. Sustainable Transport in Riyadh: Potential Trip Coverage of the Proposed Public Transport Network. King Abdullah Petroleum Studies and Research Center, October 2021. http://dx.doi.org/10.30573/ks--2021-dp17.

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Анотація:
The transport sector has always had high energy demand and is a significant contributor to greenhouse gas (GHG) emissions and climate change. To improve energy efficiency and reduce GHG emissions, Riyadh is introducing an integrated public transport system. Per capita energy consumption is much lower for public transport than for private vehicles, such as cars and taxis. This study investigates the potential impact of Riyadh’s proposed public transport system on car and taxi trips.
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