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1.
Electric vehicles (EVs) have been regarded as effective options for solving the environmental and energy problems in the field of transportation. However, given the limited driving range and insufficient charging stations, searching and selecting charging stations is an important issue for EV drivers during trips. A smart charging service should be developed to help address the charging issue of EV drivers, and a practical algorithm for charging guidance is required to realise it. This study aims to design a geometry-based algorithm for charging guidance that can be effectively applied in the smart charging service. Geographic research findings and geometric approaches are applied to design the algorithm. The algorithm is practical because it is based on the information from drivers’ charging requests, and its total number of calculations is significantly less than that of the conventional shortest-first algorithm. The algorithm is effective because it considers the consistency of direction trend between the charging route and the destination in addition to the travel distance, which conforms to the travel demands of EV drivers. Moreover, simulation examples are presented to demonstrate the proposed algorithm. Results of the proposed algorithm are compared with those of the other two algorithms, which show that the proposed algorithm can obtain a better selection of charging stations for EV drivers from the perspective of entire travel chains and take a shorter computational time. 相似文献
2.
Increasingly, experts are forecasting the future of transportation to be shared, autonomous and electric. As shared autonomous electric vehicle (SAEV) fleets roll out to the market, the electricity consumed by the fleet will have significant impacts on energy demand and, in turn, drive variation in energy cost and reliability, especially if the charging is unmanaged. This research proposes a smart charging (SC) framework to identify benefits of active SAEV charging management that strategically shifts electricity demand away from high-priced peak hours or towards renewable generation periods. Time of use (TOU), real time pricing (RTP), and solar generation electricity scenarios are tested using an agent-based simulation to study (1) the impact of battery capacity and charging infrastructure type on SAEV fleet performance and operational costs under SC management; (2) the cost reduction potential of SC considering energy price fluctuation, uncertainty, and seasonal variation; (3) the charging infrastructure requirements; and (4) the system efficiency of powering SAEVs with solar generation. A case study from the Puget Sound region demonstrates the proposed SC algorithm using trip patterns from the regional travel demand model and local energy prices. Results suggest that in the absence of electricity price signals, SAEV charging demand is likely to peak the evening, when regional electricity use patterns already indicate high demand. Under SC management, EVs with larger battery sizes are more responsive to low-electricity cost charging opportunities, and have greater potential to reduce total energy related costs (electricity plus charging infrastructure) for a SAEV fleet, especially under RTP structure. 相似文献
3.
Early adopters promoting electric vehicles in their social network may speed up market uptake of this technology. Apart from their opinion leader status, few previous research details the motivations which turn early adopters into advocates for innovation who approach the non-adopters among their family and friends, or casual acquaintances.Drawing on a survey among 1398 e-bike and 133 e-scooter early adopters in Austria, personal drivers of engagement in interpersonal diffusion are investigated. Longitudinal data one year later for 157 e-bike users allows tests of causal relations. A complementary sample of 33 network peers illustrates the early adopters’ social impact.Early adopters engage actively in discussing product features, instigating trial behavior and recommending purchase. Analyses by structural equation modeling show that efforts at interpersonal diffusion are driven by opinion leadership, experienced product performance, and perceived normative expectations of others toward pro-environmental technologies. Mediator and moderator analyses underline that opinion leadership is conveyed upon early adopters because personal norms and technophilia qualify them as credible and competent for the specific topic of e-vehicles. Social norm interrelations point to dynamic interactions and discourse between early adopters and their addressees. Evidence from the peer sample suggests though that the persuasive impact of early adopters is small.To accelerate market entry of electric vehicles, public or private agencies should foremost approach early adopters scoring high in the identified drivers, and empower them in their role as multiplicators by providing pre-prepared product information and encouraging them to continuously address peers. 相似文献
4.
The suitability of an electric vehicle of a given range to serve in place of a given conventional vehicle is not limited by the daily travel over distances within that that range, but rather by the occasional inconvenience of finding alternative transport for longer trips. While the frequency of this inconvenience can be computed from usage data, the willingness of individual users to accept that replacement depends on details of available transportation alternatives and their willingness to use them. The latter can be difficult to assess. Fortunately, 65% of US households have access to the most convenient alternative possible: a second car. In this paper we describe an analysis of prospective EV acceptance and travel electrification in two-car households in the Puget Sound region. We find that EVs with 60 miles of useful range could be acceptable (i.e. incur inconvenience no more than three days each year) to nearly 90% of two-car households and electrify nearly 55% of travel in those households (32% of all travel). This compares to 120 miles range required to achieve the same fraction of electrified travel via one-for-one replacement of individual vehicles. Even though only one third of personal vehicles in the US may be replaced in this paradigm, the ‘EV as a second-car’ concept is attractive in that a significant fraction of travel can be electrified by vehicles with modest electric range and virtually no dependence on public charging infrastructure. 相似文献
5.
A reliable estimate of the potential for electrification of personal automobiles in a given region is dependent on detailed understanding of vehicle usage in that region. While broad measures of driving behavior, such as annual miles traveled or the ensemble distribution of daily travel distances are widely available, they cannot be predictors of the range needs or fuel-saving potential that influence an individual purchase decision. Studies that record details of individual vehicle usage over a sufficient time period are available for only a few regions in the US. In this paper we compare statistical characterization of four such studies (three in the US, one in Germany) and find remarkable similarities between them, and that they can be described quite accurately by properly chosen set of distributions. This commonality gives high confidence that ensemble data can be used to predict the spectrum of usage and acceptance of alternative vehicles in general. This generalized representation of vehicle usage may also be a powerful tool in estimating real-world fuel consumption and emissions. 相似文献
6.
Previous research has shown that electric vehicle (EV) users could behave differently compared to internal combustion engine vehicle (ICEV) drivers due to their consciousness or practices of eco-driving, but very limited research has fully investigated this assumption. This research explores this topic through investigating EV drivers’ eco-driving behaviors and motivations. We first conducted a questionnaire survey on EV drivers’ driving behavior and some hypothetical decisions of their driving. It indicates various characteristics between EV and ICEV commuters, including self-reported daily driving habits, preferences of route choices, tradeoff between travel time and energy saving, and adoption of in-vehicle display (IVD) technologies. Then, through statistical analysis with Fisher’s exact test and Mann-Whitney U test, this research reveals that, compared to ICEV drivers, EV drivers possess significantly calmer driving maneuvers and more fuel-efficient driving habits such as trip chaining. The survey data also show that EV drivers are much more willing to save energy in compensation of travel time. Furthermore, the survey data indicate that EV drivers are more willing to adopt eco-friendly IVD technologies. All these findings are expected to improve the understanding of some unique behavior found in EV drivers. 相似文献
7.
The spread of electric vehicles (EVs) and their increasing demand for electricity has placed a greater burden on electricity generation and the power grid. In particular, the problem of whether to expand the electricity power stations and distribution facilities due to the construction of EV charging stations is emerging as an immediate issue. To effectively meet the demand for additional electricity while ensuring the stability of the power grid, there is a need to accurately predict the charging demands for EVs. Therefore, this study estimates the changes in electricity charging demand based on consumer preferences for EVs, charging time of day, and types of electric vehicle supply equipment (EVSE) and elucidates the matters to be considered for constructing EV infrastructure. The results show that consumers mainly preferred charging during the evening. However, when we considered different types of EVSEs (public and private) in the analysis, people preferred to charge at public EVSEs during the day. During peak load time, people tended to prefer charging using fast public EVSEs, which shows that consumers considered the tradeoffs between the full charge time and the price for charging. Based on these findings, this study provides key political implications for policy makers to consider in taking preemptive measures to adjust the electricity supply infrastructure. 相似文献
8.
The market share of Electric Vehicles (EVs), an attractive alternative to conventional vehicles, is expected to exceed 30% of all vehicles by 2033 in Australia. Although the expected EV uptake may place greater burdens on electricity networks, the potential impacts contributed by different EV user categories and vehicle models to peak loads at different times during the day are not well understood. This paper addresses the issue through statistical analysis of the charge events in the Victorian EV Trial in Australia as well as modeling the charging behaviors according to participant categories and vehicle models. The analysis was performed on 4933 charge events that were recorded by both private and public Electric Vehicle Supply Equipment. In total, these events consumed over 33 MW h of energy over 12,170 h by the 178 trial participants, out of which about 70% were household participants while the others were fleet participants. Based on a range of EV uptake scenarios and modeled charging behaviors from the trial, the power demand in the summer of 2032/33 was estimated for all of Victoria. The results of the simulations show that the broad scale uptake of EVs produces a relatively small increase in overall power demand (estimated to be between 5.72% and 9.79% in 2032/33). 相似文献
9.
In view of global warming and climate change, a transition from combustion to electric vehicles (EVs) can help to reduce greenhouse gas emissions and improve air quality. However, high acquisition costs and short driving ranges are considered to be main factors which impede the diffusion of EVs. Since electricity needs to be produced from renewable energy sources for EVs to be a true green alternative, the environmental performance of EVs is also presumed to be an important factor. This paper investigates the role of environmental performance compared to price value and range confidence regarding consumer purchase intentions for EVs. To develop our hypothesis, we interview 40 end-user subjects about their beliefs toward EVs. Then, we perform 167 test drives with a plug-in battery EV and conduct a survey with the participants to test the hypothesis. Results of a structural equation modeling support the hypothesis that the environmental performance of EVs is a stronger predictor of attitude and thus purchase intention than price value and range confidence. 相似文献
10.
This research evaluated the potential for wireless dynamic charging (charging while moving) to address range and recharge issues of modern electric vehicles by considering travel to regional destinations in California. A 200-mile electric vehicle with a real range of 160 miles plus 40 miles reserve was assumed to be used by consumers in concert with static and dynamic charging as a strict substitute for gasoline vehicle travel. Different combinations of wireless charging power (20–120 kW) and vehicle range (100–300 miles) were evaluated. One of the results highlighted in the research indicated that travel between popular destinations could be accomplished with a 200-mile EV and a 40 kW dynamic wireless charging system at a cost of about $2.5 billion. System cost for a 200-mile EV could be reduced to less than $1 billion if wireless vehicle charging power levels were increased to 100 kW or greater. For vehicles consuming 138 kWh of dynamic energy per year on a 40 kW dynamic system, the capital cost of $2.5 billion plus yearly energy costs could be recouped over a 20-year period at an average cost to each vehicle owner of $512 per year at a volume of 300,000 vehicles or $168 per year at a volume of 1,000,000 vehicles. Cost comparisons of dynamic charging, increased battery capacity, and gasoline refueling were presented. Dynamic charging, coupled with strategic wayside static charging, was shown to be more cost effective to the consumer over a 10-year period than gasoline refueling at $2.50 or $4.00 per gallon. Notably, even at very low battery prices of $100 per kWh, the research showed that dynamic charging can be a more cost effective approach to extending range than increasing battery capacity. 相似文献
11.
Considering the depletion of fossil fuels and the environmental impact of transport, reducing the use of such fuels is a globally accepted priority. Thus, when moving towards alternative energy types, the first will undoubtedly be electrical energy. In order to accelerate and contribute to this process, electric vehicles (EV) must be preferred over conventional motor vehicles. However, there are various problems associated with the use of EVs, such as range and recharge status. Optimal planning of electric vehicle charging stations (EVCS) is a solution to these problems. For this purpose, parameters affecting EVCS locations have been determined in the paper. Considering these parameters and the current EVCS locations, the most suitable alternative EVCS locations were identified using Geographical Information Systems (GIS). Both the current and alternative EVCS locations were evaluated by Analytic Hierarchy Process (AHP), Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE), and VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) from multi-criteria decision-making (MCDM) methods. The results show that, in Istanbul, the southeast of the European side and the southwest of the Anatolian side were most suitable for EVCS. 相似文献
12.
Shared autonomous vehicles, or SAVs, have attracted significant public and private interest because of their opportunity to simplify vehicle access, avoid parking costs, reduce fleet size, and, ultimately, save many travelers time and money. One way to extend these benefits is through an electric vehicle (EV) fleet. EVs are especially suited for this heavy usage due to their lower energy costs and reduced maintenance needs. As the price of EV batteries continues to fall, charging facilities become more convenient, and renewable energy sources grow in market share, EVs will become more economically and environmentally competitive with conventionally fueled vehicles. EVs are limited by their distance range and charge times, so these are important factors when considering operations of a large, electric SAV (SAEV) fleet.This study simulated performance characteristics of SAEV fleets serving travelers across the Austin, Texas 6-county region. The simulation works in sync with the agent-based simulator MATSim, with SAEV modeling as a new mode. Charging stations are placed, as needed, to serve all trips requested (under 75 km or 47 miles in length) over 30 days of initial model runs. Simulation of distinctive fleet sizes requiring different charge times and exhibiting different ranges, suggests that the number of station locations depends almost wholly on vehicle range. Reducing charge times does lower fleet response times (to trip requests), but increasing fleet size improves response times the most. Increasing range above 175 km (109 miles) does not appear to improve response times for this region and trips originating in the urban core are served the quickest. Unoccupied travel accounted for 19.6% of SAEV mileage on average, with driving to charging stations accounting for 31.5% of this empty-vehicle mileage. This study found that there appears to be a limit on how much response time can be improved through decreasing charge times or increasing vehicle range. 相似文献
13.
Upward expectations of future electric vehicle (EV) growth pose the question about the future load on the electricity grid. While existing literature on EV charging demand management has focused on technical aspects and considered EV-owners as utility maximizers, this study proposes a behavioural model incorporating psychological aspects relevant to EV-owners facing charging decisions and interacting with the supplier. The behavioural model represents utility maximization under myopic loss aversion (MLA) within an ultimatum game (UG) framework where the two players are the EV-owner and the electricity supplier. Experimental economics allowed testing the validity of the behavioural model by designing three experiments where a potential EV-owner faces three decisions (i.e., to postpone EV charging to off-peak periods for a discount proposed by the supplier, the amount of discount to request for off-peak charging at times decided by the supplier, and the amount of discount to accept for supplier-controlled charging) under two contract durations (i.e., short-term, long-term). Findings from the experiments show that indeed potential EV-owners perform charging decisions while being affected by MLA resulting from monetary considerations and the UG participation, and that presenting long-term contracts help potential EV-owners to curtail MLA behaviour and minimise cost even though the assumption of utility maximization is violated. 相似文献
14.
In this study several hypotheses comprising a heuristic framework derived from rational-choice (RC) premises and regarding some potentially influencing variables on future use intention of different vehicle types are tested with a rural area sample. Especially the differentiation between long-term vs. short-term as well as functional/rational vs. extra-functional/emotional motivators is assessed. Results suggest a predominance of functional motivators and rational connotations over extra-functional/emotional ones. The models to check whether short-term or long-term effects dominate did not clearly confirm a predominance of long-term factors as hypothesized. In several regression models a moderating effect of rational short-term connotations on different long-term motivators was found, thus contributing notably to the prediction of future vehicle use-intention. The need for further research and theory-driven modeling is briefly discussed. 相似文献
15.
Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design details, with applications that reflect the costs of installing, operating, and maintaining service equipment, including land acquisition. Fast electric vehicle charging stations (EVCSs) are placed across a congested city's network subject to stochastic demand for charging under a user-equilibrium traffic assignment. BEV users’ station choices consider endogenously determined travel times and on-site charging queues. The model allows for congested-travel and congested-station feedback into travelers’ route choices under elastic demand and BEV owners’ station choices, as well as charging price elasticity for BEV charging users.Boston-network results suggest that EVCSs should locate mostly along major highways, which may be a common finding for other metro settings. If 10% of current EV owners seek to charge en route, a user fee of $6 for a 30-min charging session is not enough for station profitability under a 5-year time horizon in this region. However, $10 per BEV charging delivers a 5-year profit of $0.82 million, and 11 cords across 3 stations are enough to accommodate a near-term charging demand in this Boston-area application. Shorter charging sessions, higher fees, and/or allowing for more cords per site also increase profits generally, everything else constant. Power-grid and station upgrades should keep pace with demand, to maximize profits over time, and avoid on-site congestion. 相似文献
16.
The integration of electric vehicles (EVs) will affect both electricity and transport systems and research is needed on finding possible ways to make a smooth transition to the electrification of the road transport. To fully understand the EV integration consequences, the behaviour of the EV drivers and its impact on these two systems should be studied. This paper describes an integrated simulation-based approach, modelling the EV and its interactions in both road transport and electric power systems. The main components of both systems have been considered, and the EV driver behaviour was modelled using a multi-agent simulation platform. Considering a fleet of 1000 EV agents, two behavioural profiles were studied (Unaware/Aware) to model EV driver behaviour. The two behavioural profiles represent the EV driver in different stages of EV adoption starting with Unaware EV drivers when the public acceptance of EVs is limited, and developing to Aware EV drivers as the electrification of road transport is promoted in an overall context. The EV agents were modelled to follow a realistic activity-based trip pattern, and the impact of EV driver behaviour was simulated on a road transport and electricity grid. It was found that the EV agents’ behaviour has direct and indirect impact on both the road transport network and the electricity grid, affecting the traffic of the roads, the stress of the distribution network and the utilization of the charging infrastructure. 相似文献
17.
This paper develops empirical models for evaluating the service quality (SQ) of paratransit. Specifically, several models are developed based on structural equation modeling (SEM) using twenty-four SQ variables. To calibrate those models, a data set of 2008 paratransit users of Dhaka City are utilized, who were interviewed with a structured questionnaire to know their experience, level of satisfaction and opinion about the existing service as well as their expectations. SEM reveals the observed and latent SQ variables and their relationship with the overall SQ of paratransit. Among the different models developed, the best one is selected using statistical parameters and resemblance with real life expectations. Out of twenty-four SQ variables, ‘Punctuality and Reliability’ and ‘Service Features’ are respectively found to be the observed and latent variables having the greatest influence on the paratransit SQ. Moreover, the effect of heterogeneity among users on the performance of the best model is investigated. All the study findings support the data collected from the paratransit users. The research outcomes can be utilized by the city transportation officials of developing countries to improve the overall paratransit performance to attract new users as well as retain the current ones. 相似文献
18.
Inductive charging, a form of wireless charging, uses an electromagnetic field to transfer energy between two objects. This emerging technology offers an alternative solution to users having to physically plug in their electric vehicle (EV) to charge. Whilst manufacturers claim inductive charging technology is market ready, the efficiency of transfer of electrical energy is highly reliant on the accurate alignment of the coils involved. Therefore understanding the issue of parking misalignment and driver behaviour is an important human factors question, and the focus of this paper. Two studies were conducted, one a retrospective analysis of 100 pre-parked vehicles, the second a dynamic study where 10 participants parked an EV aiming to align with a charging pad with no bay markings as guidance. Results from both studies suggest that drivers are more accurate at parking laterally than in the longitudinal direction, with a mean lateral distance from the centre of the bay being 12.12 and 9.57 cm (retrospective and dynamic studies respectively) compared to longitudinally 23.73 and 73.48 cm. With current inductive charging systems having typical tolerances of approximately ±10 cm from their centre point, this study has shown that only 5% of vehicles in both studies would be aligned sufficiently accurately to allow efficient transfer of electrical energy through induction. 相似文献
19.
Discrete choice modeling is experiencing a reemergence of research interest in the inclusion of latent variables as explanatory variables of consumer behavior. There are several reasons that motivate the integration of latent attributes, including better-informed modeling of random consumer heterogeneity and treatment of endogeneity. However, current work still is at an early stage and multiple simplifying assumptions are usually imposed. For instance, most previous applications assume all of the following: independence of taste shocks and of latent attributes, exclusion restrictions, linearity of the effect of the latent attributes on the utility function, continuous manifest variables, and an a priori bound for the number of latent constructs. We derive and apply a structural choice model with a multinomial probit kernel and discrete effect indicators to analyze continuous latent segments of travel behavior, including inference on the energy paradox. Our estimator allows for interaction and simultaneity among the latent attributes, residual correlation, nonlinear effects on the utility function, flexible substitution patterns, and temporal correlation within responses of the same individual. Statistical properties of the Bayes estimator that we propose are exact and are not affected by the number of latent attributes. 相似文献
20.
A new facility location model and a solution algorithm are proposed that feature (1) itinerary-interception instead of flow-interception; (2) stochastic demand as dynamic service requests; and (3) queueing delay. These features are essential to analyze battery-powered electric shared-ride taxis operating in a connected, centralized dispatch manner. The model and solution method are based on a bi-level, simulation–optimization framework that combines an upper level multiple-server allocation model with queueing delay and a lower level dispatch simulation based on earlier work by Jung and Jayakrishnan. The solution algorithm is tested on a fleet of 600 shared-taxis in Seoul, Korea, spanning 603 km2, a budget of 100 charging stations, and up to 22 candidate charging locations, against a benchmark “naïve” genetic algorithm that does not consider cyclic interactions between the taxi charging demand and the charger allocations with queue delay. Results show not only that the proposed model is capable of locating charging stations with stochastic dynamic itinerary-interception and queue delay, but that the bi-level solution method improves upon the benchmark algorithm in terms of realized queue delay, total time of operation of taxi service, and service request rejections. Furthermore, we show how much additional benefit in level of service is possible in the upper-bound scenario when the number of charging stations is unbounded. 相似文献