Impact of government incentives on the market penetration of electric vehicles in Australia

Incentives to buy and use electric vehicles (EVs) may influence individuals’ decisions to do so. To examine these impacts, a latent class discrete choice model is developed to analyse consumer preferences related to EV attributes and related government incentives. Data was collected from a stated preference survey of 1,076 residents of New South Wales (NSW), Australia. According to the results, the proposed latent constructs classify respondents into five segments. The segments are then used to distinguish respondent behaviours regarding EV attributes and related government incentives. The results show that rebate on the upfront cost of an EV is the most preferred one-off financial incentive, because EVs are expected to be expensive, especially in Australia which has a very small EV market at present. Furthermore, rebates on energy bills and parking fees are also well-received, as these things are expensive in Sydney, Australia. Thus, operational incentives for discounts on energy bills and parking fees may facilitate the success of EVs in NSW.     

A long panel survey to elicit variation in preferences and attitudes in the choice of electric vehicles

This paper describes the methodology we set up to gather appropriate data to study the impact of real life experience with electric vehicles (EVs) over a relatively long period of time on individual preferences and attitudes. We used stated choices (SC) to elicit individual preferences because EVs and their associated charging infrastructure are not yet fully integrated onto the market. Furthermore, to measure the extent to which the experience of using an EV may affect individual preferences and attitudes, we set up a “long panel” survey, where data was gathered before and after individuals experienced an EV in real life during a three-month period. We also measured attitudinal effects (AE) that might affect the choice of an EV by individuals. To our knowledge, this represents the first example of a “long panel” SC/AE and the first attempt to measure the formation of preferences and attitudes for this emerging product. Our results show that preferences and attitudes are indeed affected by real life experience. In the SC experiment, the respondents only chose the EV half as often as compared to the situation where they had not yet tried it. Furthermore, we measured a change in attitude for statements regarding the use of EVs. On the whole, respondents got a more positive view of the EV driving performance and this change is significantly greater for women than for men. However, respondents expressed more concern about being able to maintain current mobility with an EV. The data gathered in this survey should also serve to analyse the changes generated by direct experience with EVs, and eventually to formulate and estimate advanced discrete choice models that allow insights into factors relevant for improved understanding of market behaviour.     

Who will buy electric vehicles? Identifying early adopters in Germany

Electric vehicles (EVs) have noteworthy potential to reduce global and local emissions and are expected to become a relevant future market for vehicle sales. Both policy makers and car manufacturers have an interest to understand the first large EV user group, frequently referred to as ‘early adopters’. However, there are only a few empirical results available for this important group. In this paper, we analyse and discuss several empirical data sets from Germany, characterising this user group from both a user and a product perspective, i.e. who is willing to buy an EV and who should buy one. Our results show that the most likely group of private EV buyers in Germany are middle-aged men with technical professions living in rural or suburban multi-person households. They own a large share of vehicles in general, are more likely to profit from the economical benefits of these vehicles due to their annual vehicle kilometres travelled and the share of inner-city driving. They state a higher willingness to buy electric vehicles than other potential adopter groups and their higher socio-economic status allows them to purchase EVs. In contrast to this, inhabitants of major cities are less likely to buy EVs since they form a small group of car owners in general, their mileage is too low for EVs to pay off economically and they state lower interest and lower willingness to pay for EVs than other groups. Our results indicate that transport policy promoting EVs should focus on middle-aged men with families from rural and sub-urban cities as first private EV buyers.     

The relative importance of price and driving range on electric vehicle adoption: Los Angeles case study

Electric vehicles (EVs) are still a maturing technology. Barriers to their adoption include price and range anxiety. EV batteries are significant in determining both EV prices and costs. In this work, we focus on the impact of a high-capacity battery and EV rebates on an EV ecosystem. Using survey data from Los Angeles, California, we simulate different cases of battery costs and prices by means of an agent-based EV ecosystem model. We find that even in Los Angeles, a geographically spread out city, the price of EVs is a more significant barrier to adoption than EV range. In fact, even a quintupling of battery size at no additional costs improves EV adoption by only 5 %. Therefore, policy makers should focus more on affordability than range in promoting EV adoption.     

Optimal recharging strategies for electric vehicle fleets with duration constraints

Electrical vehicles (EVs) have become a popular green transportation means recently because they have lower energy consumption costs and produce less pollution. The success of EVs relies on technologies to extend their driving range, which can be achieved by the good deployment of EV recharging stations. This paper considers a special EV network composed of fixed routes for an EV fleet, where each EV moves along its own cyclic tour of depots. By setting up a recharging station on a depot, an EV can recharge its battery for no longer than a pre-specified duration constraint. We seek an optimal deployment of recharging stations and an optimal recharging schedule for each EV such that all EVs can continue their tours in the planning horizon with minimum total costs. To solve this difficult location problem, we first propose a mixed integer program (MIP) formulation and then derive four new valid inequalities to shorten the solution time. Eight MIP models, which were created by adding different combinations of the four valid inequalities to the basic model, have been implemented to test their individual effectiveness and synergy over twelve randomly generated EV networks. Valuable managerial insights into the usage of valid inequalities and the relations between the battery capacity and the total costs, number of recharging facilities to be installed, and running time are analyzed.     

Electric vehicles’ energy consumption measurement and estimation

Use of electric vehicles (EVs) has been viewed by many as a way to significantly reduce oil dependence, operate vehicles more efficiently, and reduce carbon emissions. Due to the potential benefits of EVs, the federal and local governments have allocated considerable funding and taken a number of legislative and regulatory steps to promote EV deployment and adoption. With this momentum, it is not difficult to see that in the near future EVs could gain a significant market penetration, particularly in densely populated urban areas with systemic air quality problems. We will soon face one of the biggest challenges: how to improve efficiency for EV transportation system? This research takes the first step in tackling this challenge by addressing a fundamental issue, i.e. how to measure and estimate EVs’ energy consumption. In detail, this paper first presents a system which can collect in-use EV data and vehicle driving data. This system then has been installed in an EV conversion vehicle built in this research as a test vehicle. Approximately 5 months of EV data have been collected and these data have been used to analyze both EV performance and driver behaviors. The analysis shows that the EV is more efficient when driving on in-city routes than driving on freeway routes. Further investigation of this particular EV driver’s route choice behavior indicates that the EV user tries to balance the trade-off between travel time and energy consumption. Although more data are needed in order to generalize this finding, this observation could be important and might bring changes to the traffic assignment for future transportation system with a significant share of EVs. Additionally, this research analyzes the relationships among the EV’s power, the vehicle’s velocity, acceleration, and the roadway grade. Based on the analysis results, this paper further proposes an analytical EV power estimation model. The evaluation results using the test vehicle show that the proposed model can successfully estimate EV’s instantaneous power and trip energy consumption. Future research will focus on applying the proposed EV power estimation model to improve EVs’ energy efficiency.     

Testing electric vehicle demand in ‘hybrid households’ using a reflexive survey

The debate over electric vehicles (EVs) pivots largely on issues of market demand: will consumers purchase a vehicle that provides substantially less driving range, yet can be refueled at home, than an otherwise comparable gasoline vehicle? Also, what role do other unique attributes of EVs play in the purchase decision? Most previous studies find that limited driving range is a serious market barrier; many of those same studies ignore or under-value other novel attributes. To probe these future consumer decision processes deeply and robustly, we first devised and conducted detailed, interactive and experiment-oriented interviews. Then, incorporating what we learned, we designed an innovative mail survey and administered it to 454 multi-car households in California. The four-stage mail survey included a video of EV use and recharging and other informational material, completion of a 3-day trip diary and map of activity locations, and vehicle choice experiments. In addition to propulsion systems, respondents made choices of body styles, driving ranges, and other features. We formalized and tested what we call the hybrid household hypothesis: households who choose EVs will be purposefully diversifying their vehicle holdings to achieve the unique advantages of different propulsion systems. The hypothesis is supported, given the assumptions in our experimental design. In fact, a significantly larger number of EVs are chosen than the minimum number that would support our hypothesis. We find that purchases of battery-powered EVs by hybrid households would account for between 7 and 18% of annual light duty vehicle sales in California. EVs sold to fleets and other households would be in addition to those identified by this study.     

Electric vehicles revisited: a review of factors that affect adoption

Electric vehicles (EVs) were recently reintroduced to the global car market. These are an improvement over their predecessors in performance and electric driving range. Although the uptake of EVs has been notable in a short period of time, most government goals for adoption have not been met. This paper reviews a growing body of peer-reviewed literature assessing factors affecting EV adoption. Several important gaps in knowledge are identified. First, there is mixed evidence of the effectiveness of government incentives in encouraging EV uptake and particularly little knowledge in regards to issues of timing and magnitude. The literature shows that public charging infrastructure is an important factor associated with EV uptake, though the direction of causality is yet unclear. Public charging infrastructure can ease range anxiety, particularly for battery electric vehicles, but there is little guidance as to the way in which government should best go about ensuring the provision of infrastructure. Lastly, the nascent EV market means that studies primarily rely on surveys about hypothetical situations. There is strong evidence that actual purchases are much lower than consumers’ stated preferences. Improving understanding of this “attitude–action” gap is important to better informing studies of EV uptake over time.     

Policy effects on charging behaviour of electric vehicle owners and on purchase intentions of prospective owners: Natural and stated choice experiments

Policy makers are looking for effective ways to promote the adoption of electric vehicles (EVs). Among the options is the roll-out and management of charging infrastructure to meet the EV drivers’ refuelling needs. However, policies in this area do not only have a long-term effect on the adoption of EVs among prospective owners, they also have short-term impacts on the usage of public charging infrastructure among current EV owners and vice versa. Presently, studies focusing on both effects simultaneously are lacking, missing out on possible cross-pollination between these areas. This study uniquely combines stated and revealed preference data to estimate the effect of particular policy measures aimed at EV adoption, on the one hand, and charging behaviour, on the other. Using a large dataset (1.7 million charging sessions) related to charging behaviour using public charging infrastructure in the Netherlands we quantify the effects of (i) daytime-parking (to manage parking pressure) and (ii) free parking (to promote purchase of EVs) policies on charging behaviour. To estimate the effects of these particular policies on EV purchase intentions, a stated choice experiment was conducted among potential EV-buyers. Results show that cross-pollinations between EV charging and adaptation policies exist and should be taken into account when designing policies for EV adoption.     

Addressing electric vehicle (EV) sales and range anxiety through parking layout,policy and regulation

Electric Vehicles (EV) are highly beneficial due to their reliance on electricity and Climate Change response yet EV sales are lower than would be expected due to range anxiety. If a potential buyer cannot be assured of having constantly-available and compatible charging stations, they will not purchase an EV. To increase the sales of EVs through improved charger availability, this paper examines parking configurations, charger design, convenient “EV only” parking, free charging, etiquette in unplugging another’s vehicle, and legislation. Data were derived from academic publications, trade market press, conversations, personal observations, and laws. The results show that chargers are often in a lot’s corner and thus accessible only to one vehicle, EV owners leave their charged car in the space, drivers use EV spaces for parking, etiquette cards are not understood, and legislation makes it illegal to unplug another’s EV. Improvements include less convenient charger spots, an octopus charger in the middle of the parking lot, modest charging fees to foster turnover, chargers that indicate an EV is charged, education and legislation about etiquette cards, and legislation that allows an individual to unplug another’s charged EV. Improvements to charging should be implemented simultaneously to lessen range anxiety and realize the environmental benefits from reductions in gasoline consumption and mobile source air pollution.     

Performance measure for reliable travel time of emergency vehicles

Travel time is very critical for emergency response and emergency vehicle (EV) operations. Compared to ordinary vehicles (OVs), EVs are permitted to break conventional road rules to reach the destination within shorter time. However, very few previous studies address the travel time performance of EVs. This study obtained nearly 4-year EV travel time data in Northern Virginia (NOVA) region using 76,000 preemption records at signalized intersections. First, the special characteristics of EV travel time are explored in mean, median, standard deviation and also the distribution, which display largely different characteristics from that of OVs in previous studies. Second, a utility-based model is proposed to quantify the travel time performance of EVs. Third, this paper further investigates two important components of the utility model: benchmark travel time and standardized travel time. The mode of the distribution is chosen as benchmark travel time, and its nonlinear decreasing relationship with the link length is revealed. At the same time, the distribution of standardized travel time is fitted with different candidate distributions and Inv. Gaussian distribution is proved to be the most suitable one. Finally, to validate the proposed model, we implement the model in case studies to estimate link and route travel time performance. The results of route comparisons also show that the proposed model can support EV route choice and eventually improve EV service and operations.     

Routing and charging locations for electric vehicles for intercity trips

This study addresses two problems in the context of battery electric vehicles (EVs) for intercity trips: the EV routing problem and the EV optimal charging station location problem (CSLP). The paper shows that EV routing on the shortest path subject to range feasibility for one origin–destination (O–D) pair, called the shortest walk problem (SWP), as well as a stronger version of the problem – the p-stop limited SWP – can be reduced to solving the shortest path problem on an auxiliary network. The paper then addresses optimal CSLPs in which EVs are range feasible with and without p-stops. We formulate the models as mixed-integer multi-commodity flow problems on the same auxiliary network without path and relay pattern enumeration. Benders decomposition is used to propose an exact solution approach. Numerical experiments are conducted using the Indiana state network.     

Consumer purchase intentions for electric vehicles: Is green more important than price and range?

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.     

Survey of the operation and system study on wireless charging electric vehicle systems

This survey investigates the state-of-the-art in operations and systems-related studies of wireless charging electric vehicles (EVs). The wireless charging EV is one of emerging transportation systems in which the EV’s battery is charged via wireless power transfer (WPT) technology. The system makes use of charging infrastructure embedded under the surface of the road that transfers electric power to the vehicle while it is in transit. The survey focuses on studies related to both dynamic and quasi-dynamic types of wireless charging EV – charging while in motion and while temporarily stopped during a trip, respectively. The ability to charge EVs while in transit has raised numerous operations and systems issues that had not been observed in conventional EVs. This paper surveys the current research on such issues, including decisions on the allocation of charging infrastructure; cost and benefit analyses; billing and pricing; and other supporting operations and facilities. This survey consists of three parts. The first provides an orienting review of terminology specific to wireless charging EVs; it also reviews some past and ongoing developments and implementations of wireless charging EVs. The second part surveys the research on the operations and systems issues prompted by wireless charging EVs. The third part proposes future research directions. The goal of the survey is to provide researchers and practitioners with an overview of research trends and to provide a guide to promising future research directions.     

Consumer attitudes about electric cars: Pricing analysis and policy implications

As electric vehicles (EVs) become more readily available, sales will depend on consumers’ interest and understanding. A survey of consumer attitudes on electric cars was conducted in Manitoba from late 2011 to early 2012. It utilizes two price assessment methods. The van Westendorp price sensitivity method (PSM) shows the acceptable price range for EVs to be $22,000–27,500. This range closely matches average price range for sales of conventional cars during the same period. The willingness-to-pay method reveals consumers are unwilling to pay large premiums for EVs, even when given information on future fuel savings. A consumer group with experience or exposure to EVs is somewhat different. Nearly 25% of these people are willing to pay a premium of up to $10,000. Different interpretations can be drawn from these responses, calling for further research. An apparent policy opportunity involves consumer education to enhance knowledge and facilitate EV purchase decisions. Survey results also support the hypothesis that EV rollout has focused too much on technology, and not enough on consumers.     

Market dynamics and indirect network effects in electric vehicle diffusion

The diffusion of electric vehicles (EVs) is studied in a two-sided market framework consisting of EVs on the one side and EV charging stations (EVCSs) on the other. A sequential game is introduced as a model for the interactions between an EVCS investor and EV consumers. A consumer chooses to purchase an EV or a conventional gasoline alternative based on the upfront costs of purchase, the future operating costs, and the availability of charging stations. The investor, on the other hand, maximizes his profit by deciding whether to build charging facilities at a set of potential EVCS sites or to defer his investments.The solution of the sequential game characterizes the EV-EVCS market equilibrium. The market solution is compared with that of a social planner who invests in EVCSs with the goal of maximizing the social welfare. It is shown that the market solution underinvests EVCSs, leading to slower EV diffusion. The effects of subsidies for EV purchase and EVCSs are also considered.     

A systematic review of route optimisation and pre-emption methods for emergency vehicles

ABSTRACT

Reducing the travel time of emergency vehicles (EVs) is an effective way to improve critical services such as ambulance, fire, and police. Route optimisation and pre-emption are powerful techniques used to reduce EV travel time. This paper presents a systematic literature review of optimisation and pre-emption techniques for routing EVs. A detailed classification of existing techniques is presented along with critical analysis and discussion. The study observes the limitations of existing routing systems and lack of real-world applications of the proposed pre-emption systems, leading to several interesting and important knowledge and implementation gaps that require further investigation. These gaps include optimisations using real-time dynamic traffic data, considering time to travel as a critical parameter within dynamic route planning algorithms, considering advanced algorithms, assessing and minimising the effects of EV routing on other traffic, and addressing safety concerns in traffic networks containing multiple EVs at the same time.     

Consumer preferences for electric vehicles: a literature review

Widespread adoption of electric vehicles (EVs) may contribute to the alleviation of problems such as environmental pollution, global warming and oil dependency. However, the current market penetration of EV is relatively low in spite of many governments implementing strong promotion policies. This paper presents a comprehensive review of studies on consumer preferences for EV, aiming to better inform policy-makers and give direction to further research. First, we compare the economic and psychological approach towards this topic, followed by a conceptual framework of EV preferences which is then implemented to organise our review. We also briefly review the modelling techniques applied in the selected studies. Estimates of consumer preferences for financial, technical, infrastructure and policy attributes are then reviewed. A categorisation of influential factors for consumer preferences into groups such as socio-economic variables, psychological factors, mobility condition, social influence, etc. is then made and their effects are elaborated. Finally, we discuss a research agenda to improve EV consumer preference studies and give recommendations for further research.

Abbreviations: AFV: alternative fuel vehicle; BEV: battery electric vehicle; CVs: conventional vehicles; EVs: electric vehicles; FCV: fuel cell vehicle; HCM: hybrid choice model; HEV: hybrid electric vehicle (non plug-in); HOV: high occupancy vehicle; MNL: MultiNomial logit; MXL: MiXed logit model; PHEV: plug-in hybrid electric vehicle; RP: revealed preference; SP: stated preference.     

Simulation of electric vehicle driver behaviour in road transport and electric power networks

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.