US residential charging potential for electric vehicles

We assess existing and potential charging infrastructure for plug-in vehicles in US households using data from the American Housing Survey and the Residential Energy Consumption Survey. We estimate that less than half of US vehicles have reliable access to a dedicated off-street parking space at an owned residence where charging infrastructure could be installed. Specifically, while approximately 79% households have off-street parking for at least some of their vehicles, only an estimated 56% of vehicles have a dedicated off-street parking space – and only 47% at an owned residence. Approximately 22% vehicles currently have access to a dedicated home parking space within reach of an outlet sufficient to recharge a small plug-in vehicle battery pack overnight. Access to faster charging, required for vehicles with longer electric range, will usually require infrastructure investment ranging from several hundred to several thousand dollars, depending on panel and construction requirements. We discuss sensitivity of results to uncertain factors and implications for the potential of mainstream penetration of plug-in vehicles.     

Electric vehicles in multi-vehicle households

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.     

Exhaust emissions generated under actual operating conditions from a hybrid vehicle and an electric one fitted with a range extender

The paper describes exhaust emission tests performed on a PHEV (Plug-in Hybrid Electric Vehicle) and a BEV (Battery Electric Vehicle), in which the combustion engine was used as a range extender. The measurements of the exhaust emissions were performed for CO₂/fuel consumption, CO, THC and NO_x. The RDE measurements were performed including the engine operating parameters and emissions analysis. This analysis shows that the engines of BEVs and PHEVs operate in a different parameter range when under actual operating conditions, which directly translates into the exhaust emission values. This is particularly the case for the emission of NO_x. The investigations were carried out for two routes differentiated by the length and share of the urban and extra-urban cycles. For both routes, the emission of THC and CO were lower for the PHEV engine – HC by 69% (22 mg/km, route 1) and 6% (15 mg/km, route 2), CO by 69% (0.12 mg/km, route 1) and 80% (0.1 mg/km, route 2). For route 1, characterized by a greater share of the urban cycle, the emission of NO_x was lower by 70% (2 mg/km) for the BEV engine, and (route 2) lower by 60% (8 mg/km) for the PHEV engine. Additionally, the curves of the exhaust emissions in time for individual exhaust components have been presented that indicate that in the motorway cycle the emission of THC and CO from the BEV vehicle increases significantly up to ten times compared to urban cycle.     

Modelling market diffusion of electric vehicles with real world driving data – German market and policy options

Plug-in electric vehicles (PEVs) have the potential to reduce green house gas emissions from the transport sector. However, the limited electric range of PEVs could impede their market introduction. Still some potential users are willing to pay more for PEVs. The combined effect of these and other influencing factors as well as the resulting future market evolution are unclear. Here, we study the market evolution of PEVs in Germany until 2020. Our results reveal a great deal of uncertainty in the market evolution of PEVs due to external conditions and the users’ willingness to pay. We find the future share of PEVs in German passenger car stock to range from 0.4% to almost 3% by 2020. Energy prices have a large impact on PEV market evolution as a 25% increase in fuel prices would double the number of PEVs in stock by 2020 compared to a reference scenario. We find a special depreciation allowance for commercial vehicles and a subsidy of 1000 Euro as the most effective and efficient monetary policy options. The high uncertainty of the market evolution implies that policies to foster market diffusion of PEVs should be dynamically adaptable to react to changing framework conditions.     

A network-based dispatch model for evaluating the spatial and temporal effects of plug-in electric vehicle charging on GHG emissions

The well-to-wheel emissions associated with plug-in electric vehicles (PEVs) depend on the source of electricity and the current non-vehicle demand on the grid, thus must be evaluated via an integrated systems approach. We present a network-based dispatch model for the California electricity grid consisting of interconnected sub-regions to evaluate the impact of growing PEV demand on the existing power grid infrastructure system and energy resources. This model, built on a linear optimization framework, simultaneously considers spatiality and temporal dynamics of energy demand and supply. It was successfully benchmarked against historical data, and used to determine the regional impacts of several PEV charging profiles on the current electricity network. Average electricity carbon intensities for PEV charging range from 244 to 391 gCO₂e/kW h and marginal values range from 418 to 499 gCO₂e/kW h.     

A network wide simulation strategy of alternative fuel vehicles

This paper presents an integrated simulator “CUIntegration” to evaluate routing strategies based on energy and/or traffic measures of effectiveness for any Alternative Fuel Vehicles (AFVs). The CUIntegration can integrate vehicle models of conventional vehicles as well as AFVs developed with MATLAB-Simulink, and a roadway network model developed with traffic microscopic simulation software VISSIM. The architecture of this simulator is discussed in this paper along with a case study in which the simulator was utilized for evaluating a routing strategy for Plug-in Hybrid Electric Vehicles (PHEVs) and Electric Vehicles (EVs). The authors developed a route optimization algorithm to guide an AFV based on that AFV driver’s choice, which included; finding a route with minimum (1) travel time, (2) energy consumption or (3) a combination of both. The Application Programming Interface (API) was developed using Visual Basic to simulate the vehicle models/algorithms developed in MATLAB and direct vehicles in a roadway network model developed in VISSIM accordingly. The case study included a section of Interstate 83 in Baltimore, Maryland, which was modeled, calibrated and validated. The authors considered a worst-case scenario with an incident on the main route blocking all lanes for 30 min. The PHEVs and EVs were represented by integrating the MATLAB-Simulink vehicle models with the traffic simulator. The CUIntegration successfully combined vehicle models with a roadway traffic network model to support a routing strategy for PHEVs and EVs. Simulation experiments with CUIntegration revealed that routing of PHEVs resulted in cost savings of about 29% when optimized for the energy consumption, and for the same optimization objective, routing of EVs resulted in about 64% savings.     

插电式混合动力四轮驱动SUV控制策略研究

基于无级变速可插电混合动力四轮驱动SUV系统,对其运行模式及控制策略进行研究分析,并基于MATLAB/SIMULIk/stateflow建立了整车的控制策略模型,利用Mototron快速原型开发工具对其策略进行实车验证,结果表明:该控制策略下,整车模式切换平顺,混合动力模式下城市工况下节油超过25%。     

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.     

Rapid estimation of electric vehicle acceptance using a general description of driving patterns

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.     

插电式混合动力汽车的油耗和电耗

为检测可外接充电的混合动力电动汽车的油耗和电耗,文章分别按最高荷电和最低荷电2种状态条件,在汽车排放试验室的底盘测功机上进行试验,分别测出这2种状态下的CO,CO2,HC排放量和电能消耗量.利用测得的CO,CO2,HC排放量,以碳平衡法计算这2种状态下的燃料消耗量.假设储能装置2次充电之间的平均行驶里程为25 km,通过加权平均值的计算,得出混合动力电动汽车的油耗和电耗.