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A recent turbulence in the oil market, as well as the ever-decreasing stocks of fossil fuels, has led to growth of interest in various alternative technologies like automotive hybrid vehicles. Despite the rapid increase of markets of hybrid-electric vehicles, their scope for the Gulf Corporation Council region still needs to be explored further. Awareness about benefits of using hybrid-electric vehicles is fast spreading in the Gulf Corporation Council region and this has positive impacts both in terms of consumer satisfaction and reduction of environmental pollutants. The major aim of presented work is to explore the benefits of using hybrid vehicle technology in terms of savings in cost and reduction in greenhouse gas emissions. Emissions savings were found to be in a range of 9–13%. Fuel savings per 100 km were in a range of 8–10 L. The presented work discusses various issues related to background, features, and components of hybrid vehicles. Trends in the design, energy management, component sizing, energy costs, greenhouse emissions, fuel economy, and performance of these vehicles have been analyzed. Further conclusions and recommendations have been made about these issues keeping in focus market trends in the Gulf Corporation Council region. [ABSTRACT FROM AUTHOR]

This paper demonstrates a new process that has been specifically designed for the support of the U.S. Department of Transportation's (DOT's) Corporate Average Fuel Economy (CAFE) standards. In developing the standards, DOT's National Highway Traffic Safety Administration made use of the CAFE Compliance and Effects Modeling System (the 'Volpe model' or the 'CAFE model'), which was developed by DOT's Volpe National Transportation Systems Center for the 2005-2007 CAFE rulemaking and has been continuously updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer's fleet until the requirements under consideration are met. The Volpe model relies on numerous technology-related and economic inputs, such as market forecasts, technology costs, and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology 'decision trees'. Part of the model's function is to estimate CAFE improvements that a given manufacturer could achieve by applying additional technology to specific vehicles in its product line. A significant number of inputs to the Volpe decision-tree model are related to the effectiveness (fuel consumption reduction) of each fuel-saving technology. Argonne National Laboratory has developed a fullvehicle simulation tool named Autonomie, which has become one of the industry's standard tools for analyzing vehicle energy consumption and technology effectiveness. Full-vehicle simulation tools use physics-based mathematical equations, engineering characteristics (e.g., engine maps, transmission shift points, and hybrid vehicle control strategies), and explicit drive cycles to predict the effectiveness of individual and combined fuel-saving technologies. The Large-Scale Simulation Process accelerates and facilitates the assessment of individual technological impacts on vehicle fuel economy. This paper will show how Argonne efficiently simulates hundreds of thousands of vehicles to model anticipated future vehicle technologies. [ABSTRACT FROM AUTHOR]

This paper proposes a blended rule-based energy management system (EMS) for a plug-in hybrid electric vehicle (PHEV). The proposed EMS is formulated over driving information and vehicle trip energy and not over vehicle speed profiles, as usually seen. The proposed EMS design structure and strategy is described followed by its evaluation. This is the first time a platform for a rule-based acausal EMS has been designed. Performance metrics such as the fuel economy and the number of engine stop–starts are compared with conventional rule-based EMS over real-world destinations with uncertain trip demand. Its performance metrics compared with a conventional EMS for a full parallel PHEV was found to be superior in this paper. [ABSTRACT FROM PUBLISHER]

Increasingly stringent fuel economy and emissions regulations alongside efforts to reduce oil dependence have accelerated the global deployment of advanced vehicle technologies. In recent years, original equipment manufacturers (OEMs) and consumers have generally been successful in mutually deploying cleaner vehicle options with little sacrifice in cost, performance or overall utility. Projections regarding the challenges and impacts associated with compliance with mid- and long-term targets in the U.S., however, incur much greater uncertainty. The share of existing new vehicles that is expected to comply with future regulations, for example, falls below 10% by 2020. This article explores advanced technologies that result in reduced fuel consumption and emissions that are commercially available in 2014 Model Year compact and midsize passenger cars. A review of the recent research literature and publicly available cost and technical specification data addressing correlations between incremental cost and fuel economy is presented. This analysis reveals that a 10% improvement in the sales-weighted average fuel economy of passenger cars has been achieved between 2011 and 2014 at costs that are at or below levels anticipated by the regulations by means of reductions in weight, friction, and drag; advancements in internal combustion efficiency; turbocharging combined with engine downsizing; transmission upgrades; and the growth of hybrids. Benefit-cost analyses performed on best-selling models in the selected classifications reveal that consumers thus far are not substantially incentivized to purchase fuel economy. Under baseline conditions, benefit-cost ratios are above a breakeven value of unity for only 6 of 28 models employing improved fuel-economy technologies. Sales-weighted data indicate that the “average” consumer that elected to invest in greater fuel economy spent $1490 to realize a 17.3% improvement in fuel economy, equating to estimated savings of $1070. Thus savings were, on average, insufficient to cover technology costs in the baseline scenario. However, a sensitivity analysis reveals that a majority of new technologies become financially attractive to consumers when average fuel prices exceed $5.60/gallon, or when annual miles traveled exceed 16,400. The article concludes with techno-economic implications of the research on future fuel economy regulations for stakeholders. In general, the additional cost consumers incur in exchange for a given level of fuel economy improvement in the coming years will need to be steadily reduced compared to current levels to ensure that the expected benefits of fuel savings are financially warranted. [ABSTRACT FROM AUTHOR]

Fuel-speed curves (FSC) are used to account for the aggregate effects of congestion on fuel consumption in transportation scenario analysis. This paper presents plausible FSC for conventional internal combustion engine (ICE) vehicles and for advanced vehicles such as hybrid electric vehicles, fully electric vehicles (EVs), and fuel cell vehicles (FCVs) using a fuel consumption model with transient driving schedules and a set of 145 hypothetical vehicles. The FSC shapes show that advanced power train vehicles are expected to maintain fuel economy (FE) in congestion better than ICE vehicles, and FE can even improve for EV and FCV in freeway congestion. In order to implement these FSC for long-range scenario modeling, a bounded approach is presented which uses a single congestion sensitivity parameter. The results in this paper will assist analysis of the roles that vehicle technology and congestion mitigation can play in reducing fuel consumption and greenhouse gas emissions from motor vehicles. [ABSTRACT FROM AUTHOR]

Abstract: Hybrid electric vehicles require an algorithm that controls the power split between the internal combustion engine and electric machine(s), and the opening and closing of the clutch. Optimal control theory is applied to derive a methodology for a real-time optimal-control-based power split algorithm. The presented strategy is adaptive for vehicle mass and road elevation, and is implemented on a standard Electronic Control Unit of a parallel hybrid electric truck. The implemented strategy is experimentally validated on a chassis dynamo meter. The fuel consumption is measured on 12 different trajectories and compared with a heuristic and a non-hybrid strategy. The optimal control strategy has a fuel consumption lower (up to 3%) than the heuristic strategy on all trajectories that are evaluated, except one. Compared to the non-hybrid strategy the fuel consumption reduction ranged from 7% to 16%. [Copyright &y& Elsevier]

• A fuel consumption model for Hybrid Electric Vehicles (HEVs) is developed. • Real driving tests of Argonne National Laboratory are used to verified the model. • HEVs show considerable fuel saving in various traffic conditions. • HEVs can not save much fuel when the traffic is in free flow state. Despite extensive work on the fuel consumption of vehicles, the evaluation of hybrid electric vehicles (HEVs) requires a model that can predict fuel consumption second by second. In this paper, a fuel consumption model for hybrid vehicles is developed based on the operation of internal combustion engine (ICE), electric machine (EM) and battery. The fuel consumption model for engine is based on steady-state fuel mapping with a transient correction. EM and battery module (EBM) is introduced to estimate the fuel consumption for different modes of hybrid vehicle. The Argonne National Laboratory (ANL) measurements of different driving cycles including the steady-state cycle, the Urban Dynamometer Driving Schedule (UDDS) cycle, the Highway cycle and the United States 06 (US06) cycle are used to verified the model. With cellular automaton simulation, we study the fuel consumption in traffic flow and show that the fuel consumption can be significantly reduced by hybrid mode. The mean fuel saving is approximately 30% in the traffic flow on a horizontal road. The fuel consumption of traffic flow under uphill, downhill, tailwind and headwind conditions also showes considerable fuel saving. The model can be used to evaluate the fuel economy of HEVs, and provide eco-driving route-choice suggestions for drivers. [ABSTRACT FROM AUTHOR]