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Research in plug in vehicles (PHEV and BEV) has of course been ongoing for decades, however now that these vehicles are finally being produced for a mass market an intense focus over the last few years has been given to proper evaluation techniques and standard information to effectively convey efficiency information to potential consumers. The first challenge is the development of suitable test procedures. Thanks to many contributions from SAE members, these test procedures have been developed for PHEVs (SAE J1711 now available) and are under development for BEVs (SAE J1634 available later this year). A bigger challenge, however, is taking the outputs of these test results and dealing with the issue of off-board electrical energy consumption in the context of decades-long consumer understanding of MPG as the chief figure of merit for vehicle efficiency.

Career development is no longer something you focus on in your twenties and are set for life, it is ongoing and constant. New technologies, globalization and the world-wide competition for jobs demand that we continue to grow our skills and knowledge throughout our life. This session will provide you with tools to help you meet this demand as an engineering professional. Participants will create a personal mission statement and set career goals, identify the best way to research new opportunities and build their network while also crafting a personal brand with consistent messaging. Organizer Martha Schanno, SAE International Panelist Caryn Mateer, Transformational Leaders Intl. Kathleen Riley, Transformational Leaders Intl.

Selective Catalytic Reduction (SCR) catalysts are used to reduce NOx emissions from internal combustion engines in a variety of applications [1,2,3,4]. Southwest Research Institute (SwRI) performed an Internal Research & Development project to study SCR catalyst thermal deactivation. The study included a V/W/TiO2 formulation, a Cu-zeolite formulation and a Fe-zeolite formulation. This work describes NH3 storage capacity measurement data as a function of aging time and temperature. Addressing one objective of the work, these data can be used in model-based control algorithms to calculate the current NH3 storage capacity of an SCR catalyst operating in the field, based on time and temperature history. The model-based control then uses the calculated value for effective DEF control and prevention of excessive NH3 slip. Addressing a second objective of the work, accelerated thermal aging of SCR catalysts may be achieved by elevating temperatures above normal operating temperatures.

Over the past several years, new recommended practices for testing plug-in vehicles have been developed by SAE standards committees. At first only proprietary or prototype vehicles were available to validate new procedures. However, with the recent availability of Chevy Volt and Nissan Leaf, these test procedures were put to the test in Argonne�s National Laboratory�s dynamometer test facility. Procedures for the Volt were according to the SAE J1711 procedures. The Leaf was tested according to procedures still under development in the SAE J1634 task force. Identified were aspects of the tests that were successful and areas where more development is needed. As described in SAE J2841, the Volt results were analyzed using a �utility factor� to estimate in-use expectations of electric-only miles.

The Hybrid Electric Vehicle Team of Virginia Tech participated in the three-year EcoCAR Advanced Vehicle Technology Competition organized by Argonne National Laboratory, and sponsored by General Motors and the U.S. Department of Energy. The team established goals for the design of a plug-in, range-extended hybrid electric vehicle that meets or exceeds the competition requirements for EcoCAR. The challenge involved designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use, regulated tailpipe emissions, and well-to-wheel greenhouse gas emissions. To interface with and control the hybrid powertrain, the team added a Hybrid Vehicle Supervisory Controller, which enacts a torque split control strategy. This paper builds on an earlier paper [1] that evaluated the petroleum energy use, criteria tailpipe emissions, and greenhouse gas emissions of the Virginia Tech EcoCAR vehicle and control strategy from the 2nd year of the competition.

In support of the U.S Department of Energy's Vehicle Technologies Program, numerous vehicle technology combinations have been simulated using Autonomie. Argonne National Laboratory (Argonne) designed and wrote the Autonomie modeling software to serve as a single tool that could be used to meet the requirements of automotive engineering throughout the development process, from modeling to control, offering the ability to quickly compare the performance and fuel efficiency of numerous powertrain configurations. For this study, a multitude of vehicle technology combinations were simulated for many different vehicles classes and configurations, which included conventional, power split hybrid electric vehicle (HEV), power split plug-in hybrid electric vehicle (PHEV), extended-range EV (E-REV)-capability PHEV, series fuel cell, and battery electric vehicle.

Software products in the automotive industry are by nature widely distributed and costly to update (recall), so high reliability is clearly of utmost importance. Just as clearly, the increasing reliance on remote access to such systems, for diagnostic and other purposes, has made security an essential requirement, and traditional techniques for software development are proving to be inadequate in dealing with these issues. Correctness by Construction is a software design and development methodology that builds reliability and security into the system from the start. It can be used to demonstrate, with mathematical rigor, a program's correctness properties while reducing the time spent during testing and debugging. This paper will discuss the use of Correctness by Construction, and its accompanying SPARK language technology, to improve automotive systems' security and reliability. (The approach can also account for safely issues, although that is not the focus of this paper.)

This paper reports results of an experimental investigation performed on a commercial diesel engine supplied with fuel blends having low cetane number to attain a simultaneous reduction in NOx and smoke emissions. Blends of 20% and 40% of n-butanol in conventional diesel fuel have been tested, comparing engine performance and emissions to diesel ones. Taking advantage of the fuel blend higher resistance to auto ignition, it was possible to extend the range in which a premixed combustion is achieved. This allowed to match the goal of a significant reduction in emissions without important penalties in fuel consumption. The experimental activity was carried on a turbocharged, water cooled, 4 cylinder common rail DI diesel engine. The engine equipment included an exhaust gas recirculation system controlled by an external driver, a piezo-quartz pressure transducer to detect the in-cylinder pressure signal and a current probe to acquire the energizing current to the injector.

In this work a detailed model to simulate the transient behavior of catalytic converters is presented. The model is able to predict the unsteady and reacting flows in the exhaust ducts, by solving the system of conservation equations of mass, momentum, energy and transport of reacting chemical species. The en-gine and the intake system have not been included in the simulation, imposing the measured values of mass flow, gas temperature and chemical composition as a boundary condition at the inlet of the exhaust system. A detailed analysis of the diffusion stage triggering is proposed along with simplifications of the physics, finalized to the reduction of the calculation time. Submodels for water condensation and its following evaporation on the monolith surface have been taken into account as well as oxygen storage promoted by ceria oxides.

A numerical investigation on a series of Diesel spray experiments in constant-volume vessels is proposed. Non reacting conditions were used to assess the spray models and to determine the grid size required to correctly predict the fuel-air mixture formation process. To this end, not only computed liquid and vapor penetrations were compared with experimental data, but also a detailed comparison between computed and experimental mixture fraction distributions was performed at different distances from the injector. Grid dependency was reduced by introducing an Adaptive Local Mesh Refinement technique (ALMR) with an arbitrary level of refinement. Once the capabilities of the current implemented spray models have been assessed, reacting conditions at different ambient densities and temperatures were considered. A Perfectly Stirred Reactor (PSR) combustion model, based on a direct integration of complex chemistry mechanisms over a homogenous cell, was adopted.

Direct injection offers a large number of degrees of freedom, as it strongly influences the mixture stratification process. Experiments on a single cylinder research engine fuelled by H2, carried out at Argonne National Laboratory, showed the influence of injection parameters (timing and geometry) on engine efficiency and combustion stability. At low load, when a late injection strategy was performed, an unstable engine behavior was detected varying the injection direction. In order to optimize the mixture stratification process in DI H2 engines, it is important to understand the physics underlying the experimental results. A spatially resolved representation of the in-cylinder processes is a useful tool to properly set the injection parameters. Also, the knowledge of the pre-injection flow field is of added value in optimizing the injection process.

Mopeds are popular means of transportation, particularly in southern Europe and in eastern and southern Asia. The relative importance of their emissions increases in urban environments which host large fleets of mopeds. In Naples, for example, mopeds make a considerable contribution to HC emissions (about 53%), although the percentage of mopeds (12.4%) in the total circulating fleet is lower than that of other vehicle categories [1]. This study presents a method for analysing the influence of kinematic parameters on the emission factors of mopeds during the “cold-start” and “hot” phases of elementary kinematic sequences (speed-time profiles between two successive stops). These elementary sequences were obtained through appropriate fragmentation of complex urban driving cycles. In a second step, we show how to estimate, for the whole cycle, the duration of the cold phase and the relevant time-dependence function.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

For a series plug-in hybrid electric vehicle (PHEV), it is critical that batteries be sized to maximize vehicle performance variables, such as fuel efficiency, gasoline savings, and zero emission capability. The wide range of design choices and the cost of prototype vehicles calls for a development process to quickly and systematically determine the design characteristics of the battery pack, including its size, and vehicle-level control parameters that maximize the net present value (NPV) of a vehicle during the planning stage. Argonne National Laboratory has developed Autonomie, a modeling and simulation framework. With support from The MathWorks, Argonne has integrated an optimization algorithm and parallel computing tools to enable the aforementioned development process. This paper presents a study that utilized the development process, where the NPV is the present value of all the future expenses and savings associated with the vehicle.

The paper presents a method for the indoor testing of road vehicle suspension systems. A suspension is positioned on a rotating drum which is located in the Laboratory for the Safety of Transport at Politecnico di Milano. Special six-axis load cells have been designed and used for measuring the forces/moments acting at each suspension-chassis joints. The forces/moments, wheel accelerations, displacements are measured up to 100 Hz. Two different types of test can be performed. The tire/wheel unbalance effect on the suspension system behavior (Vibration and Harshness, VH) has been analyzed by testing the suspension system from zero to the vehicle maximum speed on a flat surface and by monitoring the forces transmitted to the chassis. In the second kind of test, the suspension system has been excited as the wheel passes over different cleats fixed on the drum.

A comprehensive research is presented aiming at assessing the ride comfort of subjects seated into road or off-road vehicles. Although many papers and books have appeared in the literature, many issues on ride comfort are still to be understood, in particular, the paper investigates the mutual effects of the posture and the vibration caused mostly from road unevenness. The paper is divided into two parts. In the first part, a mathematical model of a seated subject is validated by means of actual measurements on human subjects riding on a car. Such measurements refer to the accelerations acting at the subject/seat interface (vertical acceleration at the seat cushion and horizontal acceleration at the seat back). A proper dummy is used to derive the seat stiffness and damping.

Ammonia/urea-SCR is a mature technology, applied worldwide for the control of NOx emissions in combustion exhausts from thermal power plants, cogeneration units, incinerators and stationary diesel engines and more recently also from mobile sources. However a greater DeNOx activity at low temperatures is desired in order to meet more and more restrictive legislations. In this paper we report transient and steady state data collected over commercial Fe-ZSM-5 and V₂O₅-WO₃/TiO₂ catalysts showing high NOx reduction efficiencies in the 200 - 350°C T-range when NO and ammonia react with nitrates, e.g., in the form of an aqueous solution of ammonium nitrate. Under such conditions a new reaction occurs, the so-called "Enhanced SCR" reaction, 2 NH₃ + 2 NO + NH₄NO₃ → 3 N₂ + 5 H₂O.

This paper evaluates the impact of energy management strategy on the cost benefits of a plug-in hybrid electric vehicle (PHEV) by taking into account the impact of PHEV energy management on battery life and petroleum displacement over the life of the vehicle. Using Battery in the Loop (BIL), a real battery is subjected to transient power demands by a virtual vehicle. The vehicle energy management strategy is varied, resulting in different battery utilization scenarios. Battery life, which varies with battery utilization, is estimated for the different energy management scenarios. The same representative drive cycle is used over the different energy management strategies to isolate the impact of energy management on battery utilization. PHEV gasoline savings, in comparison to a charge sustaining hybrid, are calculated for each of the energy management strategies, for a fixed distance of 40 miles.

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

Although the application of cylinder pressure sensors to gain insight into the combustion process is not a novel topic itself, the recent availability of inexpensive in-cylinder pressure sensors has again prompted an upcoming interest for the utilization of the cylinder pressure signal within engine control and monitoring. Besides the use of the in-cylinder pressure signal for combustion analysis and control the information can also be used to determine related quantities in the exhaust or intake manifold. Within this work two different methods to estimate the pressure inside the exhaust manifold are proposed and compared. In contrary to first principle based approaches, which may require time extensive parameterization, alternative data driven approaches were pursued. In the first method a Principle Component Analysis (PCA) is applied to extract the cylinder pressure information and combined with a polynomial model approach.