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This session covers topics regarding new CI and SI engines and components. This includes analytical, experimental, and computational studies covering hardware development as well as design and analysis techniques. Presenter Sung Hoon Lee, Hyundai Motor Co.

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.)

The development of PM and NOx reduction system with the combination of DOC included DPF and SCR catalyst in addition to the AOC sub-assembly for NH3 slip protection is described. DPF regeneration strategy and manual regeneration functionality are introduced with using ITH, HCI device on the EUI based EGR, VGT 12.3L diesel engine at the CVS full dilution tunnel test bench. With this system, PM and NOx emission regulation for JPNL was satisfied and DPF regeneration process under steady state condition and transient condition (JE05 mode) were successfully fulfilled. Manual regeneration process was also confirmed and HCI control strategy was validated against the heat loss during transient regeneration mode. Presenter Seung-il Moon

Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

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.

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.

Wide attention to fuel cell electric vehicles (FCEVs) comes from two huge issues currently the world is facing with: the concern of the petroleum reserves depletion due to consequent oil dependence and the earth global warming due in some extent to vehicle emissions. In this background, Hyundai, along with its sister company Kia, has been building the FCEVs and operating their test fleet with several tens of units at home and abroad. Since 2004, 32 passenger vehicles have been offered for the Department of Energy's controlled hydrogen fleet and infrastructure demonstration and validation project in the U.S. In the meantime, from 2006, 30 passenger vehicles as well as four buses, featuring the in-house developed fuel cell stack and its associated components, are currently under the domestic operation for the FCEV learning demonstration led by the Ministry of Knowledge and Economy.

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.

Lignin by-products from biorefineries has the potential to provide a low-cost alternative to petroleum-based precursors to manufacture carbon fiber, which can be combined with a binding matrix to produce a structural material with much greater specific strength and specific stiffness than conventional materials such as steel and aluminum. The market for carbon fiber is universally projected to grow exponentially to fill the needs of clean energy technologies such as wind turbines and to improve the fuel economies in vehicles through lightweighting. In addition to cellulosic biofuel production, lignin-based carbon fiber production coupled with biorefineries may provide $2,400 to $3,600 added value dry Mg−1 of biomass for vehicle applications. Compared to producing ethanol alone, the addition of lignin-derived carbon fiber could increase biorefinery gross revenue by 30% to 300%.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.

A variety of methodologies to use embedded multicore controllers efficiently has been discussed in the last years. Several assumptions are usually made in the automotive domain, such as static assignment of tasks to the cores. This paper shows an approach for efficient task allocation depending on different system modes. An engine management system (EMS) is used as application example, and the performance improvement compared to static allocation is assessed. The paper is structured as follows: First the control algorithms for the EMS will be classified according to operating modes. The classified algorithms will be allocated to the cores, depending on the operating mode. We identify mode transition points, allowing a reliable switch without neglecting timing requirements. As a next step, it will be shown that a load distribution by mode-dependent task allocation would be better balanced than a static task allocation.