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Active regeneration systems for cleaning diesel exhaust can operate at extremely high temperatures up to 1000°C. The extremely high temperatures create a unique challenge for the design of regeneration structural components near their melting temperatures. In this paper, the preparation of the sheet specimens and the test set-up based on induction heating for sheet specimens are first presented. Tensile test data at room temperature, 500, 700, 900 and 1100°C are then presented. The yield strength and tensile strength were observed to decrease with decreasing strain rate in tests conducted at 900 and 1100°C but no strain rate dependence was observed in the elastic properties for tests conducted below 900°C. The stress-life relations for under cyclic loading at 700 and 1100°C with and without hold time are then investigated. The fatigue test data show that the hold time at the maximum stress strongly affects the stress-life relation at high temperatures.

This paper describes the development of the fixed seat eyellipse in the October 2008 revision of SAE Recommended Practice J941. The eye locations of 23 men and women with a wide range of stature were recorded as they sat in each of three second-row bench seats in a laboratory mockup. Testing was conducted at 19-, 23-, and 27-degree seat back angles. Regression analysis demonstrated that passenger eye location was significantly affected by stature and by seat back angle. The regression results were used to develop an elliptical approximation of the distribution of adult passenger eye locations, applying a methodology previously used to develop the driver eyellipse in SAE J941-2002.

Seat comfort is driven in part by the fit between the sitter and seat. Traditional anthropometric data provide little information about the size and shape of the torso that can be used for backrest design. This study introduces a methodology for using three-dimensional computer models of the human torso based on a statistical analysis of body shapes for conducting automated fit assessments. Surface scan data from 296 men and 417 women in a seated posture were analyzed to create a body shape model that can be adjusted to a range of statures, body shape, and postures spanning those typical of vehicle occupants. Finite-element models of two auto seat surface were created, along with custom software that generates body models and postures them in the seat. A simple simulation technique was developed to rapidly assess the fit of the torso relative to the seat back.

Understanding the lightweighting potential of materials is important in making strategic decisions for material selection for a new vehicle program. Frequently benchmarking is done to support these decisions by selecting a reference vehicle which is believed to be mass efficient, then using the teardown mass data to set targets for the vehicle under design. In this work, rather then considering a single benchmark vehicle or a small set of vehicles, we looked at a large sample of vehicles over a range of sizes and segments (approximately 200 vehicles). Statistical methods were used to identify mass drivers for each subsystem. Mass drivers are the attributes of the vehicle and subsystem which determine subsystem mass. Understanding mass-drivers allows comparisons across vehicle size, segments, and materials. Next, we identified those vehicles which had subsystems which were much lighter than the average after adjusting for mass drivers. This set was defined as mass-efficient designs.

The fore-aft location of the steering wheel relative to the pedals is a critical determinant of driving posture and comfort. Current SAE practices lack quantitative guidance on steering wheel positioning. This paper presents a model of subjective preference for fore-aft steering wheel position across a range of seat heights. Sixty-eight men and women evaluated the steering wheel positions in a total of 9 package conditions differentiated by seat height and fore-aft steering wheel position. Numerical responses were given on a 7-point scale anchored with the words “Too Close”, “Just Right”, and “Too Far”. A statistical analysis of the results demonstrated that the preferred fore-aft steering wheel position was affected by seat height and driver stature. An ordinal logistic regression model was created that predicts the distribution of subjective responses to steering wheel location. The model can be used to calculate the preferred steering wheel position for individuals or populations.

Seat belt anchorage locations have a strong effect on occupant protection. Federal Motor Vehicle Safety Standard (FMVSS) 210 specifies requirements for the layout of the anchorages relative to the seating reference point and seat back angle established by the SAE J826 H-point manikin. Sled testing and computational simulation has established that belt anchorage locations have a strong effect on occupant kinematics, particularly for child occupants using the belt as their primary restraint. As part of a larger study of vehicle geometry, the locations of the anchorage points in the second-row, outboard seating positions of 83 passenger cars and light trucks with a median model year of 2005 were measured. The lower anchorage locations spanned the entire range of lap belt angles permissible under FMVSS 210 and the upper anchorages (D-ring locations) were distributed widely as well.

This paper proposes a methodology to develop a nonlinear model predictive control (NMPC) of a dual-independent variable valve timing (di-VVT) engine using discretized nonlinear engine models. In multiple-input-multiple-output (MIMO) systems, model based control methodologies are critical for realizing the full potential of complex hardware. Fast and accurate control oriented models (COM) that capture combustion physics, actuator and system dynamics are prerequisites for developing NMPC. We propose a multi-scale simulation approach to generate the non-linear combustion model, where the high-fidelity engine cycle simulation is utilized to characterize effects of turbulence, air-to-fuel ratio, residual fraction, and nitrogen oxide (NOx) emissions. The input-to-output relations are subsequently captured with artificial neural networks (ANNs). Manifold and actuator dynamics are discretized to reduce computation efforts.

The number of control actuators available on spark-ignition engines is rapidly increasing to meet demand for improved fuel economy and reduced exhaust emissions. The added complexity greatly complicates control strategy development because there can be a wide range of potential actuator settings at each engine operating condition, and map-based actuator calibration becomes challenging as the number of control degrees of freedom expand significantly. Many engine actuators, such as variable valve actuation and flow control valves, directly influence in-cylinder combustion through changes in gas exchange, mixture preparation, and charge motion. The addition of these types of actuators makes it difficult to predict the influences of individual actuator positioning on in-cylinder combustion without substantial experimental complexity.

This study evaluates powertrain technologies capable of reducing light duty vehicle fuel consumption for compliance with 2025 CAFE standards. A fully integrated GT-Power engine model with physics based sub-models was developed to capture any positive or negative synergies between the technologies. The two zone multi-cylinder engine model included typical thermodynamic subroutines, with predictive combustion, flame quench and knock models, along with map-based turbocharger models to capture key combustion and efficiency behaviors. The engine model was calibrated to data from a boosted GDI engine and exercised through one series of current and production viable technology configurations for 2025 regulations.

Homogeneous charge compression ignition (HCCI) has received much attention in recent years due to its ability to reduce both fuel consumption and NO emissions compared to normal spark-ignited (SI) combustion. However, due to the limited operating range of HCCI, production feasible engines will need to employ a combination of combustion strategies, such as stoichiometric SI combustion at high loads and leaner burn spark-assisted compression ignition (SACI) and HCCI at intermediate and low loads. The goal of this study was to extend the high load limit of HCCI into the SACI region while maintaining a stoichiometric equivalence ratio. Experiments were conducted on a single-cylinder research engine with fully flexible valve actuation. In-cylinder pressure rise rates and combustion stability were controlled using cooled external EGR, spark assist, and negative valve overlap. Several engine loads within the SACI regime were investigated.

Urea-selective catalytic reduction (SCR) after-treatment systems are used for reducing oxides of nitrogen (NOx) emissions in medium and heavy duty diesel vehicles. This paper addresses control-oriented modeling, starting from first-principles, of SCR after-treatment systems. Appropriate simplifications are made to yield governing equations of the Urea-SCR. The resulting nonlinear partial differential equations (PDEs) are discretized and linearized to yield a family of linear finite-dimensional state-space models of the SCR at different operating points. It is further shown that this family of models can be reduced to three operating regions. Within each region, parametric dependencies of the system on physical mechanisms are derived. Further model reduction is shown to be possible in each of the three regions resulting in a second-order linear model with sufficient accuracy.

The paper describes the approach, addresses integration challenges and discusses capabilities of the Hybrid Powertrain-in-the-Loop (H-PIL) facility for the series/hydrostatic hydraulic hybrid system. We describe the simulation of the open-loop and closed-loop hydraulic hybrid systems in H-PIL and its use for concurrent engineering and development of advanced supervisory strategies. The configuration of the hydraulic-hybrid system and details of the hydraulic circuit developed for the H-PIL integration are presented. Next, software and hardware interfaces between the real components and virtual systems are developed, and special attention is given to linking component-level controllers and system-level supervisory control. The H-PIL setup allows imposing realistic dynamic loads on hydraulic pump/motors and accumulator based on vehicle driving schedule.

In this study, two sled series were conducted with a sled buck representing a compact vehicle. The first series of tests focused on the effects of crash pulse, impact angle, occupant size, and front seat location on rear seat occupant restraint with a generic rear-seat belt system without pre-tensioner or load limiter. The second series of tests focused on investigating the benefit of using advanced features for rear-seat occupant restraint in the most severe crash condition in the first sled series. The first series of tests include 16 test conditions with two impact angles (0° and 15°), two sled pulse (soft and severe), and four ATD sizes (HIII 6YO, HIII 5th female, HIII 95th male, and THOR-NT) with two ATDs in each test. The driver seat was located at the mid position, while the front passenger seat was positioned such that a constant distance between the ATD knee and the front seat is achieved.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

As lightweight materials and advanced combustion engines are being used in both conventional and electrified vehicles with diverse fuels, it is necessary to evaluate the individual and combined impact of these technologies to reduce energy and greenhouse gas (GHG) emissions. This work uses life cycle assessment (LCA) to evaluate the total energy and GHG emissions for baseline and lightweight internal combustion vehicles (ICVs), hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) when they are operated with baseline and advanced gasoline and ethanol engines. Lightweight vehicle models are evaluated with primary body-in-white (BIW) mass reductions using aluminum and advanced/high strength steel (A/HSS) and secondary mass reductions that include powertrain re-sizing. Advanced engine/fuel strategies are included in the vehicle models with fuel economy maps developed from single cylinder engine models.

Automakers have the opportunity to utilize bio-based composite materials to lightweight cars while replacing conventional, nonrenewable resource materials. In this study, Life Cycle Assessment (LCA) is used to understand the potential benefits and tradeoffs associated with the implementation of bio-based composite materials in automotive component production. This cradle-to-grave approach quantifies the fiber and resin production as well as material processing, use, and end of life for both a conventional glass-reinforced polypropylene component as well as a cellulose-reinforced polypropylene component. The comparison is calculated for an exterior component on a high performance vehicle. The life cycle primary energy consumption and global warming potential (GWP) are evaluated. Reduced GWP associated with the alternative component are due to the use of biomass as process energy and carbon sequestration, in addition to the alternative material component's lightweighting effect.

A detailed understanding of the size, shape, and postures of children is required to design effective restraint systems for protecting children in motor vehicle crashes. Compiled and edited by experts in the fields of anthropometry, ergonomics, and child restraint, this book includes 14 important papers which provide a comprehensive overview of the methods for collecting, analyzing, and applying child anthropometry data for crash safety purposes. A detailed understanding of the size, shape, and postures of children is required to design effective restraint systems for protecting children in motor vehicle crashes. Compiled and edited by experts in the fields of anthropometry, ergonomics, and child restraint, this book includes 14 important papers which provide a comprehensive overview of the methods for collecting, analyzing, and applying child anthropometry data for crash safety purposes.