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The need for efficient space utilization has provided a framework for the design of a 248mm family of torque converters that supports a wide choice of engine and transmission combinations. The axial length of the part and its weight have been substantially reduced while the performance range has been broadened without degradation of efficiency. The new converter operates in an expanded slipping clutch mode. It significantly contributes to the performance and fuel economy improvements of related vehicles. To meet the cost target, the comprehensive lineup and the resulting complexity have required a high level of component interchangeability. During the design phase, the manufacturing core competencies were scrutinized and process redundancies eliminated, both resulting in optimization of material selection and applicable technology.

One of the primary issues in the interpretation of vehicle impact response data, observed from vehicle crash test events, is coping with variability. This vehicle response inconsistency generally causes test results to be unpredictable and makes CAE test validation work difficult as well. This paper, considering the uncertain characteristics of vehicle impact events, has implemented a stochastic assessment of vehicle NCAP response variation through a CAE vehicle impact model, and it has accomplished the three primary study objectives as stated follows: 1) Identify the response variation causing factors stochastically from various structural and environmental factor candidates and quantify the degree of their influences on crash response, 2) Develop a methodology for interpreting the significance of the factor effects in conjunction with vehicle impact mechanics and physics, and 3) Implement a stochastic improvement of the vehicle NCAP responses and their repeatability

While gasoline surrogate development has progressed in the areas of more complex surrogate mixtures and in kinetic modeling tools and mechanism development, it is generally recognized that further development is still needed. This paper represents a small step in supporting this development by providing comparisons between experimental engine data and surrogate-based kinetic models. In our case, the HCCI engine data comes from a port-injected, single-cylinder research engine with intake-air heating for combustion phasing control. Timing sweeps were run at constant fuel rate for three market gasolines and five surrogate mixtures. Modeling was done using the CHEMKIN software with a gasoline mechanism set containing 1440 species and 6572 reactions. Five pure compounds were selected for the surrogate blends and include iso-octane, n-heptane, toluene, methylcyclohexane, and 1-hexene.

The objective of this work is to perform a computer model based sensitivity analysis of parameters of an automotive air conditioning system to identify the critical parameters. Design of Experiment (DOE) and Analysis of Variance (ANOVA) techniques have been used to identify the critical parameters and their relative effects on the air conditioning system performance. The sensitivity analysis has been verified by running similar tests on an air conditioning system test stand (AC Test Stand).

This paper presents a method for optimization design of an engine mounting system subjected to some constraints. The engine center of gravity, the mount stiffness rates, the mount locations and/or their orientations with respect to the vehicle can be chosen as design variables, but some of them are given in advance or have limitations because of the packaging constraints on the mount locations, as well as the individual mount rate ratio limitations imposed by manufacturability. A computer program, called DynaMount, has been developed that identifies the optimum design variables for the engine mounting system, including decoupling mode, natural frequency placement, etc.. The degree of decoupling achieved is quantified by kinetic energy distributions calculated for each of the modes. Several application examples are presented to illustrate the validity of this method and the computer program.

A continuously variable lift, duration and phase mechanical lift mechanism is described, as applied to the intake valvetrain of a SOHC, 4-valve per cylinder, four-cylinder production engine. Improvements in fuel economy were sought by reduction of pumping losses and improved charge preparation, and optimization of WOT torque was attempted by variation of intake valve closing angle. Adjustment of the mechanism is achieved by movement of the pivot shaft for the rocker arms. The relationship between lift, duration and phase is predetermined at the design stage, and is fixed during operation. There is considerable design flexibility to achieve the envelope of lift curves deemed desirable. The operation of the mechanism is described, as are the development procedure, testing with fixed cams, some cycle simulation, friction testing on a separate rig and dyno testing results for idle, part load and WOT.

Load data representing severe customer usage is required during the chassis development process. One area of current research is the use of road profiles for predicting chassis loads. The most direct method of predicting these loads is to run dynamic simulations of the vehicle using numerous road profiles as the excitation. This onerous task may be avoided, and a greatly reduced number of simulations would be required, if roads having similar characteristics can be grouped. Currently, road profiles are characterized by their spectral content. It has been noted by several researches, however, that road profiles are generally nonstationary signals that contain significant transient events and are not well described in the spectral domain. The objective of this work, then, is to develop a method by which the characteristics of the road can be captured by describing these constitutive transient events.

Recently, many authors have attempted to represent an automobile body in terms of experimentally derived frequency response functions (FRFs), and to couple the FRFs with a FEA model of chassis for performing a total system dynamic analysis. This method is called Hybrid FEA-Experimental FRF method, or briefly HYFEX. However, in cases where the chassis model does not include the bushing models, one can not directly connect the FRFs of the auto body to the chassis model for performing a total system dynamic analysis. In other cases when the chassis model includes the bushings, the bushing dynamic rates are modeled as constant stiffness rather than frequency dependent stiffness, the direct use of the HYFEX method will yield unsatisfactory results. This paper describes how the FRF's of the auto body and the frequency dependent stiffness data of the bushings can be combined with an appropriate mathematical formulation to better represent the dynamic characteristics of a full vehicle.

A new realistic motion control algorithm for digital human models is presented in this paper based on the principle of effort minimization. The proposed algorithm is developed through an innovative mathematical model to make the applications more flexible and more global, especially for the visualization of human motions in automotive assembly operations. The central idea of this unique model is to interpret the solution of the homogeneous Lagrange equation for a mannequin as the origin of dynamic motion. Furthermore, a digital human possesses about 42 joints over the main body except the head, fingers and toes, and offers a large room of kinematic redundancy. We have found 14 new 3-D independent motion markers assigned over the human body to constitute a Cartesian coordinate system, under which a minimum-effort based dynamic control scheme is developed using a state-feedback linearization procedure.

This paper examines the conformability of elastic piston rings to a distorted cylinder bore. Several bounds are available in the literature to help estimate the maximum allowable Fourier coefficient in a Fourier expansion of bore distortion: the analytically derived bounds in [7] and [8], and the semi-empirically derived bounds discussed in [9]. The underlying assumptions for each set of analytic bounds are examined and a multiple order algorithm is derived. The proposed algorithm takes account of multiple orders of distortion at once. It is tested with finite element (FE) data and compared to the classical bound approach. The results indicate that the bounds in [7] are compatible with linear elasticity theory (LET), whereas the bounds in [8] are not. Furthermore, numerical evidence indicates that the present multiple order algorithm can predict seal breaches more accurately than either of the other analytic bounds.

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.

Accurate accounting for fresh charge (fuel and air) along with trapped RGF is essential for the subsequent thermodynamic analysis of combustion in gasoline engines as well as for on-line and real-time quantification as relevant to engine calibration and control. Cost and complexity of such techniques renders direct measurement of RGF impractical for running engines. In this paper, an empirically-based approach is proposed for on-line RGF, based on an existing semi-empirical model [1]. The model developed expands the range over which the semi-empirical model is valid and further improves its accuracy. The model was rigorously validated against a well correlated GT-POWER model as well as results from 1D gas exchange model [2]. Overall, using this model, RGF estimation error was within ∼1.5% for a wide range of engine operating conditions. The model will be implemented in Dyno development and calibration at Chrysler Group.

A systems-level modeling framework developed to estimate the life cycle cost of medium- and heavy-duty trucks is discussed in this paper. Costs are estimated at a resolution of five major subsystems and 30+ subsystems, each representing a specific manufacturing technology. Interrelationships among various subsystems affecting cost are accounted for. Results of a specific Class 8 truck are finally discussed to demonstrate the modeling framework's capability, including the analysis of cost-effectiveness of some of the competing alternative system design options being considered by the industry today.

This work explores pathways to achieve diesel-like, high-efficiency combustion with stoichiometric 3-way catalyst compatible spark ignition (SI). A high stroke-to-bore engine design (1.5:1) with cooled exhaust gas recirculation (EGR) and high compression ratio (rc) was used to improve engine efficiency by up to 30% compared with a production turbocharged gasoline direct injection spark ignition engine. To achieve efficiency improvements, engine experiments were coupled with computational fluid dynamics simulations to guide and explain experimental trends between the original engine and the high stroke-to-bore ratio design (1.5:1). The effects of EGR and late intake valve closing (IVC) and fuel characteristics are investigated through their effects on knock mitigation. Direct injection of 91 RON E10 gasoline, 99 RON E0 gasoline, and liquified petroleum gas (i.e., propane/autogas) were evaluated with geometric rc ranging from 13.3:1 to 16.8:1.

G-Equation models represent propagating flame fronts with an implicit two-dimensional surface representation (level-set). Level-set methods are fast, as transport source terms for the implicit surface can be solved with finite-volume operators on the finite-volume domain, without having to build the actual surface. However, they include approximations whose practical effects are not properly understood. In this study, we improved the numerics of the FRESCO CFD code’s G-Equation solver and developed a new method to simulate kernel growth using signed distance functions and the analytical sphere-mesh overlap. We analyzed their role for simulating propane/air flames, using three well-established constant-volume configurations: a one-dimensional, freely propagating laminar flame; a disc-shaped, constant-volume swirl combustor; and torch-jet flame development through an orifice from a two-chamber device.

Vehicle thermal protection is an important aspect of the overall vehicle development process. It involves optimizing the exhaust system routing and designing heat shields to protect various components that are in near proximity to the exhaust system. Reduced time to market necessitates an efficient process for thermal protection development. A robust procedure that utilizes state of the art CFD simulation techniques proactively during the design phase is described. Simulation allows for early detection of thermal issues and development of countermeasures several months before prototype vehicles are built. Physical testing is only used to verify the thermal protection package rather than to develop heat shields. The new procedure reduces the number of physical tests and results in a robust, efficient methodology.

This report explores the relationship of different failure criteria - specifically, surface cracks, stiffness changes, and two-piece failures - on rolled, ductile, cast-iron crankshafts. Crankshaft samples were closely monitored throughout resonant bending fatigue testing and were taken to near complete fracture. By monitoring resonance shifts of the samples during testing, stiffness changes and cracks were monitored. These data showed that an accelerating frequency shift was sufficient to indicate imminent two-piece failure and that this condition can be used as a failure criterion. Fatigue studies on two different crankshafts using this failure criterion were compared to those using a surface crack failure criterion. This comparison showed that using the surface crack failure criterion erroneously decreased the apparent fatigue life of the crankshaft significantly.

Interest in operational cost reduction is driving engine manufacturers to consider low-cost fuel substitution in heavy-duty diesel engines. These dual-fuel (DF) engines could be operated either in diesel-only mode or operated with premixed natural gas (NG) ignited by a pilot flame of compression-ignited direct-injected diesel fuel. Under certain conditions, dual-fuel operation can result in increased cycle-to-cycle variability (CCV) during combustion. CFD can greatly help in understanding and identifying critical parameters influencing CCV. Innovative modelling techniques and large computing resources are needed to investigate the factors affecting CCV in dual-fuel engines. This paper discusses the use of the High Performance Computing resource Titan, at Oak Ridge National Laboratory, to investigate CCV of a dual-fuel engine.

This paper deals with the multi-parameter and boundary mannequin techniques in creating human models in automotive applications. The concepts and applications of single-parameter, multiple parameter and boundary mannequin method are discussed respectively to clarify certain confusion. Emphasis is put on how to create boundary mannequins for a specific application, which may have been puzzling many engineers in practical applications. The authors would like to share their experience in using the digital human modeling software and make discussions on some common issues. A number of case studies from typical automotive manufacturing assembly operations are also presented to demonstrate the usage of the multi-parameter and boundary mannequin techniques.

Traditional autonomous vehicle perception subsystems that use onboard sensors have the drawbacks of high computational load and data duplication. Infrastructure-based sensors, which can provide high quality information without the computational burden and data duplication, are an alternative to traditional autonomous vehicle perception subsystems. However, these technologies are still in the early stages of development and have not been extensively evaluated for lane detection system performance. Therefore, there is a lack of quantitative data on their performance relative to traditional perception methods, especially during hazardous scenarios, such as lane line occlusion, sensor failure, and environmental obstructions.