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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.

In this paper, a new solution method is presented to study the effect of wave propagation in engine manifolds, which includes solving one-dimensional models for compressible flow of air. Velocity, pressure, and density profiles are found by solving a system of non-linear Partial Differential Equations (PDEs) in space and time derived from Euler’s equations. The 1D model includes frictional losses, area change, and heat transfer. The solution is traditionally found by utilizing the Method of Characteristics and applying finite difference solutions to the resulting system of ordinary differential equations (ODEs) over a discretized grid. In this work, orthogonal collocation is used to solve the system of ODEs that is defined along the characteristic curves. Orthogonal polynomials are utilized to approximate velocity, pressure, sound speed, and the characteristic curves along which the system of PDEs reduce to a system of ODEs.

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

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.

Energy management strategies greatly influence the power performance and fuel economy of series hybrid electric tracked bulldozers. In this paper, we present a procedure for the design of a power management strategy by defining a cost function, in this case, the minimization of the vehicle’s fuel consumption over a driving cycle. To explore the fuel-saving potential of a series hybrid electric tracked bulldozer, a dynamic programming (DP) algorithm is utilized to determine the optimal control actions for a series hybrid powertrain, and this can be the benchmark for the assessment of other control strategies. The results from comparing the DP strategy and the rule-based control strategy indicate that this procedure results in approximately a 7% improvement in fuel economy.

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.

The Magma engine concept is characterised by a high compression ratio, central injector combustion system employed in a downsized direct-injection gasoline engine. An advanced boosting system and Miller cycle intake-valve closing strategies are used to control combustion knock while maintaining specific performance. A key feature of the Magma concept is the use of high CR without compromise to mainstream full-load performance levels. This paper focuses on development of the Magma combustion system using a single-cylinder engine, including valve event, air motion and injection strategies. Key findings are that Early Intake Valve Closing (EIVC) is effective both in mitigating knock and improving fuel consumption. A Net Indicated Mean Effective Pressure (NIMEP) equivalent to 23.6 bar Brake Mean Effective Pressure (BMEP) on a multi-cylinder engine has been achieved with a geometric compression ratio of 13:1.

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.

A control algorithm is developed for active/semi-active suspensions which can provide more comfort and better handling simultaneously. A weighting parameter is tuned online which is derived from two components - slow and fast adaptation to assign weights to comfort and handling. After establishing through simulations that the proposed adaptive control algorithm can demonstrate a performance better than some controllers in prior-art, it is implemented on an actual vehicle (Cadillac STS) which is equipped with MR dampers and several sensors. The vehicle is tested on smooth and rough roads and over speed bumps.

In vehicles equipped with conventional Electric Power Steering (EPS) systems, the steering effort felt by the driver can be unreasonably low when driving on slippery roads. This may lead inexperienced drivers to steer more than what is required in a turn and risk losing control of the vehicle. Thus, it is sensible for tire-road friction to be accounted for in the design of future EPS systems. This paper describes the design of an auxiliary EPS controller that manipulates torque delivery of current EPS systems by supplying its motor with a compensation current controlled by a fuzzy logic algorithm that considers tire-road friction among other factors. Moreover, a steering system model, a nonlinear vehicle dynamics model and a Dugoff tire model are developed in MATLAB/Simulink. Physical testing is conducted to validate the virtual model and confirm that steering torque decreases considerably on low friction roads.

With the increasing emphasis on Systems Engineering, there is a need to ensure that Electrical/Electronic (E/E) Systems Endurance Testing of vehicles, in a real world environment, prior to Production Launch, is performed in a manner and at a technological level that is commensurate with the high level of electronics and computers in contemporary vehicles. Additionally, validating the design and performance of individual standalone electronic systems and modules “on the bench” does not guarantee that all the permutations and combinations of real-world hardware, software, and driving conditions are taken into account. Traditional Proving Ground (PG) vehicle testing focuses mainly on powertrain durability testing, with only a simple checklist being used by the PG drivers as a reminder to cycle some of the electrical components such as the power window switches, turn signals, etc.

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

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 simple strategy for building lightweight automobile body-in-whites (BIWs) is developed and discussed herein. Because cost is a critical factor, expensive advanced materials, such as carbon fiber composites and magnesium, must only be used where they will be most effective. Constitutive laws for mass savings under various loading conditions indicate that these materials afford greater opportunity for mass saving when used in bending, buckling or torsion than in tensile, shear or compression. Consequently, it is recommended that these advanced materials be used in BIW components subject to bending and torsion such as rails, sills, “A-B-C” pillars, etc. Furthermore, BIW components primarily subject to tension, compression, or shear, such as floor pans, roofs, shock towers, etc., should be made from lower cost steel. Recommendations for future research that are consistent with this strategy are included.

The detection and tracking of the damage process between surfaces in contact, together with an estimation of the remaining service life, are significant contributions to the efficient operation of hydraulic components. The commonly used approach of analyzing vibration signals in terms of spectral distributions, while being very effective, has some shortcomings. For example, the results are sensitive to both load and speed variations. The approach presented in this paper is based on the fact that the asperity distribution of surfaces in good condition have a near normal probability distribution. Deviation from this can be tracked using statistical moments. The Beta probability distribution provides a number of shapes, including normal, under the control of two positive numbers, α and β. Unlike the normal distribution, which indicates defects by kurtosis values higher than 3.0, the Beta distribution provides more flexibility.

Many design problems are discovered often late in the development process, when design flexibility is limited. It is the art of the refinement engineers to find a solution to any unpredicted issues at this stage. The refinement process contains many hours of testing and requires many prototypes. Having an accurate experimental model of the system in this phase could reduce refinement time significantly. One of the areas that usually require refinement and tuning late in the design process is engine and body mounting systems. In this paper, we introduce a technique to optimize the mounting system of a vehicle for a given objective function using experimental/numerical analysis. To obtain an accurate model of the vehicle, we introduce an experimental procedure based upon the substructuring method. The method eliminates the need for any accurate finite element method of the vehicle. Experimental results of the implementation of this approach to a real vehicle are presented.