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A simple ADAMS model was developed for simulating one possible mechanism that causes low-frequency (less than 1 kHz) noise in disc brake assemblies for heavy-duty and medium-duty trucks. The model consists of: truck tire, axle housing, torque plate, caliper, push rods, inner pad, outer pad, and rotor. Only one component (the torque plate) was modeled as a flexible body (using a finite element model), while all other parts are considered as infinitely rigid. A lumped parameter representing the suspension wrap-up stiffness resists the axle pitch motion. When the brakes are not engaged, the system has two distinct modes of vibration, namely, the axle pitch mode which is governed by the suspension wrap-up stiffness, and the caliper transverse (side-to-side) mode, which is governed by the stiffness of the torque plate (out-of-plane deflection of the torque plate) and by the suspension lateral stiffness.

Multibody Dynamics Simulation (MDS) studies are valuable in providing guidance in suspension systems design and reduce product development cost and time. These studies are used in various stages of suspension system design and development. In both concept study and detailed design the subsystem kinematics, dynamics and full vehicle dynamics studies are used. In this paper, four case studies for suspension system performance optimization using MDS studies are presented.

Engineering specifications, i.e. test bogeys, are criterion for determining the success or failure of durability designs in the product development process. Considerations in the development of the specifications for vehicle structural components, such as axle housings and suspension torque rods, have been presented in a previous SAE paper [1]. This paper has been prepared because the factors on the same subject for vehicle drive train components, such as gears and bearings, are quite different. The center of this study is on “how to define equivalent duty cycles for lab test”. Several issues distinguish this task for drive train components: High cycle fatigue, high accelerated tests, competitive failures and failure modes, empirical component load-life data, loading, field correlation, and system level tests.

Contact fatigue is a major concern on the durability of vehicle powertrain gear design. Having an effective method for gear life trend prediction will prevent over design of the powertrain gears and assure the quality of the products. The ANSI/AGMA Standard on gear contact fatigue life calculation is based on an empirical model developed from experiment data fitting. A similar approach widely used in the industry uses measured component SN curves for correspondence between loads and life cycles [1]. This method is simple. But important physical parameters such as material, lubricant, and manufacturing factors are not included in the model, therefore, the model cannot to be used for design optimization. Although some analytical models are available for the gear life prediction, they have not been accepted by the industry. On the one hand, most theoretical models are too complicated for applications.

A method for predicting the propensity of a drum brake system to produce noise is presented. The method utilizes finite element models of the individual components of the drum brake system, which have been assembled into the system model of the brake assembly. An important step in this process is the tuning of the dynamic characteristics of the FEA model to ensure validation with experimental tests. Friction is the key element, which defines the behavior of the drum brake system. The system FEA model is assembled by coupling the lining and drum at the contact interface to simulate the friction interaction. This process produces an asymmetric stiffness matrix. A complex eigenvalue analysis identifies the system dynamic characteristics such as the frequency and damping for each vibration mode. The damping values reveal which modes are unstable and therefore likely to produce noise.

Only products with high quality, low cost, and short concept-to-customer time will continue to have a high market share. For this reason, auto parts suppliers must strive to gain superior engineering capability. One key step in this pursuit is to implement widespread CAE (Computer-Aided-Engineering) in PDP (product development process) [1]. FEA (Finite Element Analysis), in particular, has been identified as a subject that deserves concentrated effort. Specifically, FEA needs to be used broadly and effectively in every phase of PDP ranging from concept evaluation and prototyping, to pre-production design and troubleshooting. However, resource requirement and process quality assurance are major issues in this undertaking [2, 3]. As a counter-measurement, developing product specific FEA guidelines has been identified as a priority strategic initiative. The focus of our presentation is on how to develop standard FEA procedures to guide FEA jobs.

Since 1983 the Torsen® differential has been employed in the powertrain of more than two-dozen sedans, SUVs, and military vehicles. This differential device is renowned for its unique high torque bias capacity. Torque bias has long been recognized as a desirable drivetrain characteristic that enhances both a vehicle's drivability and stability. Since the generation of torque bias relies on friction, the know-how in achieving balanced design of torque bias and efficiency is crucial. Presented in this paper is an analytical evaluation of the performance of Torsen differential with respect to these parameters. The mathematical model provides effective guidance in design optimization. The performance predictions were found to correlate well with experimentally measured data. In an effort to explore the theory behind the Torsen differential design, the general subject of speed differentiation and torque bias generation is reviewed.

The effect of kingpin inclination angle and wheel offset on various vehicle performance metrics such as steering effort, vehicle handling, and steering system vibration is described in this paper. A simple ADAMS model of a medium-duty truck has been developed for this study. The front axle consists of an idealized solid axle suspension with suspension system components represented by rigid bodies. The tire model used in this study is a linear tire model, and estimates of tire force coefficients were obtained as an average of several published estimates of medium-duty truck tires. Experimental design procedures (DOE) have been conducted to determine the effects of kingpin inclination angle and wheel offset on various steering system performance measures. For each performance metric, a 2-variable (KPIA and wheel offset), 5-level DOE was performed using the full factorial matrix for a total of 25 tests for each performance metric.

This paper presents a methodology for predicting drum brake performance using FEA (finite element analysis) models considering both the mechanical-structural compliance and thermal effects. The methodology for brake torque prediction with FEA models considering the structural flexibility of the brake components alone has been established [1]. The frictional heat generated during braking causes thermoelastic distortion that modifies the contact pressure distribution at the drum-lining interface. In order to capture this thermal effect, a transient thermal analysis is conducted to predict the transient temperature distribution on the brake components. In the thermal analysis, the heat generated at the drum and lining interface is based on the pressure distribution from the compliant mechanical model. Also, the mechanical properties of the brake components as well as the lining friction are dependent on the temperature distribution.

Conducting effective drivetrain NVH (Noise, Vibration and Harshness) troubleshooting is difficult because its execution requires commanding knowledge and experience on complicated vehicle system interactions. This is especially true for commercial vehicles due to the wide variety of available powertrain and chassis configurations and broad spectrum of vehicle applications. Furthermore, access to revenue producing commercial vehicles is often limited. Problem solving must be carried out within a tight schedule. Under these circumstances, a practical drivetrain NVH troubleshooting guide will come in handy. The objective of this paper is to document the “know-how” we have learned. Subjects covered in the discussions are underlying physics, problem diagnosis, solutions, and problem avoidance.

Although computer models for vehicle and sub-system performance simulations have been developed and used extensively in the past several decades, there is currently a need to enhance the overall availability of these types of tools. Increasing demands on vehicle performance targets have intensified the need to obtain rapid feedback on the effects of vehicle modifications throughout the entire development cycle. At the same time, evolution of the PC and development of Web-based applications have contributed to the availability, accessibility, and user-friendliness of sophisticated computer analysis. Web engineering is an ideal approach in supporting globalization and is a cost-effective design-analysis integration business strategy. There is little doubt that this new approach will have positive impacts on product cost, quality, and development cycle time. This paper will show how Microsoft Excel and the Web can be powerful and effective tools in the development process.

Automotive transmission design quality is generally judged by the vehicle's performance. Its acceleration, gradeability, maximum speed, terminal speeds, fuel economy and emissions provide these measures. These performance characteristics are optimized through the design process. This process, however, is iterative in nature and requires informed decision making to produce a design that is cost effective and excels in quality. In modern engineering, computer simulation plays an important role in the product design and development process. This paper provides a case study of the design and analysis of a heavy truck automatic transmission. It demonstrates the use of computer simulation models in generating and evaluating innovative design ideas.

Premature parts breakdown in the final drive of heavy vehicle powertrains in vehicles equipped with high power retarders leads one to believe that the coasting mode gear forces may be higher than anticipated. There is limited experimental data that supports this hypothesis in the observation of high bearing load and gear bending stress in coast mode. However, without an in-depth analysis, it is unclear exactly how the high load is generated. There are several suggested causes: friction, gear geometry, and system compliance. The present study focuses on the effects of hypoid gear friction on the powertrain. Analytical expressions of the gear friction vector as a function of gear pressure, pitch and spiral angles, spiral hand and directions of rotation and applied torque were derived and examined. Attempts were made to correlate test-measured quantities and results from analytical models with and without the consideration of gear friction.

The effectiveness of computer simulation modeling for product development support is evidenced by its wide-spread usage. For example, finite element analysis (FEA), has been found indispensable for reducing product development cycle time and cost as well as enhancing product quality. Along with other pertinent information, accurately defined loads are necessary for conducting effective FEA for product design optimizations. FEA results using rough estimated loads often do not provide a good basis for design improvement. A better approach is to define loads through system simulation modeling. The development of such a model involves the synthesis of a wide range of product design knowledge along with a systematic process for model correlation. As the technology becomes matured, there is a strong drive to make the process more efficient by integrating the different types of simulation techniques. Two examples are given in this paper.

Contact stress analysis or surface fatigue life prediction is a subject frequently encountered in powertrain component designs. Examples are the design of gears, bearings, cams, and load ramps. In many cases, design evaluations rely on simple analysis, component supplier's suggestions, and prototype testing. One viable technology trend in modern engineering, however, is to use computer simulation and analysis as a design guide. It is universally acknowledged that up-front computer-aided-engineering (CAE) will reduce the product development cycle time and cost, and improve product quality. In addition, this approach provides a good platform for technology growth. Scattered examples on surface durability analytical modeling techniques are available in the literature. But, the most suitable engineering tools for routine product design support are yet to be developed. Currently, a semi-empirical approach is widely used in the industry.