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This presentation proposes an approach to use ABS wheel speed sensor signals together with other vehicle state information from a brake control module to detect an unbalanced tire or tires in real-time. The proposed approach consists of two-stage algorithms that mix a qualitative method using band-pass filtering with a quantitative parameter identification using conditional least squares. This two-stage approach can improve the robustness of tire imbalance or imbalances. The proposed approach is verified through vehicle testing and the test results show the effectiveness of the approach. Presenter Jianbo Lu, Ford Motor Co.

In this paper a diagnostic design process is proposed for developmental vehicles where mainstream design process is not well-suited. First a review of current practice in on-board vehicle fault diagnostics design is presented with particular focus on the application of this process to the development of the Ford Escape Hybrid Electric Vehicle (HEV) program and a demonstration Fuel Cell Electric Vehicle (FCEV) program. Based on the review and evaluation of these experiences, a new tool for diagnostics design is proposed that promises to make the design more traceable, to reduce the repetition of work, and to improve understandability and reuse.

This paper presents the extended Kalman filter-based sideslip angle estimator design using a nonlinear 5DoF single-track vehicle dynamics model with stochastic modeling of tire forces. Lumped front and rear tire forces have been modeled as first-order random walk state variables. The proposed estimator is primarily designed for vehicle sideslip angle estimation; however it can also be used for estimation of tire forces and cornering stiffness. This estimator design does not rely on linearization of the tire force characteristics, it is robust against the variations of the tire parameters, and does not require the information on coefficient of friction. The estimator performance has been first analyzed by means of computer simulations using the 10DoF two-track vehicle dynamics model and underlying magic formula tire model, and then experimentally validated by using data sets recorded on a test vehicle.

When a vehicle with a partially filled fuel tank undergoes sudden acceleration, braking, turning or pitching motion, fuel sloshing is experienced. It is important to establish a CAE methodology to accurately predict slosh phenomenon. Fuel slosh can lead to many failure modes such as noise, erroneous fuel indication, irregular fuel supply at low fuel level and durability issues caused by high impact forces on tank surface and internal parts. This paper summarizes activities carried out by the fuel system team at Ford Motor Company to develop and validate such CAE methodology. In particular two methods are discussed here. The first method is Volume Of Fluid (VOF) based incompressible multiphase Eulerian transient CAE method. The CFD solvers used here are Star CD and Star CCM+. The second method incorporates Fluid-Structure interaction (FSI) using Arbitrary Lagrangian-Eulerian (ALE) formulation.

In vehicle design, response surface model (RSM) is commonly used as a surrogate of the high fidelity Finite Element (FE) model to reduce the computational time and improve the efficiency of design process. However, RSM introduces additional sources of uncertainty, such as model bias, which largely affect the reliability and robustness of the prediction results. The bias of RSM need to be addressed before the model is ready for extrapolation and design optimization. This paper further investigates the Bayesian inference based model extrapolation method which is previously proposed by the authors, and provides a systematic and integrated stochastic bias corrected model extrapolation and robustness design process under uncertainty. A real world vehicle design example is used to demonstrate the validity of the proposed method.

This paper proposes an approach that characterizes a driver's driving behavior and style in real-time during car-following drives. It uses an online learning of the evolving Takagi-Sugeno fuzzy model combined with the Markov model. The inputs fed into the proposed algorithm are from the measured signals of on-board sensors equipped with current vehicles, including the relative distance sensors for Adaptive Cruise Control feature and the accelerometer for Electronic Stability Control feature. The approach is verified using data collected using a test vehicle from several car-following test trips. The effectiveness of the proposed approach has been shown in the paper.

Designing a vehicle body involves meeting numerous performance requirements related to different attributes such as NVH, Durability, Safety, and others. Multi-Disciplinary Optimization (MDO) is an efficient way to develop a design that optimizes vehicle performance while minimizing the weight. Since a body design evolves in course of the product development cycle, it is essential to repeat the MDO process several times as a design matures and more accurate data become available. This paper presents a real life application of the MDO process to reduce weight while optimizing performance over the design cycle of the 2015 Mustang. The paper discusses the timing and results of the applied Multi-Disciplinary Optimization process. The attributes considered during optimization include Safety, Durability and Body NVH. Several iterations of MDO have been performed at different milestones in the design cycle leading to a significant weight reduction of the already optimized design by over 16kg.

Knowledge mapping is a first and mandatory step in creation of system architecture. This paper considers the conceptual modeling of automotive systems, and discusses the creation of a knowledge-based model with respect to the Object Process Methodology an approach used in designing intelligent systems by depicting them using object models and process models. With this knowledge, systems engineer should consider what a product is comprised of (its structure), how it operates (its dynamics), and how it interacts with the environment. As systems have become more complex, a prevalent problem in systems development has been the number of accruing errors. A clearly defined and consistent mapping of knowledge regarding structure, operation and interaction is necessary to construct an effective and useful system. An interactive, iterative and consistent method is needed to cope with this complex and circular problem.

The ISO TC22/SWG2 - Brake Lining Committee established a task force to determine and analyze root causes for variability during dynamometer brake performance testing. SAE paper 2010-01-1697 “Brake Dynamometer Test Variability - Analysis of Root Causes” [1] presents the findings from the phases 1 and 2 of the “Test Variability Project.” The task force was created to address the issue of test variability and to establish possible ways to improve test-to-test and lab-to-lab correlation. This paper presents the findings from phase 3 of this effort-description of factors influencing test variability based on DOE study. This phase concentrated on both qualitative and quantitative description of the factors influencing friction coefficient measurements during dynamometer testing.

This paper proposes an approach to use ABS wheel speed sensor signals together with other vehicle state information from a brake control module to detect an unbalanced tire or tires in real-time. The proposed approach consists of two-stage algorithms that mix a qualitative method using band-pass filtering with a quantitative parameter identification using conditional least squares. This two-stage approach can improve the robustness of tire imbalance or imbalances. The proposed approach is verified through vehicle testing and the test results show the effectiveness of the approach.

The Reverse Braking Assist (RBA) feature is designed to automatically activate full braking in a backing vehicle. When this feature activates, a backing vehicle is suddenly stopped or may slide to a stop. During this process, an understanding of the driver's behavior may be useful in the design of an appropriate human-machine-interface (HMI) for the RBA. Several experimental studies were done to examine driver behavior in response to an unexpected and automatic braking event while backing [1]. Two of these studies are reported in this paper. A 7-passenger Crossover Utility Vehicle was fitted with a rear-view camera, a center-stack mounted LCD screen, and ancillary recording devices. In the first study, an object was suddenly placed in the path of a backing vehicle. The backing vehicle came to a sudden and complete stop. The visual image of the backing path on the LCD prominently showed that an obstacle was present in the backing path of the vehicle.

The primary objective of design is to achieve the target value of its function. While principles and techniques of Robust Design address the issue of achieving target values in the presence of different types of variations and disturbances, there exists a unique challenge in achieving design targets when multiple response functions are interrelated. In order to overcome the challenge, we must avoid functional couplings and obtain the interrelationship structure as flexible as possible. In the Axiomatic Design process, such interrelationships are represented by coupling terms in a design matrix. From the targeting aspect of design, it is important to achieve a desirable design matrix structure to, first, avoid any functional coupling in a design matrix and, secondly, maximize allowable sequences of adjusting DPs.

This paper assesses the potential improvement of automotive powertrain technologies 25 years into the future. The powertrain types assessed include naturally-aspirated gasoline engines, turbocharged gasoline engines, diesel engines, gasoline-electric hybrids, and various advanced transmissions. Advancements in aerodynamics, vehicle weight reduction and tire rolling friction are also taken into account. The objective of the comparison is the potential of anticipated improvements in these powertrain technologies for reducing petroleum consumption and greenhouse gas emissions at the same level of performance as current vehicles in the U.S.A. The fuel consumption and performance of future vehicles was estimated using a combination of scaling laws and detailed vehicle simulations. The results indicate that there is significant potential for reduction of fuel consumption for all the powertrains examined.

Each more the consumer uses the vehicle noise, vibration, and harshness (NVH) attributes to define the vehicle model when purchasing a car, so the sound quality development is very important to guarantee the automaker success in a competitive market. Several vehicle components contribute to the consumer sound quality perception, as engine, gearbox and exhaust systems. So those components improvement is necessary in order to enrich the sound perception. In this article will be developed a case study that evaluates the contribution and the characteristics of the irradiated noise from the power steering system, which was classified as moan, whine and hiss noise, defines objectively each phenomena and evaluate the proposed systems.

Improvement of engine fuel efficiency through the use of low friction engine oils is a major task in engine lubrication research. This friction reduction can be achieved by improving the rheological characteristics and elastohydrodynamic (EHD) properties of engine oils, and by controlling boundary chemical interactions between oil-based additives and lubricated components in the engine. In order to achieve minimal frictional power loss under all lubrication regimes, engine tribological systems must be designed to effectively use advanced lubricant technology, material and surface modifications. This paper presents results of cooperative research addressing opportunities for minimizing friction through extension of hydrodynamic lubrication regime in lubricated components using various formulation approaches. A set of experimental oils has been evaluated using laboratory test rigs that simulate hydrodynamic, EHD, mixed and boundary lubrication.

There are a number of benefits from Ford Motor Company's participation in motorsports. This paper will describe how an engineering team developed a CAE process to assist in the design of a race car to meet impact requirements, with the technology transfer benefit of improved impact performance of composite structures in passenger cars. In 1997/98, a CAE process was developed and applied in the design and test of Formula One race car composite impact structures. For this particular engineering effort, a Ford proprietary software program, COMP-COLLAPSE, was the primary analysis tool that was utilized to successfully predict impact performance. As a result, COMP-COLLAPSE was used extensively in the design of race car composite impact structures. There were two beneficiaries from this effort: Race Vehicles: Improved vehicle impact performance as well as design improvement in crush efficiency, packaging, weight, and manufacturing.

Current road vehicles have tendency of use softer suspension springs to improve ride comfort, but as a moving device with suspension system, vehicles have other parts that can affect attributes for comfort perception, and is necessary the correct definition of which one should be modified to address the comfort issue and avoid impact in attributes for stability. Usually springs are not the main responsible for bad comfort behavior, but shock absorbers and bushings are. A typical passenger car shows a wide possibility of loads carriage and how to set up correctly the suspensions considering its tradeoffs and brand DNA is the main issue.

This work presents a statistical approach for simulation based on Monte Carlo method. As an exercise of the method a CAE vehicle dynamics model was specifically created to evaluate the likelihood to meet a given target driving a maneuver for given inputs variations. In the exercise, three different inputs were chosen as stochastic inputs (also called noise factors) and all relevant information about their statistics has been raised, based in components information. The chosen inputs are: front/rear dampers curves, front/rear ride heights and tire surface temperature. A brief description of the Monte Carlo technique is presented. The choice of this method is due to the reduced number of simulations required to have a given accuracy in comparison with other approaches, especially for multivariable system. As output variable for the exercise, the tire patch height was chosen and the resulting probability density function of it is presented.

In South America and other emerging markets sound package development is limited by the cost and weight of its components. Reaching the right balance between cost and a good NVH performance provides an important competitive advantage, therefore any achieved design opportunities can be replicated to other vehicle lines and markets. In this work the main noise transmission paths are verified by evaluating the contribution of sound package components to noise attenuation in two cases, initially from the tire contact patch through vehicle body to a number of positions within the vehicle interior and, next, from the engine compartment, by placing a High Frequency Sound Source (HFSS) at engine faces to the same vehicle interior positions. The main objective is to optimize sound package distribution and to prioritize which areas should have the sound package reinforced in order to improve Tire and Engine noise reduction.

The existing vehicle designs exhibit a high level of coupling. For instance the coupling in the suspension and steering systems manifests itself through the change in wheel alignment parameters (WAP) due to suspension travel. This change in the WAP causes directional instability and tire-wear. The approach of the industry to solve this problem has been twofold. The first approach has been optimization of suspension link lengths to reduce the change in WAP to zero. Since this is not possible with the existing architecture, the solution used is the optimization of the spring stiffness K to get a compromise solution for comfort (which requires significant suspension travel and hence a soft spring) and directional stability (which demands least possible change in wheel alignment parameters and hence a stiff spring).