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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.

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.

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.

In the thermal expansion valve (TXV) refrigerant system, transient high-pitched whistle around 6.18 kHz is often perceived following air-conditioning (A/C) compressor engagements when driving at higher vehicle speed or during vehicle acceleration, especially when system equipped with the high-efficiency compressor or variable displacement compressor. The objectives of this paper are to conduct the noise source identification, investigate the key factors affecting the whistle excitation, and understand the mechanism of the whistle generation. The mechanism is hypothesized that the whistle is generated from the flow/acoustic excitation of the turbulent flow past the shallow cavity, reinforced by the acoustic/structural coupling between the tube structural and the transverse acoustic modes, and then transmitted to evaporator. To verify the mechanism, the transverse acoustic mode frequency is calculated and it is coincided to the one from measurement.

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.

In recent years, rapid and significant advances in fuel cell technology, together with advances in power electronics and control methodology, has enabled the development of high performance fuel cell powered electric vehicles. A key advance is that the low temperature (80°C) proton-exchange-membrane (PEM) fuel cell has become mature and robust enough to be used for automotive applications. Apart from the apparent advantage of lower vehicle emission, the overall fuel cell vehicle static and dynamic performance and power and energy efficiency are critically dependent on the intelligent design of the control systems and control methodologies. These include the control of: fuel cell heat and water management, fuel (hydrogen) and air (oxygen) supply and distribution, electric drive, main and auxiliary power management, and overall powertrain and vehicle systems.

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.

As automotive manufacturers continue to increase their use of thermoplastics for interior and exterior components, there is a likelihood of squeaks due to material contacts. To address this issue, Ford's Body Chassis NVH Squeak and Rattle Prevention Engineering Department has developed a tester that can measure friction, and any accompanying audible sound, as a function of sliding velocity, normal load, surface roughness, and environmental factors. The Ford team has been using the tester to address manufacturing plant issues and to develop a database of polymeric material pairings that will be used as a guide for current and future designs to eliminate potential noise concerns. Based upon the database, along with a physical property analysis of the various plastic (viscoelastic) materials used in the interior, we are in the process of developing an analytical model which will be a tool to predict frictional behavior.

Piston slap is a problem that plagues many engines. One of the most difficult aspects of designing to eliminate piston slap is that slight differences in operating conditions and in part geometries from build to build can create large differences in the magnitude of piston slap. In this paper we will describe a design for robustness CAE approach to eliminating piston slap. This approach considers the variations of the significant control factors in the design, e.g. piston pin offset, piston skirt design, etc. as well as the variation in the noise factors the system is subjected to, e.g. assembly clearance, skirt collapse, peak cylinder pressure, cylinder pressure rise rate, and location of peak cylinder pressure. Using analytical knowledge about how these various factors impact the generation of piston slap, a piston design for low levels of piston slap can be determined that is robust to the various noise factors.

The last ten years have experienced a massive integration of consumer electronics devices in vehicles such as mobile phones, audio and video players, USB devices, and internet access capability. Consumers are now demanding the integration of portable and home devices to vehicle systems transforming it to an extension of the home and office thus providing entertainment and connectivity to both short and long trips The integration of devices that were not designed or specified to operate in the vehicle environment has imposed challenges to the engineers designing vehicle electronics systems in particular to the EMC engineers. The need to design the subsystems that are completely integrated with the consumer electronics devices and also compliant with the car makers current specifications has proven to be a major issue due to the fact that one of the components, the consumer electronic devices, cannot be controlled.

For purposes of reducing development time, cost and risk, the majority of new vehicles are derived strongly or at least generally from a surrogate vehicle, often of the same general size or body style. Previous test data and lessons learned can be applied as a starting point for design of the new vehicle, especially at early phases of the design before definite design decisions have been finalized and before prototype of production test hardware is available. This is true as well of vehicle NVH development where most new vehicles being developed are variants of existing vehicles for which the main noise transfer paths from sources of interest are already understood via test results and existing targets. The NVH targets for new vehicles are defined via benchmarking, market considerations, and other higher-level decisions. The objective is then to bridge the gap between test data from surrogate vehicles to direct support of the NVH development of new vehicle programs.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Within the automotive industry, more and more of this validation testing is being performed using Hardware-in-the-Loop (HIL) simulators to automate the extensive test sequences. A HIL simulation typically mates the physical PCS to a closed-loop real time computer simulation of a powertrain. Interfacing the physical PCS hardware to a powertrain simulation requires the HIL simulator to have extensive signal input/output (I/O) electronics and simulated actuator electrical loading.

Two critical milestones that must be achieved during concept design are 1) definition of a product architecture that meets performance, producibility, and strategic objectives, and 2) estimation of the integration risk in each candidate concept. This paper addresses these issues by describing the role played by the producibility members of an Integrated Product Team (IPT) during concept design. Our focus is on the execution of the what we call the “chain method”, which illustrates the structure of function delivery in a concept in a simple pictorial way and helps the IPT to understand the advantages or disadvantages of using a modular or an integral product architecture. The producibility members play a central role in capturing and evaluating the chains for different candidate concepts and decompositions.

Validation of the Ford General Engine SIMulation program (GESIM) with measured firing data from a modified single cylinder Ricardo HYDRA research engine is described. GESIM predictions for peak cylinder pressure and burn duration are compared to test results at idle operating conditions over a wide range of valve overlap. The calibration of GESIM was determined using data from only one representative world-wide operating point and left unchanged for the remainder of the study. Valve overlap was varied by as much as 36° from its base setting. In most cases, agreement between model and data was within the accuracy of the measurements. A cycle simulation computer model provides the researcher with an invaluable tool for acquiring insight into the thermodynamic and fluid mechanical processes occurring in the cylinder of an internal combustion engine.

This paper begins with a comparison of the automotive power supply and loads in the early 1950's (near the end of the six-volt era) to the modern counterpart in the early 1990's (possibly near the end of the 12-volt era). A typical power supply specification sheet is developed based on the in-vehicle performance characteristics. From this summary, two attributes are noted: first, the system voltage is not very stable and second, transient protection is limited. With this awareness and the knowledge that the power supply of the future will need architectural change, a review of the design assumptions using a total system view and a long term outlook is advanced. Using a rule based design process and employing available technology to enhance the power system architecture, a number of elements are proposed for consideration in new designs.

A new, systematic, sensitivity based design process for weight reduction is presented. Traditionally, a trial and error method is used when a design fails to meet the weight and the design criteria, which often conflict. This old approach not only is time and cost consuming but also does not provide insight into structural behavior. This proposed process uses state-of-the-art technologies such as design sensitivity analysis, numerical optimization, graphical user interface, etc. It handles multi-discipline design criteria simultaneously and provides design engineers insight into structural responses for frequency, durability, and stiffness concerns and a means for systematic weight reduction and quality improvement. The new design process has been applied for the weight reduction of advanced truck frame designs. Results show that a significant weight savings has been achieved while all design criteria are met.

A flow network method was developed to predict the underhood temperature distribution of an automobile. The method involves the solution of simplified energy and momentum equations of the air flow in control volumes defined by subdividing the air space between the surfaces of the underhood components and the front-end geometry. The control volumes are interconnected by ducts with branches and bends to form a flow network. Conservation of mass and momentum with appropriate pressure-loss coefficients leads to a system of algebraic equations to be solved for the flow rates through each volume. The computed flow rates are transferred to a thermal model to calculate the temperatures of the air and the major vehicle components that affect the underhood environment. The method was applied to a 1986 3.0L Taurus and compared with vehicle experiments conducted in a windtunnel.

The paper briefly reviews the current and future needs for automotive electronic packaging technology and the related reliability issues. Reliability approaches based upon physics-of-failure are discussed, and an example is given to illustrate the importance of understanding the root cause of failure and the application of a state-of-the-art approach to life prediction of leadless solder joints under thermal cycling. An introduction is also given to the recent development of the CAIR (Computer Aided Interconnect Reliability) system developed at Ford for reliability prediction of solder interconnects in automotive electronic packaging. The system integrates a number of software modules using a user interface and allows for evaluation of critical design parameters within a short period of time. The system is intended to implement the “prevention mode” into the product design process to meet the increasing reliability demand and to reduce cost and cycle time.

Dimensional variability must be managed. Assembly plant installation processes which require operator adjustment result in random, unpredictable variability. On the other hand, processes which use locators and quality controlled components eliminate operator adjustments. This results in managed variability with repeatable and dimensionally consistent end products. The 1994½ Windstar mini-van incorporated locators with a detailed component quality control plan and then went one step further. Dimensional variability was managed and verified during the design process to ensure that every vehicle produced would meet customer quality standards. To verify that the Windstar would achieve the customer quality standards, by design, a full vehicle dimensional variability model was developed. The body structure, interior trim, major instrument panel components, suspension, steering and various subsystems were modeled.