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With the inception of model-based design and automatic code generation, many organizations are developing controls and diagnostics algorithms in model-based development tools to meet customer and regulatory requirements. Advances in model-based design have made it easier to generate C code from models and help software engineers streamline their workflow. Typically, after the software has been developed, the models are handed over to a calibration team responsible for calibrating the features to meet specified customer and regulatory requirements. However, once the models are handed over to the calibration team, the calibration engineers are unaware of how to calibrate the features because documentation is not available. Typically, model documentation trails behind the software process because it is created manually, most of this time is spent on formatting. As a result, lack of model documentation or up-to date documentation causes a lot of pain for OEM’s and Tier 1 suppliers.

In a CAS system, the distance and relative velocity between front and host vehicles are estimated to calculate time-to-collision (TTC). The distance estimates by different methods will certainly include noise which should be removed to ensure the accuracy of TTC calculations. Kalman filter is a good tool to filter such type of noise. Nevertheless, Kalman filter is a model based filter, which means a correct model is important to get the good filtering results. Usually, a vehicle is either moving with a constant velocity (CV) or constant acceleration (CA) maneuvers. This means the distance data between front and host vehicles can be described by either constant velocity or constant acceleration model. In this paper, first, CV and CA models are used to design two Kalman filters and an interacting multiple model (IMM) is used to dynamically combine the outputs from two filters.

The paper describes a new strategy for real-time sensor diagnostics that is based on the statistical correlation of various sensor signal pairs. During normal fault-free operation there is a certain correlation between the sensor signals which is lost in the event of a fault. The proposed algorithm quantifies the correlation between sensor signal pairs using real-time scalar metrics based on the Mahalanobis-distance concept. During normal operation all metrics follow a similar pattern, however in the event of a fault; metrics involving the faulty sensor would increase in proportion to the magnitude of the fault. Thus, by monitoring this pattern and using a suitable fault-signature table it is possible to isolate the faulty sensor in real-time. Preliminary simulation results suggest that the strategy can mitigate the false-alarms experienced by most model-based diagnostic algorithms due to an intrinsic ability to distinguish nonlinear vehicle behavior from actual sensor faults.

This work discusses the development of SAE procedure J2747, “Hydraulic Pump Airborne Noise Bench Test”. This is a test procedure describing a standard method for measuring radiated sound power levels from hydraulic pumps of the type typically used in automotive power steering systems, though it can be extended for use with other types of pumps. This standard was developed by a committee of industry representatives from OEM's, suppliers and NVH testing firms familiar with NVH measurement requirements for automotive hydraulic pumps. Details of the test standard are discussed. The hardware configuration of the test bench and the configuration of the test article are described. Test conditions, data acquisition and post-processing specifics are also included. Contextual information regarding the reasoning and priorities applied by the development committee is provided to further explain the strengths, limitations and intended usage of the test procedure.

A new optimal control strategy for dealing with braking actuator failures in a vehicle equipped with a brake-by-wire and steer-by- wire system is described. The main objective of the control algorithm during the failure mode is to redistribute the control tasks to the functioning actuators, so that the vehicle performance remains as close as possible to the desired performance in spite of a failure. The desired motion of the vehicle in the yaw plane is determined using driver steering and braking inputs along with vehicle speed. For the purpose of synthesizing the control algorithm, a non-linear vehicle model is developed, which describes the vehicle dynamics in the yaw plane in both linear and non-linear ranges of handling. A control allocation algorithm determines the control inputs that minimize the difference between the desired and actual vehicle motions, while satisfying all actuator constraints.

This study examines the effectiveness of gaseous oxygen at preventing embrittlement in steel associated with exposure to gaseous hydrogen under static loading conditions. Notched C-ring samples machined from 4340 steel and heat treated to HRC 51-53 were used to test the neutrality of an oxygen-hydrogen gas mixture similar to that which may be used as a generant in an air bag inflator. The 29 percent oxygen to hydrogen gas ratio of the gas mixture was found to be sufficient to protect the steel from hydrogen embrittlement under static loading conditions. This would indicate that any steel with a hardness of HRC 51 or lower would be safe to use in gas-based air bag inflators containing a oxygen to hydrogen gas ratio of 29 percent or higher.

This paper describes a robust engineering DOE (design of experiment) completed by hydraulic simulation of a Variable Cam Phaser System based on an L4 IC engine. The robust engineering study focused on the high temperature and low speed portions of overall engine operating conditions where the cam phase rates are slow and oscillation is high. The analysis included a preliminary DOE with multiple noise variables used as the control factors in order to quantify and compound the factors into just two noise levels; best and worst conditions. Following the noise DOE, a larger DOE study was completed with 16 control variables including phaser, oil control valve and various engine parameters. It was run at 3 engine rpm (signal levels), 2 noise levels, and was analyzed for 3 responses (advancing rate, retarding rate, and oscillation amplitude while holding an intermediate position). These DOE experiments determined potential gains for each design proposal.

The laboratory test method commonly known as “random vibration” is almost always used for Squeak & Rattle testing in today's automotive applications due to its obvious advantages: the convenience in simulating the real road input, the relatively low cost, and efficiency in obtaining the desired test results. Typically, Loudness N10 is used to evaluate the Squeak & Rattle (S&R) performance. However, due to the nature of random distribution of the excitation input, the repeatability of the loudness N10 measurements may vary significantly. This variation imposes a significant challenge when one is searching for a fine design improvement solution in minimizing S&R noise, such as a six-sigma study. This study intends to investigate (1) the range of the variations of random vibration control method as an excitation input with a given PSD, (2) the possibility of using an alternate control method (“time-history replication”) to produce the vibration of a given PSD for a S&R evaluation.

This paper reviews the current strategies for physical prototyping of Magnesium instrument panel (I/P) structures. Bottlenecks in the traditional physical prototype based product development process are discussed. As demand for fast-to-market and cost-reduction mounts, virtual prototyping becomes increasingly important in meeting the timing and performance goals. A virtual prototyping methodology is presented in this paper to enable high performance Magnesium I/P structures in Safety, NVH, and initial part quality aspects. Examples of Finite Element Analysis (FEA) results and correlations are included.

Execution of a software safety program is an accepted best practice to help verify that potential software hazards are identified and their associated risks are mitigated. Successful execution of a software safety program involves selecting and applying effective analysis methods and tasks that are appropriate for the specific needs of the development project and that satisfy software safety program requirements. This paper describes the effective application of a set of software safety methods and tasks that satisfy software safety program requirements for many applications. A key element of this approach is a tightly coupled fault tree analysis and failure modes and effects analysis. The approach has been successfully applied to several automotive embedded control systems with positive results.

A steering wheel is an indispensable component in an automobile. Although the steering wheel was invented about one hundred years ago and its structure has since become more and more complex with numerous innovations, documented analysis on steering wheel performance is very limited. Today, a steering wheel is not only a wheel that controls where your car goes; it also plays an important role in a vehicle occupant protection system. Therefore, many requirements have to be met before a steering wheel goes into production. With the development of computational mechanics and increasing computer capability, it has become much easier to evaluate the steering wheel performance in a totally different way. Instead of running prototype tests, steering wheel designs can be modeled virtually in various scenarios using finite element analysis, thus facilitating the development cycle.

As automotive electronic control systems continue to increase in usage and complexity, the challenges for developing automotive diagnostics also increase. Reduced development cycle times, the increased significance of diagnostics for safety critical systems, and the integration of vehicle systems across multiple control systems all add to the tasks of developing diagnostics for the automobiles of today and tomorrow. Addressing automotive diagnostics now requires the Tier 1 supplier to utilize a formal diagnostic development methodology. There are also opportunities for Tier 1 suppliers to add value by developing vehicle-level supervisory diagnostic strategies, in addition to subsystem and system-level diagnostic strategies. There is also a prospect to provide strategies and tools to enhance service at the vehicle level. This paper proposes an approach for Tier 1 suppliers to address diagnostic and service issues at the component, system, and vehicle level.

Low frequency drum brake squeal is often very intense and can cause high levels of customer complaints. During a noise event, vehicle framework and suspension components are excited by the brake system and result in a violent event that can be heard and felt during a brake application. This paper illustrates the experimental and analytical studies on a low frequency drum brake squeal problem that caused high warranty cost. First the environmental condition was identified and noise was reproduced. Vehicle tests were performed and operating deflection shapes were acquired. The sensitivity of the lining material to different environmental conditions was investigated. With the use of complex eigenvalue method, models were constructed to obtain further understanding of the phenomena. Finally, the squeal mechanism of a drum brake system is discussed and various solution techniques for low frequency drum brake noise are evaluated.

The perceived interior noise has been one of the major driving factors in the design of automotive interior assemblies. Buzz, Squeak and Rattle (BSR) issues are one of the major contributors toward the perceived quality in a vehicle. Traditionally BSR issues have been identified and rectified through extensive hardware testing. In order to reduce the product development cycle and minimize the number of costly hardware builds, however, one must rely on engineering analysis and simulation upfront in the design cycle. In this paper, an analytical and experimental study to identify potential BSR locations in a cockpit assembly is presented. The analytical investigation utilizes a novel and practical methodology, implemented in the software tool Nhance.BSR, for identification and ranking of potential BSR issues. The emphasis here is to evaluate the software for the BSR predictions and the identification of modeling issues, rather than to evaluate the cockpit design itself for BSR issues.

This paper proposes the concept of Generalized Diagnostic Component (GDC) and presents a modular fault diagnostic strategy for safety critical automotive systems. The diagnostic strategy makes full use of hierarchical techniques, integrates the generalized diagnostic design into all-purpose vehicle diagnoses based on reconfiguration of the GDCs, and inherits the model-based diagnostic algorithms developed for Steering/Braking-By-Wire systems. The GDC-based approach simplifies the design and integration of diagnostics in complex dynamical control systems, and has been successfully implemented in an eight degrees of freedom NAVDyn (Non-Linear Analysis of Vehicle Dynamics) simulation model using Matlab Simulink. The simulation results are provided in this paper to testify that the diagnostic strategy and implementation are feasible, efficient and dependable.

This paper reviews the state of the art on analytical design of cockpit modules in two most crucial performance categories: safety and comfort. On safety, applications of finite element analysis (FEA) for achieving robust designs that meet FMVSS 201, 208 and 214 requirements and score top frontal and side NCAP star-ratings are presented. On comfort, focus is placed on Noise, Vibration and Harshness (NVH) performance. Cutting-edge analytical tools for Buzz, Squeak and Rattle (BSR) avoidance and passenger compartment noise reduction are demonstrated. Most of the analytical results shown in this paper are based on the development work of a real-life application program. Correlations between the analytical results and physical test results are included. Examples of Computational Fluid Dynamics (CFD) analysis for climate control are also included. At the end, the road map toward 100 percent virtual prototyping and validation is presented.

Computer modeling and simulation have become one of the primary methods for development and design of automobile occupant protection systems (OPS). To ensure the accuracy and reliability of a math-based OPS design, the correlation quality assessment of mathematical models is essential for program success. In a typical industrial approach, correlation quality is assessed by comparing chart characteristics and scored based on an engineer's modeling experience and judgment. However, due to the complexity of the OPS models and their responses, a systematic approach is needed for accuracy and consistency. In this paper, a correlation grading methodology for the OPS models is presented. The grading system evaluates a wide spectrum of a computer model's performances, including kinematics, dynamic responses, and dummy injury measurements. Statistical analysis is utilized to compare the time histories of the tested and simulated dynamic responses.

The interaction between the deploying airbag and the Out-Of-Position (OOP) occupants remains a challenge in occupant protection system simulations. The integration of Computational Fluid Dynamics (CFD) analysis into Finite Element (FE) airbag model is a helpful and important tool to address this challenge. Three major commercial crash simulation software packages widely used in the automotive safety industry, LS-DYNA, MADYMO and PAM-CRASH are in the process of implementing different approaches for airbag CFD simulation. In this study, an attempt was made to evaluate and compare the CFD integrated airbag models in these software packages. Specially designed tests were conducted to study and capture the pressure distribution inside a flat airbag and the test results were used for the evaluation. Strengths and limitations of each software package are discussed in this paper.

A new single-brick Ba + alkali metals NOx-Trap catalyst has been developed to replace a two-brick NOx-Trap system containing a downstream three-way catalyst. Major development efforts include: 1) platinum group metals selection for higher HC oxidation with potassium-containing washcoat, 2) alumina and ceria selection, and Rh architecture design for more efficient NOx reduction and 3) NiO to suppress H2S odor. Mitsubishi Motors' 1.8L GDI™ with this Delphi new NOx-Trap catalyst with H2S control achieves J-LEV standard with less cost and lower backpressure compared to the previous model. It is further discovered that incorporation of NiO into the NOx-Trap washcoat is effective for H2S control during sulfur purge but has a negative impact on thermal durability and sulfur resistance. Further study to improve this trade-off has been made and preliminary results of an advanced washcoat design are presented in this paper. Details will be reported in a future publication.

A squeal analysis on a front disc brake is presented here utilizing the new complex eigenvalue capability in ABAQUS/Standard. As opposed to the direct matrix input approach that requires users to tailor the friction coupling matrix, this method uses nonlinear static analyses to calculate the friction coupling prior to the complex eigenvalue extraction. As a result, the effect of non-uniform contact pressure and other nonlinear effects are incorporated. Friction damping is used to reduce over-predictions and the velocity dependent friction coefficient is defined to contribute negative damping. Complex eigenvalue predictions of the example cases show very good correlation with test data for a wide range of frequencies. Finally, the participation of rotor tangential modes is also discussed.