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Three computational gas and fluid dynamic methods, CV/UP (Control Volume/Uniform Pressure), CPM (Corpuscular Particle Method), and ALE (Arbitrary Lagrangian and Eulerian), were investigated in this research in an attempt to predict the responses of side crash pressure sensors. Acceleration-based crash sensors have been used extensively in the automotive industry to determine the restraint system firing time in the event of a vehicle crash. The prediction of acceleration-based crash pulses by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crush zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side crash applications.

Vehicle fire investigators often use the existence of burn patterns, along with the amount and location of fire damage, to determine the fire origin and its cause. The purpose of this paper is to study the effects of ventilation location on the interior burn patterns and burn damage of passenger compartment fires. Four similar Ford Fusion vehicles were burned. The fire origin and first material ignited were the same for all four vehicles. In each test, a different door window was down for the duration of the burn test. Each vehicle was allowed to burn until the windshield, back glass, or another window, other than the window used for ventilation, failed, thus changing the ventilation pattern. At that point, the fire was extinguished. Temperatures were measured at various locations in the passenger compartment. Video recordings and still photography were collected at all phases of the study.

An eight-group taxonomy was created to classify real-world frontal crashes from the Crashworthiness Data System (CDS) component of the National Automotive Sampling System (NASS). Three steps were taken to develop the taxonomy: (1) frontal-impact towaway crashes were identified by examining 1985-2005 model year light passenger vehicles with Collision Deformation Classification (CDC) data from the 1995-2005 calendar years of NASS; (2) case reviews, engineering judgments, and categorization assessments were conducted on these data to produce the eight-group taxonomy; and (3) two subsets of the NASS dataset were analyzed to assess the consistency of the resulting taxonomic-group frequencies. “Full-engagement” and “Offset” crashes were the most frequent crash types, each contributing approximately 33% to the total. The group identified as “D, Y, Z No-Rail” was the most over-represented crash type for vehicles with at least one seriously-injured occupant.

This study demonstrates the use of pressure sensing technology to predict the crash severity of frontal impacts. It presents an investigation of the pressure change in the front structural elements (bumper, crush cans, rails) during crash events. A series of subsystem tests were conducted in the laboratory that represent a typical frontal crash development series and provided empirical data to support the analysis of the concept. The pressure signal energy at different sensor mounting locations was studied and design concepts were developed for amplifying the pressure signal. In addition, a pressure signal processing methodology was developed that relies on the analysis of the air flow behavior by normalizing and integrating the pressure changes. The processed signal from the pressure sensor is combined with the restraint control module (RCM) signals to define the crash severity, discriminate between the frontal crash modes and deploy the required restraint devices.

Described in this paper is a component test methodology to evaluate the door trim armrest performance in an Insurance Institute for Highway Safety (IIHS) side impact test and to predict the SID-IIs abdomen injury metrics (rib deflection, deflection rate and V*C). The test methodology consisted of a sub-assembly of two SID-IIs abdomen ribs with spine box, mounted on a linear bearing and allowed to translate in the direction of impact. The spine box with the assembly of two abdominal ribs was rigidly attached to the sliding test fixture, and is stationary at the start of the test. The door trim armrest was mounted on the impactor, which was prescribed the door velocity profile obtained from full-vehicle test. The location and orientation of the armrest relative to the dummy abdomen ribs was maintained the same as in the full-vehicle test.

This paper describes the development of a three-dimensional lumped-mass structure and dummy model to study barrier-to-car side impacts. The test procedures utilized to develop model input data are also described. The model results are compared to crash test results from a series of six barrier-to-car crash tests. Sensitivity analysis using the validated model show the necessity to account for dynamic structural rate effects when using quasi-statically measured vehicle crush data.

This study deals with passenger side restraint system design for frontal impact and four impact modes are considered in optimization. The objective is to minimize the Relative Risk Score (RRS), defined by the National Highway Traffic Safety Administration (NTHSA)'s New Car Assessment Program (NCAP). At the same time, the design should satisfy various injury criteria including HIC, chest deflection/acceleration, neck tension/compression, etc., which ensures the vehicle meeting or exceeding all Federal Motor Vehicle Safety Standard (FMVSS) No. 208 requirements. The design variables include airbag firing time, airbag vent size, inflator power level, retractor force level. Some of the restraint feature options (e.g., some specific features on/off) are also considered as discrete design variables. Considering the local variability of input variables such as manufacturing tolerances, the robustness and reliability of nominal designs were also taken into account in optimization process.

Optimization of heavy materials like steel, in order to create a lighter vehicle, it is a major goal among most automakers, since heavy vehicles simply cannot compete with a lightweight model's fuel economy. Thinking this way, this paper shows a case study where the Size Optimization technique is applied to a front floor reinforcement. The reinforcement is used by two different vehicles, a subcompact and a crossover Sport Utility Vehicle (SUV), increasing the problem complexity. The Size Optimization technique is supported by Finite Element Method (FEM) tools. FEM in Computer Aided Engineering (CAE) is a numerical method for solving engineering problems, and its use can help to optimize prototype utilization and physical testing.

Rear Window Buffeting (RWB) is the low-frequency, high amplitude, sound that occurs in many 4-door vehicles when driven 30-70 mph with one rear window lowered. The goal of this paper is to demonstrate that the mechanisms of RWB are similar to that of sun roof buffeting and to describe the results of several actions suspected in contributing to the severity of RWB. Finally, the results of several experiments are discussed that may lend insight into ways to reduce the severity of this event. A detailed examination of the side airflow patterns of a small Sport Utility Vehicle (SUV) shows these criteria exist on a small SUV, and experiments to modify the SUV airflow pattern to reduce RWB are performed with varying degrees of success. Based on the results of these experiments, design actions are recommended that may result in the reduction of RWB.

Customer perception of vehicle quality and safety is based on many factors. One important factor is the customers impression of the sounds produced by body and interior components such as doors, windows, seats, safety belts, windshield wipers, and other similar items like sounds generated automatically for safety and warning purposes. These sounds are typically harmonic or constant, and the relative level of perception, duration, multiplicity, and degree of concurrence of these sounds are elements that the customer will retain in an overall quality impression. Chime sounds are important to the customer in order to alert that something is not accomplished in a right way or for safe purposes. The chimes can be characterized by: sound level perception, frequency of the signal, shape of the signal, duration of the “beep” and the silence duration.

In this study, the occupant containment characteristics of automotive laminated safety glass in side window applications was evaluated through two full-scale, full-vehicle dolly rollover crash tests. The dolly rollover crash tests were performed on sport utility vehicles equipped with heat-strengthened laminated safety glass in the side windows in order to: (1) evaluate the capacity of laminated side window safety glass to contain unrestrained occupants during rollover, (2) analyze the kinematics associated with unrestrained occupants during glazing interaction and ejection, and (3) to identify laminated side window safety glass failure modes. Dolly rollovers were performed on a 1998 Ford Expedition and a 2004 Volvo XC90 at a nominal speed of 43 mph, with unbelted Hybrid II Anthropomorphic Test Devices (ATDs) positioned in the outboard seating positions.

A computational model of a mid-size sport utility vehicle was developed using MADYMO. The model includes a detailed description of the suspension system and tire characteristics that incorporated the Delft-Tyre magic formula description. The model was correlated by simulating a vehicle suspension kinematics and compliance test. The correlated model was then used to simulate a J-turn vehicle dynamics test maneuver, a roll and non-roll ditch test, corkscrew ramp and a lateral trip test, the results of which are presented in this paper. The results indicate that MADYMO is able to reasonably predict the vehicle and occupant responses in these types of applications and is potentially suited as a tool to help setup a suite of vehicle configurations and test conditions for rollover sensor testing. A suspension system sensitivity study is presented for the laterally tripped non-roll event.

An assessment tool was developed for rollover CAE signals evaluation to assess primarily the qualities of CAE generated sensor waveforms. This is a key tool to be used to assess CAE results as to whether they can be used for algorithm calibration and identify areas for further improvement of sensor. Currently, the method is developed using error estimates on mean, peak and standard deviation. More metrics, if necessary, can be added to the assessment tool in the future. This method has been applied to various simulated signals for laboratory-based rollover test modes with rigid-body-based MADYDO models.

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

This study applies a detailed finite element model of the human body to simulate occupant knee impacts experienced in vehicular frontal crashes. The human body model includes detailed anatomical features of the head, neck, chest, thoracic and lumbar spine, abdomen, and lower and upper extremities. The material properties used in the model for each anatomic part of the human body were obtained from test data reported in the literature. The total human body model used in the current study has been previously validated in frontal and side impacts. Several cadaver knee impact tests representing occupants in a frontal impact condition were simulated using the previously validated human body model. Model impact responses in terms of force-time and acceleration-time histories were compared with test results. In addition, stress distributions of the patella, femur, and pelvis were reported for the simulated test conditions.

Automotive manufacturing presents unique challenges for ergonomic analysis. The variety of tasks and frequencies are typically not seen in other industries. Moving these challenges into the realm of digital human modeling poses new challenges and offers the opportunity to create and enhance tools brought over from the traditional reactive approach. Chiang et al. (2006) documented an enhancement to the Siemen's Jack Static Strength Prediction tool. This paper will document further enhancements to the ErgoSolver (formerly known as the Ford Static Strength Prediction Solver).

The traditional moveable glass window seal development process has relied heavily on physical prototypes for design verification. Due to frequent styling changes and an overall reduction in design time, physical prototypes for the glass window seals have proven to be inadequate. Utilization of computer aided engineering (CAE) tools is necessary in order to shorten lead time. CAE tools will help to decrease expensive prototyping, free up valuable manufacturing line time, and improve overall quality. A cross functional approach has been applied to expand the scope beyond traditional methods of moveable glass window seal design, such as wedged boarding, into new computerized modeling methods. The CAE was used to address major requirements of the glass window seals including glass velocity, glass stall force, sealing-ability, seal durability, seal assembly, seal appearance, and regulator motor current.

Various frontal impact risk curves were assessed for the next-generation USA New Car Assessment Program (NCAP). Specifically, the “NCAP risk curves” — those chosen by the government for the 2011 model year NCAP — as well as other published risk curves were used to estimate theoretically the injury rates of belted drivers in real-world frontal crashes. Two perspectives were considered: (1) a “point” estimate of NCAP-type events from NCAP fleet tests, and (2) an “aggregate” estimate of 0 ≤ ΔV ≤ 56 km/h crashes from a modeled theoretical vehicle whose NCAP performance approximated the average of the studied fleet. Four body regions were considered: head, neck, chest, and knee-thigh-hip complex (KTH). The curve-based injury rates for each body region were compared with those of real-world frontal crashes involving properly-belted adult drivers in airbag-equipped light passenger vehicles. The assessment yielded mixed results.

As part of an ongoing technical collaboration between Ford and Rouge Steel Company, a comprehensive study of door slam event was undertaken. The experimental phase of the project involved measurements of accelerations at eight locations on the outer panel and strains on six locations of the inner panel. Although slam tests were conducted with window up and window down, results of only one test is presented in this paper. The CAE phase of the project involved the development of suitable “math” model of the door assembly and analysis methodology to capture the dynamics of the event. The predictability of the CAE method is examined through detailed comparison of accelerations and strains. While excellent agreement between CAE and test results of accelerations on the outer panel is obtained, the analysis predicts higher strains on the inner panel than the test. In addition, the tendency of outer panel to elastically buckle is examined.

Structure enhancement based on data monitored in a traditional side impact evaluation is primarily a trial and error exercise resulting in a large number of computer runs. This is because how the structure gets loaded and the degree of contribution of local structural components to resist the impact while absorbing energy during a side collision is not completely known. Developing real time complete load profiles on a body side during the time span of an impact is not an easy task and these loads cannot be calculated from that calculated at the barrier mounting plate. This paper highlights the load distribution, calculated by a procedure using computer aided engineering (CAE) tools, on a typical 2-door vehicle body side when struck by moving deformable barriers used in the insurance institute for highway safety (IIHS), EuroNCAP and LINCAP side impact evaluations.