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In the automobile industry, the reliability and predictive capabilities of computer models for a dynamic system need to be assessed quantitatively. Quantitative validation allows engineers to assess and improve model reliability and quality objectively and ultimately lead to potential reduction in the number of prototypes built and tests. A good metric, which is essential in model validation, requires considering uncertainties in both testing and computer modeling. In addition, it needs to be able to compare multiple responses simultaneously, as multiple quantities are often encountered at different spatial and temporal points of a dynamic system. In this paper, a state-of-the-art validation technology is developed for multivariate complex dynamic systems by exploiting a probabilistic principal component analysis method and Bayesian statistics approach.

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.

This paper starts describing the in-mold grain lamination and bilaminated film cover when applied to instrument panels with seamless passenger air bag doors. It then offers a comparison between two different PAB door weakening processes, the laser scoring and the scoring by milling. It further discuss the scoring by milling process and analyses its implementation on a real case instrument panel. In the implementation case, the scoring pattern is checked against a pre-defined engineering specification and correlated to the results of a drop tower test, which shows the force necessary to break the PAB door. Three iterations are performed until the results for scoring pattern and breaking force are achieved. The breaking force results are then statistically validated against the specification and capability analysis.

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 order to quantify the dynamic restraint capability of a passenger airbag, a sub-system test method has been developed. The sub-system included a passenger airbag, an adjustable generic instrument panel (IP) and an adjustable windshield. The test was called the Passenger Air Bag Linear Impactor Test (PABLIT). This test method could be used for not only A to B comparisons, but also to evaluate the performance of any PAB module design in general, including performance variability of airbag systems. A variety of impactor, pendulum and drop tower test methods are currently used by inflatable restraint suppliers. PABLIT was aimed to standardize airbag testing and data analysis. Various production hardware designs were tested to investigate the characteristics of the sub-assemblies that provide restraint capability.

Head restraint has become an important element in seat design due to the severity of neck injuries in rear-end collisions. The objective of this paper is to present an analytical and efficient approach to assist engineers in analyzing the design parameters of the seat and head restraint system. The CAE simulation models with Bio-RID dummy were assembled to correlate to 10 mph rear impact sled tests. The correlated models were then adopted in Design of Experiment (DOE) studies to explore all the significant design parameters influencing occupant neck injuries. Based on the results from the DOE studies, we are able to improve the seat and head restraint designs for reducing the risk of neck injuries in rear-end impacts.

There are a wide variety of approaches to model the automotive seat and occupant interaction. This paper traces the studies conducted for simulating the occupant to seat interaction in frontal and/or rear crash events. Starting with an initial MADYMO model, a MADYMO-LS/DYNA coupled model was developed. Subsequently, a full Finite Element Analysis model using LS/DYNA was studied. The main objective of the studies was to improve the accuracy and efficiency of CAE models for predicting the dummy kinematics and structural deformations at the restraint attachment locations in laboratory tests. The occupant and seat interaction was identified as one of the important factors that needed to be accurately simulated. Quasi-static and dynamic component tests were conducted to obtain the foam properties that were input into the model. Foam specimens and the test setup are discussed. Different material models in LS/DYNA were evaluated for simulating automotive seat foam.

A passenger airbag is an important part of a vehicle restraint system which provides supplemental protection to an occupant in a crash event. New Federal Motor Vehicle Safety Standards No. 208 requires considering multiple crash scenarios at different speeds with various sizes of occupants both belted and unbelted. The increased complexity of the new requirements makes the selection of an optimal airbag shape a new challenge. The aim of this research is to present an automated optimization framework to facilitate the airbag shape design process by integrating advanced tools and technologies, including system integration, numerical optimization, robust assessment, and occupant simulation. A real-world frontal impact application is used to demonstrate the methodology.

The Federal Motor Vehicle Safety Standard or FMVSS 208 requires passenger cars, multi-purpose vehicles, trucks with less than unloaded vehicle weight of 2,495 kg either to have an automatic suppression feature or to pass the injury criteria specified under low risk deployment test requirement for a 1 year old dummy in rearward and forward facing restraints as well as a forward facing 3 and 6 year old dummy. A convertible child seat was installed in a sub-system test buck representing a passenger car environment with a one-year- old dummy in it at the passenger side seat and a passenger side airbag was deployed toward the convertible child seat. A MADYMO model was built to represent the test scenario and the model was correlated and validated to the results from the experiment.

The relation cost versus performance in the design of an automobile is crucial for its success. These two characteristics, much like the project development timing, are closely related to the attributes that the new design must achieve (e.g. weight, fuel economy, torsional stiffness, NVH, safety, etc.). In this respect, the design optimization of body reinforcements (i.e. part thickness, quantity of reinforcements, and number of spot welds) contributes greatly to a sound and robust project concept. This paper describes one application of 6-Sigma methodology to evaluate the performance of different configurations of seat belt reinforcements resulting in an optimized concept that achieved the proposed performance targets with weight and sub-assembly complexity reduction. Using a Design of Experiments (DOE) and Finite Element Analysis (FEA), each proposal was evaluated for its resistance to plastic deformation.

Computer Aided Engineering (CAE) has become a vital tool for product development in automotive industry. Various computer models for occupant restraint systems are developed. The models simulate the vehicle interior, restraint system, and occupants in different crash scenarios. In order to improve the efficiency during the product development process, the model quality and its predictive capabilities must be ensured. In this research, an objective model validation metric is developed to evaluate the model validity and its predictive capabilities when multiple occupant injury responses are simultaneously compared with test curves. This validation metric is based on the probabilistic principal component analysis method and Bayesian statistics approach for multivariate model assessment. It first quantifies the uncertainties in both test and simulation results, extracts key features, and then evaluates the model quality.

Objective: This study analyzes rear sled tests with a 95th% male and 5th% female Hybrid III dummy in various seating positions on ABTS (All Belt to Seat) seats in severe rear impact tests. Dummy interactions with the deforming seatback and upper body extension around the seat frame are considered. Methods: The 1st series involved an open sled fixture with a Sebring ABTS seat at 30 mph rear delta V. A 95th% Hybrid III dummy was placed in four different seating positions: 1) normal, 2) leaning inboard, 3) leaning forward and inboard, and 4) leaning forward and outboard. The 2nd series used a 5th% female Hybrid III dummy in a Grand Voyager body buck at 25 mph rear delta V. The dummy was leaned forward and inboard on a LeSabre ABTS or Voyager seat. The 3rd series used a 5th% female Hybrid III dummy in an Explorer body buck at 26 mph rear delta V. The dummy was leaned forward and inboard on a Sebring ABTS or Explorer seat.

The Restraint System and interior design (seats, steering wheel, etc) are critical for Vehicle Occupant Injury performance. Assuming a given Vehicle pulse the restraints and interior design determine the dummy kinematics. Furthermore, some interior characteristics (shape, material, thickness, etc) have direct influence on Occupant's Body Energy Absorption. The paper describes a Non-airbag interior development to meet Head Impact Criteria (HIC) as per FMVSS208 Frontal Impact requirements. Several proposals were assessed by CAE and component and vehicle level testing on their influence on Occupant Kinematics and Dynamics. After a few design iterations, a significant reduction in HIC value was achieved.

Unlike the conventional seat belt system wherein the shoulder belt upper anchor is mounted on the vehicle body, Seat Integrated Restraint (SIR) system has the shoulder belt upper anchor mounted on the top of seat back frame. During a vehicle frontal impact, the stiffness of seat and that of the floor underneath the seat play a significant role in the performance of the restraint system in providing protection to the occupants. In this study the effect of the stiffness of seat and floor on the restraint system is investigated with other restraint parameters such as retractor load limit, fire time lag of dual stage inflator and air bag vent size. The stiffness of seat and floor is varied to determine the range of best occupant protection. This study attempts to establish feasible design targets of seat and floor stiffness for optimal restraint performance.

Computer modeling has played important roles and gained great momentum in product development as numerical methods, computer software and hardware technologies advance rapidly. Computer models (e.g. MADYMO) that simulate vehicle interior, restraint system and occupants in various crash modes have been widely used to improve occupant safety. However, to build good occupant models, engineers often have to spend tremendous time on model correlation. The challenge of model correlation for occupant safety is that it requires matching numerous injury curves with tests, for examples: head G, chest G, chest deflection, shoulder belt load, femur loads, neck load and moment. Traditionally, this model correlation task is done by a trial and error method. This paper attempts to solve the problem systematically by using a genetic algorithm. It demonstrates that the genetic algorithm is a valuable optimization tool to obtain a high quality MADYMO model.

Federal Motor Safety Standard (FMVSS) 225 establishes requirements for child restraint anchorage systems to ensure their proper location and strength for the effective securing of child restraints, to reduce the likelihood of the anchorage systems failure and to increase the likelihood that child restraints are properly secured and thus more fully achieve their potential effectiveness in motor vehicles. Current CAE simulations are focused on evaluating localized structural strength by applying the loads as vectors to the child tether anchorages to approximate the loading. This method cannot be used to determine the displacement requirements of child tether that was added recently to FMVSS 225 specifications. A new CAE procedure that takes into account the effect of seat structure and belt system has been developed and successfully applied to truck programs.

A theoretical, mathematical, risk assessment procedure was developed to estimate the fraction of drivers that incurred head and thoracic AIS3+ injuries in full-engagement frontal crashes. The estimates were based on numerical simulations of various real-world events, including variations of crash severity, crash speed, level of restraint, and occupant size. The procedure consisted of four steps: (1) conduct the simulations of the numerous events, (2) use biomechanical equations to transform the occupant responses into AIS3+ risks for each event, (3) weight the maximum risk for each event by its real-world event frequency, and (4) sum the weighted risks. To validate the risk assessment procedure, numerous steps were taken. First, a passenger car was identified to represent average field performance.

State of the art electronic restraint systems rely on the acceleration measured during a vehicle crash for deployment decisions. The acceleration signal is analyzed with different criteria, among which the velocity change is a dominant criterion in almost any existing crash detection algorithm. Sensors in the front crush zone have recently been added to help develop restraint systems that comply with the new FMVSS208 and EuroNCAP regulations. Front crash sensors are usually evaluated for their velocity change during a crash and typically play a key role in the deployment decision. CAE based FEA analysis has recently been used to generate signals at the sensor module locations in crash simulations to provide supplemental information for crash sensing algorithm development and calibration. This paper presents an initial effort in developing a velocity-based crash detection algorithm, that allows broad use of CAE generated velocity time histories for system calibration.

With the increasing demands of developing vehicles for global markets, different regulations and public domain tests need to be considered simultaneously for side impact. Various side impact countermeasures, such as side airbags, door trim, energy absorbing foams etc., are employed to meet multiple side impact performance requirements. However, it is quite a challenging task to design a balanced side impact restraint system that can meet all side impact requirements for multiple crash modes. This paper presents an integrated multi-objective optimal design and robustness assessment framework for vehicle side impact restraint system design.

Traditionally, Knee Air Bag (KAB) is constructed of a woven nylon or polyester fabric. Recently, Ford developed an injection molded air bag system for the passenger side called Active Glove Box (AGB). This system integrates a plastic bladder welded between the glove box outer and inner doors. This new system is smaller and lighter, thus improving the roominess and other creature comforts inside the passenger cabin while providing equivalent restraint performance as traditional knee airbag system. This patented technology allows positioning of airbags in new locations within the vehicle, thus giving more freedom to designers. The first application of this technology was standard equipment on the 2015 Ford Mustang. Given that this technology is first in the industry, it was a challenge to design, test and evaluate the performance of the system as there is no benchmark to compare this technology. A CAE driven design methodology was chosen to overcome this challenge.