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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.

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.

This study focused on European NCAP activities of introducing a new head protection evaluation procedure, as proposed by BASt (Federal Highway Research Institute - GERMANY). Various kinds of E-bikes are available in the market, ranging from E-bikes that have a small motor to assist the rider’s pedal-power i.e., pedelecs to somewhat more powerful E-bikes which is similar to a moped-style scooter. This paper focused on identifying the factors influencing bicyclist head kinematics during bicycle vs. passenger vehicle (PV) collisions at the intersection. Two AM50 bicyclist FE models are developed using i) GHBMC Human Body Model (HBM) and ii) WorldSID (WS) side impact dummy. Head kinematics of bicyclists of pedal-assist E-bike and normal bike were compared using CAE simulation. It is found that the vehicle’s impact velocity, type of bicycle, the mass of E-bike and bicycle traveling speed will influence the head kinematics.

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.

The authors have proposed a new method to identify the important information which links to the basic principle of the design's physical behavior by using CAE technology, and this method was named as CAP (Computer-Aided Principle).This method can help the engineers to grasp the basic physical characteristic that governs the first-order behavior. In this study, the authors applied CAP to the simulations of the design of frontal crash phenomena, which are difficult to understand because of the problem of strong nonlinearity, and explored the possibilities for using CAP. The correlative physical parameters thus obtained can help designers to understand the essence of the phenomena involved.

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.

The Computer-Aided Principle (CAP) is applied in this study as an effective approach to the crashworthiness design of the vehicle front-end structure. With this method, correlative parameters are extracted in a parametric study by using a cluster analysis. The results can help engineers to understand the fundamental mechanisms of structural phenomena. A simulation example of an offset frontal crash against a deformable barrier (ODB) is presented to show the effectiveness of the proposed method.

With SUVs and minivans accounting for a larger share of the US market in the past decade, rollover accidents have drawn greater attention, leading to more active research from different perspectives. This ranges from investigations for elucidating the basic causes and mechanisms of rollover accidents to studies of more advanced occupant protection measures. As the phenomenon of a rollover accident is longer in duration than frontal, side or rear impacts, it is relatively difficult [1] to simulate such accidents for experimental verification and also for proper evaluation of occupant restraint system performance. In this work, we focused on the trip-over type, which occurs most frequently, and performed simulations to reproduce real-world rollover accidents by combining PC-Crash and FEA.

Most of the side impact air bag systems in the current market are designed to protect the thorax area only. The new Head and Thorax SRS Side Impact Air Bag system, which Nissan recently introduced into the market, was designed to help provide additional protection for the head in certain side impacts. The system may help protect occupant head contacts when the vehicle collides into a tree, or the high hood of a large striking vehicle. This paper introduces the additional features and function of the new Head and Thorax SRS Side Impact Air Bag system, and some evaluation results in laboratory testing.

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.

The probability or risk of traffic accidents must be estimated quantitatively in order to implement effective traffic safety measures. In this study, various statistical data and probability theory were used to examine a method for predicting the risk of crossing-collisions, representing a typical type of accident at intersections in Japan. Crossing-collisions are caused by a variety of factors, including the road geometry and traffic environment at intersections and the awareness and intentions of the drivers of the striking and struck vehicles. Bayes' theorem was applied to find the accident probability of each factor separately. Specifically, the probability of various factors being present at the time of a crossing-collision was estimated on the basis of traffic accident data and observation survey data.

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.

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.

The front end module technology is a system developed to make the interface with vehicle body in accordance with costumer requirements. This modular system also has characteristics to reinforce the structure (chassis, main rails, shotguns), respecting its robustness (tolerances of the body) in accordance with NVH performance. The decision of having a FEM design made by steel and plastic was taken due to NVH specification, impact and safety requirements. Other items were either considered such as: fixation on the body of the vehicle, constraints between bumper beam and engine cooling module. Simulation tools including: durability test (static and dynamic) and modal F.E.A analysis, CAE system, crash test performance, aerodynamics required to insure results desired results.