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Determining occupant kinematics in a vehicle crash is essential when understanding injury mechanisms and assessing restraint performance. Identifying contact marks is key to the process. This study was conducted to assess the ability to photodocument the various fluids on different vehicle interior component types and colors with and without the use of ultraviolet (UV) lights. Biological (blood, saliva, sweat and skin), consumable and chemical fluids were applied to vehicle interior components, such as seatbelt webbing, seat and airbag fabrics, roof liner and leather steering wheel. The samples were photodocumented with natural light and UV light (365 nm) exposure immediately after surface application and again 14 days later. The review of the photos indicated that fabric type and color were important factors. The fluids deposits were better visualized on non-porous than porous materials. For example, blood was better documented on curtain airbags than side or driver airbags.

Occupant protection in side impacts, in particular for near-side occupants, is a challenge due to the occupant’s close proximity to the impact. Near-side occupants have limited space to ride down the impact. Curtain and side airbags fill the gap between occupant and the side interior. This analysis was conducted to provide insight on the characteristics of side impacts and the relevancy of currently regulated test configurations. For this purpose, 2007-2015 NASS-CDS and 2017-2021 CISS side crash data were analyzed for towed light vehicles. 2008 and newer model year vehicle data was selected to ensure that most vehicles were equipped with side/curtain airbags. The results showed that side impacts accounted for approximately 26.7% of the vehicles involved and 18.9% of the vehicles with at least one seriously injured occupant. Most side impacts involved damage to the front and front-to-center of the vehicle.

This study was conducted to assess the occupant restraint use and injury risks by seating position. The results were used to discuss the merit of selected warning systems. The 1989-2015 NASS-CDS and 2017-2021 CISS data were analyzed for light vehicles in all, frontal and rear tow-away crashes. The differences in serious injury risk (MAIS 3+F) were determined for front and rear seating positions, including the right, middle and left second-row seats. Occupancy and restraint use were determined by model year groups. Occupancy relative to the driver was 27% in the right-front (RF) and 17% in the second row in all crashes. About 39% of second-row passengers were in the left seat, 15% in the center seat and 47% in the right seat. Restraint use was lower in the second row compared to front seats. It was 43% in the right-front and 32% in the second-row seats in all crashes involving serious injury. Restraint use increased with model year groups.

In 1983, a seat belt use rate survey was published in which 9% shoulder belt use was observed for front-outboard passengers. Nearly forty years later the national estimate of seat belt use has achieved a record high of 91.6% belt use by adult front-seat passengers in 2022. In contrast, there have been very few studies conducted in order to determine seat belt use within large buses and motorcoaches. In 2013, the NHTSA published a final rule amending FMVSS 208 to require seat belts for each seating position in all new over-the-road buses. Beginning in 2016, newly manufactured buses were required to be equipped with lap and shoulder belts for each driver and passenger seat. Recent studies have reported that seat belt use on motorcoaches with relatively long routes was only 2.6%. Similarly, seat belt use in airport shuttle buses was reported to be only 1%. The present observational study was conducted to determine an updated seat belt usage rate of passengers on airport shuttle buses.

This study focused on occupant responses in very large pickup trucks in rollovers and was conducted in three phases. Phase 1 - Field data analysis: In a prior study [9], 1998 to 2020 FARS data were analyzed; Pickup truck drivers with fatality were 7.4 kg heavier and 4.6 cm taller than passenger car drivers. Most pickup truck drivers were males. Phase 1 extended the study by focusing on the drivers of very large pickup trucks. The size of 1999-2016 Ford F-250 and F-350 drivers involved in fatal crashes was analyzed by age and sex. More than 90% of drivers were males. The average male driver was 179.5 ± 7.5 cm tall and weighed 89.6 ± 18.4 kg. Phase 2 – Surrogate study: Twenty-nine male surrogates were selected to represent the average size of male drivers of F-250 and F-350s involved in fatal crashes. On average, the volunteers weighed 88.6 ± 5.2 kg and were 180.0 ± 3.2 cm tall with a 95.2 ± 2.2 cm seated height.

The computer-aided engineering (CAE) automation study requires a large disk space and a premium processor. If all finite element (FE) models run locally, it may crash the local machine, and if the FE model runs on high-performance computing (HPC), transferring data from the server to the local machine to do the optimization may cause latency issues. This automation study provides a unique road map to optimize the design by working efficiently using the initial setup on the local machine, running an analysis of a large number of FE models on HPC, and performing optimization on the server. CAE Automation process has been demonstrated using a case study on a driveline component, crush spacer. Crush spacer is a very critical engineering design because, first, it provides the minimum required preload to the bearing inner races to keep them in position and, second, it endures a number of duty cycles.

Electrification is the well-accepted solution to address carbon emissions and modernize vehicle controls. Batteries play a critical in the journey of electrification and modernization with battery voltage prediction as the foundation for safe and efficient operation. Due to its strong dependency on prior information, battery voltage was estimated with recurrent neural network methods in the recent literatures exploring a variety of deep learning techniques to estimate battery behaviors. In these studies, standard recurrent neural networks, gated recurrent units, and long-short term memory are popular neural network architectures under review. However, in most cases, each neural network architecture is individually assessed and therefore the knowledge about comparative study among three neural network architecture is limited. In addition, many literatures only studied either the dynamic voltage response or the voltage relaxation.

Forensic investigators of automobile collisions are commonly tasked with determining whether physical evidence observed on restraint systems is consistent with the occupant’s use or non-use of the seat belt restraint. The characteristics of collision-induced markings generated on seat belt systems are not solely dependent on the belted status of the occupant, but also the technological features incorporated in the seat belt assembly. As the state-of-the-art for seat belt assemblies has changed over time, so has the constellation of physical evidence typically created on seat belt restraint systems. Pretensioner deployment can leave physical evidence on restraint system hardware in the absence of occupant loading. This study presents examples of physical evidence collected from seat belt systems involved in real-world collisions, which were initially alleged to affirm proper belt use, but were ultimately proven to be evidence of non-use.

This paper analyzes motorcycle braking characteristics during stops at various speeds on a dry, asphalt surface with and without the use of the anti-lock brake system (ABS). To characterize the braking performance of the motorcycle, threshold brake stops were performed on a motorcycle of the superbike category at various speed increments. Motorcycle and brake system outputs consisting of brake pressures, wheel speeds, accelerations and yaw rates were measured and analyzed to highlight the different characteristics between a motorcycle with an integrated anti-lock brake system and multiple anti-lock brake system rider modes. Three different brake input strategies were used to brake the motorcycle; a front only brake application, a front and rear brake application, and a rear only brake application. The anti-lock brake system rider modes consist of a sport setting, a race setting and a setting that deactivates the anti-lock brake system.

Reconstruction of passenger vehicle accidents involving side impacts with narrow objects has traditionally been approached using side stiffness coefficients derived from moveable deformable barrier tests or regression analysis using the maximum crush in available lateral pole impact testing while accounting for vehicle test weight. Current Lateral Impact New Car Assessment Program (LINCAP) testing includes 20 mph oblique lateral pole impacts. This test program often incorporates an instrumented pole so the force between the vehicle and pole at several elevations along the vehicle - pole interface is measured. Force-Displacement (F-D) characteristics of vehicle structures were determined using the measured impact force and calculated vehicle displacement from on-board vehicle instrumentation. The absorbed vehicle energy was calculated from the F-D curves and related to the closing speed between the vehicle and the pole by the vehicle weight.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

A copula-based approach for model bias characterization was previously proposed [18] aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to preprocess data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

Ultrasonic fatigue tests (testing frequency around 20 kHz) have been conducted on four different cast aluminum alloys each with a distinct composition, heat treatment, and microstructure. Tests were performed in dry air, laboratory air and submerged in water. For some alloys, the ultrasonic fatigue lives were dramatically affected by the environment humidity. The effects of different factors like material composition, yield strength, secondary dendrite arm spacing and porosity were investigated; it was concluded that the material strength may be the key factor influencing the environmental humidity effect in ultrasonic fatigue testing. Further investigation on the effect of chemical composition, especially copper content, is needed.

Since their inception, the design of airbag sensing systems has continued to evolve. The evolution of air bag sensing system design has been rapid. Electromechanical sensors used in earlier front air bag applications have been replaced by multi-point electronic sensors used to discriminate collision mechanics for potential air bag deployment in front, side and rollover accidents. In addition to multipoint electronic sensors, advanced air bag systems incorporate a variety of state sensors such as seat belt use status, seat track location, and occupant size classification that are taken into consideration by air bag system algorithms and occupant protection deployment strategies. Electronic sensing systems have allowed for the advent of event data recorders (EDRs), which over the past decade, have provided increasingly more information related to air bag deployment events in the field.

For more than 30 years, field research and laboratory testing have consistently demonstrated that properly wearing a seat belt dramatically reduces the risk of occupant death or serious injury in motor vehicle crashes. In severe rollover crashes, deformation to vehicle body structures can relocate body-mounted seat belt anchors altering seat belt geometry. In particular, roof pillar mounted shoulder belt anchors (“D-rings”) are subject to vertical and lateral deformation in the vehicle coordinate system. The ROllover Component test System (ROCS) test device was utilized to evaluate seat belt system performance in simulated severe rollover roof-to-ground impacts. A mechanical actuator was designed to dynamically relocate the D-ring assembly during a roof-to-ground impact event in an otherwise rigid test vehicle fixture. Anthropomorphic test device (ATD) kinematics and kinetics and seat belt tensions were compared between tests with and without D-ring relocation.

Numerous studies describe the fuel consumption benefits of changing the powertrain temperature based on vehicle operating conditions. Actuators such as electric water pumps and active thermostats now provide more flexibility to change powertrain operating temperature than traditional mechanical-only systems did. Various control strategies have been proposed for powertrain temperature set-point regulation. A characteristic of powertrain thermal management systems is that the operating conditions (speed, load etc) change continuously to meet the driver demand and in most cases, the optimal conditions lie on the edge of the constraint envelope. Control strategies for set-point regulation which rely purely on feedback for disturbance rejection, without knowledge of future disturbances, might not provide the full fuel consumption benefits due to the slow thermal inertia of the system.