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Enhanced protection against high speed crashes requires more aggressive passive safety countermeasures as compared to what are provided in vehicle structures today. Apart from such collision-related scenarios, high energy explosions, accidentally caused or otherwise, require superior energy-absorbing capability of vehicle body subsystems. A case in point is a passenger vehicle subjected to an underbody blast emanating shock wave energy of military standards. In the current study, assessment of the behavior of a “hollow” countermeasure in the form of a depressed steel false floor panel attached with spot-welds along flanges to a typical predominantly flat floor panel of a car is initially carried out with an explicit LS-DYNA solver. This is followed up with the evaluation of PU (polyurethane) foam-filled and liquid-filled false floor countermeasures. In all cases, a charge is detonated under the false floor subjecting it to a high-energy shock pressure loading.

Over the past decade there has been significant development in Automated Driving (AD) with continuous evolution towards higher levels of automation. Higher levels of autonomy increase the vehicle Dynamic Driving Task (DDT) responsibility under certain predefined Operational Design Domains (in SAE level 3, 4) to unlimited ODD (in SAE level 5). The AD system should not only be sophisticated enough to be operable at any given condition but also be reliable and safe. Hence, there is a need for Automated Vehicles (AV) to undergo extensive open road testing to traverse a wide variety of roadway features and challenging real-world scenarios. There is a serious need for accurate Ground Truth (GT) to locate the various roadway features which helps in evaluating the perception performance of the AV at any given condition. The results from open road testing provide a feedback loop to achieve a mature AD system.

Today’s advanced vehicles have high degree of interaction due to numerous sensors, actuators and also with complex communication within the control units. In order to hack a vehicle, it has to be within a certain range of communication. Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure. The results discussed here focus on the first detection method that is Cyber-Attack detection algorithm.

The Hotelling multivariate control chart and the sample generalized variance |S| are used to monitor the mean and dispersion of vehicle build vision data including the pallet information to identify the non-conforming pallets that are used in body shops of FCA US LLC assembly plants. An iterative procedure and the Gaussian mixture model (GMM) are used to rank the non-conforming or bad pallets in the order of severity. The Hotelling multivariate T2 test statistic along with Mason-Tracy-Young (MYT) signal decomposition method is used to identify the features that are affected by the bad pallets. These algorithms were implemented in the Advanced Pallet Analysis module of the FCA US software Body Shop Analysis Toolbox (BSAT). The identified bad pallets are visualized in a scatter plot with a different color for each of the top bad pallets. The run chart of an affected feature confirms the bad pallet by highlighting data points from the bad pallet.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

Due to the variation of compartment design and occupant’s posture in self-driving cars, there is a new and major challenge for occupant protection. In particular, the studies on occupant restraint systems used in the self-driving car have been significantly delayed compared to the development of the autonomous technologies. In this paper, a numerical study was conducted to investigate the effectiveness of three typical restraint systems on the driver protection in three different scenarios.

There has been recent progress over the past 10 years in research comparing 6-year-old thoracic and abdominal response of pediatric volunteers, pediatric post mortem human subjects (PMHS), animal surrogates, and 6-year-old ATDs. Although progress has been made to guide scaling laws of adult to pediatric thorax and abdomen data for use in ATD design and development of finite element models, further effort is needed, particularly with respect to lateral impacts. The objective of the current study was to use the impact response data of age equivalent swine from Yaek et al. (2018) to assess the validity of scaling laws used to develop lateral impact response corridors from adult porcine surrogate equivalents (PSE) to the 3-year-old, 6-year-old, and 10-year-old for the thorax and abdominal body regions.

Evaluations of the dynamic and acoustic responses of panels, partitions, and walls are of concern across many industries, from building home appliances, planning meeting rooms, to designing airplanes and passenger cars. Over the past few decades, search efforts for developing new methodologies and technologies to enable NVH engineers to acquire and correlate dynamically the relationship between input excitations and vibro-acoustic responses of arbitrary-shaped panels has grown exponentially. The application of a particular methodology or technology to the evaluation of a specific structure depends intimately on the goals and objectives of the NVH engineers and industries.

Previous study suggested that female, thin, obese, and older occupants had a higher risk of death and serious injury in motor vehicle crashes. Human body finite element models were a valuable tool in the study of injury biomechanics. The mesh deformation method based on radial basis function(RBF) was an attractive alternative for morphing baseline model to target models. Generally, when a complex model contained many elements and nodes, it was impossible to use all surface nodes as landmarks in RBF interpolation process, due to its prohibitive computational cost. To improve the efficiency, the current technique was to averagely select a set of nodes as landmarks from all surface nodes. In fact, the location and the number of selected landmarks had an important effect on the accuracy of mesh deformation. Hence, how to select important nodes as landmarks was a significant issue. In the paper, an efficient peak point-selection RBF mesh deformation method was used to select landmarks.

Fiber composite materials are widely used in many industrial applications - specially in automotive, aviation and consumer goods. Introducing light-weighting material solutions to reduce vehicle mass is driving innovative materials research activities as polymer composites offer high specific stiffness and strength compared to contemporary engineering materials. However, there are issues related to high production volume, automation strategies and handling methods. The state of the art for the production of these light-weight flexible textile or composite fiber products is setting up multi-stage manual operations for hand layups. Material handling of flexible textile/fiber components is a process bottleneck. Consequently, the long term research goal is to develop semi-automated pick and place processes for flexible materials utilizing collaborative robots within the process. Collaborative robots allow for interactive human-machine tasks to be conducted.

This paper details the vehicle testing activities performed during the Year 4 of the EcoCAR 3 competition by the Wayne State University team on a Pre-Transmission Parallel PHEV. The paper focuses on two main testing platforms: the chassis dynamometer and the closed-course track (on-road). The focus of the former is to evaluate the emissions and energy consumption associated with different driving scenarios, while the latter has been used to assess the vehicle performance and their impact on the consumer appeal. The paper presents the objectives of each test, the setup accomplished for the different vehicle testing platforms, the results obtained and the comparison with the values expected from simulations. In addition, the impact of the results on the refinement of the control strategies and on the validation of the simulation models are discussed.

Analysis and validation of current scaling relationships and existing response corridors using animal surrogate test data is valuable, and may lead to the development of new or improved scaling relationships. For this reason, lateral pendulum impact testing of appropriate size cadaveric porcine surrogates of human 3-year-old, 6-year-old, 10-year-old, and 50th percentile male age equivalence, were performed at the thorax and abdomen body regions to compare swine test data to already established human lateral impact response corridors scaled from the 50th percentile human adult male to the pediatric level to establish viability of current scaling laws. Appropriate Porcine Surrogate Equivalents PSE for the human 3-year-old, 6-year-old, 10-year-old, and 50th percentile male, based on whole body mass, were established. A series of lateral impact thorax and abdomen pendulum testing was performed based on previously established scaled lateral impact assessment test protocols.

In order to improve the comprehensive protection for children with variable shapes and sizes, this paper conducted studies on the impact injury for obese children based on a 10-YO finite element model. Some specific geometrics on the body surface were firstly acquired by the combination of pediatric anthropometric database and generator of body (GEBOD). A Radial Basis Function (RBF) based mesh morphing technique was then used to modify the original standard size FE model using the obtained geometrics. The morphed FE model was validated based on the experimental data of frontal sled test and chest-abdomen impact test. The effects of obesity on injury performances were analyzed through simplified high-speed and low-speed crash simulations.

In order to provide an improved countermeasure for occupant protection, a new type of active reversible preload seatbelt (ARPS) is presented in this paper. The ARPS is capable of protecting occupants by reducing injuries during frontal collisions. ARPS retracts seatbelt webbing by activating an electric motor attached to the seatbelt retractor. FCW (Forward Collision Warning) and LDW (Lane Departure Warning) provide signals as a trigger to activate the electric motor to retract the seatbelt webbing, thus making the occupant restraint system work more effectively in a crash. It also helps reduce occupant’s forward movement during impact process via braking. Four important factors such as preload force, preload velocity and the length and timing of webbing retraction play influential roles in performance of the ARPS. This paper focuses on studying preload performance of ARPS under various test conditions to investigate effects of the aforementioned factors.

An understanding of stiffness characteristics of different body regions, such as thorax, abdomen and pelvis of ES-2re and SID-IIs dummies under controlled laboratory test conditions is essential for development of both compatible performance targets for countermeasures and occupant protection strategies to meet the recently updated FMVSS214, LINCAP and IIHS Dynamic Side Impact Test requirements. The primary purpose of this study is to determine the transfer functions between the ES-2re and SID-IIs dummies for different body regions under identical test conditions using flat rigid wall sled tests. The experimental set-up consists of a flat rigid wall with five instrumented load-wall plates aligned with dummy’s shoulder, thorax, abdomen, pelvis and femur/knee impacting a stationary dummy seated on a rigid low friction seat at a pre-determined velocity.

The main purpose of this study was to determine the impact responses of the different body regions (shoulder, thorax, abdomen and pelvis/leg) of the ES-2re and SID-IIs dummies using rigid wall impacts under different initial test conditions. The experimental set-up consisted of a flat rigid wall with five instrumented load-wall plates aligned with dummy’s shoulder, thorax, abdomen, pelvis and knee impacting a stationary dummy seated on a rigid seat at a pre-determined velocity. The relative location and orientation of the load-wall plates was adjusted relative to the body regions of the ES-2re and SID-IIs dummies respectively.

The main purpose of this study was to determine the impact responses of the different body regions (shoulder, thorax, abdomen and pelvis/leg) of the ES-2re and SID-IIs dummies using rigid wall impacts under different initial test conditions. The experimental set-up consisted of a flat rigid wall with five instrumented load-wall plates aligned with dummy’s shoulder, thorax, abdomen, pelvis and knee impacting a stationary dummy seated on a rigid seat at a pre-determined velocity. The relative location and orientation of the load-wall plates was adjusted relative to the body regions of the ES-2re and SID-IIs dummies respectively.

This paper details the Wayne State University development of the Hybrid Supervisory Controller strategies for the Year 3 of the EcoCAR 3 competition. Included in this paper are the processes for developing the strategies for the supervisory control system, which includes the torque distribution among the powertrain components, and the diagnostic strategies adopted to guarantee the safety critical functionalities of the vehicle. The EcoCAR 3 competition challenges sixteen North American universities to re-engineer the 2016 Chevrolet Camaro to reduce its environmental impact without compromising its performance and consumer acceptability. During the Year 3 of the competition the team has refined the control strategies designed in the previous years, to enable the powertrain full functionalities and achieve better energy consumption over pre-determined drive cycles.

It is recognized that there is a dearth of studies that provide a comprehensive understanding of vehicle-occupant system dynamics for various road conditions, sitting occupancies and vehicle velocities. In the current work, an in-house-developed 50 degree-of-freedom (DOF) multi-occupant vehicle model is employed to obtain the vehicle and occupant biodynamic responses for various cases of vehicle velocities and road roughness. The model is solved using MATLAB scripts and library functions. Random road profiles of Classes A, B, C and D are generated based on PSDs (Power Spectral Densities) of spatial and angular frequencies given in the manual ISO 8608. A study is then performed on vehicle and occupant dynamic responses for various combinations of sitting occupancies, velocities and road profiles. The results obtained underscore the need for considering sitting occupancies in addition to velocity and road profile for assessment of ride comfort for a vehicle.

Vehicle safety systems may use occupant physiological information, e.g., occupant heights and weights to further enhance occupant safety. Determining occupant physiological information in a vehicle, however, is a challenging problem due to variations in pose, lighting conditions and background complexity. In this paper, a novel occupant height estimation approach is presented. Depth information from a depth camera, e.g., Microsoft Kinect is used. In this 3D approach, first, human body and frontal face views (restricted by the Pitch and Roll values in the pose estimation) based on RGB and depth information are detected. Next, the eye location (2D coordinates) is detected from frontal facial views by Haar-cascade detectors. The eye-location co-ordinates are then transferred into vehicle co-ordinates, and seated occupant eye height is estimated according to similar triangles and fields of view of Kinect.