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As per WHO 2018 report, pedestrian fatalities account for 23% of world road accident fatalities. Every day 850 pedestrians lose their lives in the world. As per MoRTH 2018 report, 16% of road accident fatalities are of pedestrians in India. Everyday 64 pedestrians lose their lives in India. Based on accident data, one of the most common reason for the pedestrian fatality is head injury due to primary contact from vehicle front-end structure. Pedestrian head injury performance highly depends on front-end styling, bonnet stiffness, clearance with aggregates underneath the bonnet and hard contact points. During concept stage of vehicle development, safety recommendation on front-end design is provided based on geometric assessment of the class A surface.

Aluminum alloy wheels are being widely used in the automotive industry since the last decade due to its superior styling and performance. Alloy wheel rim is one of the critical components and plays an important role in a frontal crash scenario. The wheel rim failure prediction in safety simulation is essential to ensure robust safety performance. Determining failure characteristics of an alloy wheel poses many difficulties considering its brittle nature, porosity and inhomogeneity in material properties across different regions of wheel rim due to mold design, cooling rate and other process parameters of the low-pressure die casting process. This paper describes the modelling and simulation methodology developed to predict accurate wheel behavior. The methodology addresses two distinct areas of challenges such as alloy wheel rim failure prediction and associated tire blow out.

The vehicle crash signature (here on referred as crash pulse) significantly affects occupant restraints system performance in frontal crash events. Restraints system optimization is usually undertaken in later phase of product development. This leads to sub-optimal configurations and performance, as no opportunity exists to tune vehicle structure and occupant package layouts. In concept phase of development, crash pulse characterization helps to map occupant package environment with available structure crush space and stiffness. The crash pulse slope, peaks, average values at discrete time intervals, can be tuned considering library of restraints parameters. This would help to derive an optimal occupant kinematics and occupant-restraints interaction in crash event. A case study has been explained in this paper to highlight the methodology.

Restraints systems (airbags and seat belts) have been proven to be very effective in occupant protection in crashes. Timely deployment of these devices is very essential for meeting performance requirements. Precision and reliability in restraints deployments demand selection of a robust sensing configuration that caters to the wide variations of real world. This paper highlights complexities involved in engineering of restraints sensing configurations through different case studies on vehicle programs. The paper explains the need for restraints sensing configuration optimization and well defined sensing strategies for a robust solution in real world. A methodology is discussed to achieve good discrimination between crashes of different types and severities. Virtual and physical test data collected at different stages of vehicle development is used. It is found that criteria for threshold levels in restraints sensing requires efforts to identify real world usage variations.

Integrating safety features may lead to changes in vehicle interior component designs. Considering this complexity, design guidelines have to take care of aspects which may help in package feasibility studies that consider systems performance requirements. Occupant restraints systems for protection in side crashes generally comprise of Side Airbag (SAB) and Curtain Airbag (IC). These components have to be integrated considering design and styling aspects of interior trims, seat contours and body structure for performance efficient package definition. In side crashes, occupant injury risk increases due to hard contact with intruding structure. This risk could be minimized by cushioning the occupant contact through provision of SAB and Inflatable IC. This paper explains the methodology for deciding the package definitions using Knowlwdge Based Engineering (KBE) tools.

Automobile safety is becoming one of the important criteria for customer vehicle selection. Vehicle manufacturers have a challenging task for introducing variety of products in market in short time domain. Engineering a product for safety parameters involves many critical attributes which could affect vehicle design and styling parameters. In this context, instrument panel (hereafter referred as IP) profile, design and package are one of the aspects which affect lower extremity injuries of an occupant in a frontal crash. The occupants due to inertial properties, and shock levels move inside the passenger compartment thereby resulting into knees and lower legs contacting the IP. It is found in many cases that knee-femur injuries are higher due to improper contact area and package of hard components behind IP. This paper explains a methodology of establishing the knee impact zone using a Knowledge Based Engineering (KBE) application.

Supplementary Restraints Systems (SRS) are provided in automobiles for occupant protection in severe accidents. Real world accidents are a varied mix of types and severities; thereby a need exists to engineer such systems for adequate performance robustness. Statistical data suggests high serious to fatal occupant injuries due to inadvertent SRS deployments, or sub-optimal Time-to-Fires (TTF) which lead to bag induced injuries. This paper explains the work done on a project to establish requirements of SRS deployments in different load cases of low, medium and high severity. LSDyna and MADYMO CAE applications have been used for this work and final validation through physical tests. The study considers different real world accident types and involves analysis of occupant-restraints system interactions. It includes variations in occupant types and seat belt configurations.

The heavy commercial vehicles are equipped with under-run protection devices (UPD) to enhance safety of occupants in small vehicles in the event of under-run. These UPD are popularly classified as RUPD (rear under-run protection devices), SUPD (side under-run protection devices), FUPD (front under-run protection devices). These devices primarily work to improve safety of smaller vehicles by changing its interaction with heavy vehicles thereby resulting in change in small vehicle structural engagement for energy absorption. Without UPD, smaller vehicle passenger compartment is likely to interact with stiff commercial vehicle chassis frame structures. However with UPD, the smaller vehicle front-end structure gets involved in the crash which helps in controlled energy absorption and safe-guards the passenger compartment.

There are many types of transducers mounted at different locations on-board the vehicle or test items being subjected to dynamic impact tests including full vehicle crash tests. The natural frequency of the sensors as mounted on vehicle structure is location dependant. This in turn can influence the data quality as the impact event is of very small duration with high shock levels and the sampling rates and frequency content of signals is generally high. Considering this, the mounting brackets and mounting location of all the transducers have to be stiff enough to avoid any influence on actual signals. Low natural frequency of sensors as mounted could result in poor quality of data thereby leading to wrong evaluation of the test. This paper explains the methodology for evaluation as per ISO 6487 [1]. These implantation tests have been conducted on a test vehicle at different intended mounting locations and with different types of mounting brackets.