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The study of aerodynamic forces in hypersonic environments is important to ensure the safety and proper functioning of aerospace vehicles. These forces vary with the angle of attack (AOA) and there exists an optimum angle of attack where the ratio of the lift to drag force is maximum. In this paper, computational analysis has been performed on a blunt cone model to study the aerodynamic characteristics when hypersonic flow is allowed to pass through the model. The flow has a Mach number of 8.44 and the angle of attack is varied from 0º to 20º. The commercial CFD solver ANSYS FLUENT is used for the computational analysis and the mesh is generated using the ICEM CFD module of ANSYS. Air is selected as the working fluid. The simulation is carried out for a time duration of 1.2 ms where it reaches a steady state and the lift and drag forces and coefficients are estimated. The pressure, temperature, and velocity contours at different angles of attack are also observed.

Modern combat aircraft demands efficient maintenance strategies to ensure operational readiness while minimizing downtime and costs. Innovative approaches using Digital Twining models are being explored to capture inter system behaviours and assessing health of systems which will help maintenance aspects. This approach employs advanced deep learning protocols to analyze the intricate interactions among various systems using the data collected from various systems. The research involves extensive data collection from sensors within combat aircraft, followed by data preprocessing and feature selection, using domain knowledge and correlation analysis. Neural networks are designed for individual systems, and hyper parameter tuning is performed to optimize their performance. By combining the outputs of these during the model integration phase, an overall health assessment of the aircraft will be generated.

In recent years, the push for reduced product development timelines has been more than ever with significant changes in the automotive market. High electrification, intelligent vehicle systems and increased number for car manufacturers are a few key drivers to the same. The front loading of development activities is now a key focus area for achieving faster product development. From vehicle dynamics point of view availability of subjective evaluation feedback plays a key role in optimization various system specifications. This paper discusses an approach for front loading through parallel development of the tire and vehicle chassis system, using advanced simulation and driving simulator technology. The proposed methodology uses virtual tire models which in combination with real-time vehicle model enables subjective evaluation of vehicle performance in driver-in-loop simulators.

The current research focuses on enhancing the performance of Si solar cells by using Er2O3 (Erbium Oxide) in cubic crystalline nature serves as an anti-reflection coating material. An anti-reflective coating aims to improve the Efficient Power Conversion (EPC) of polycrystalline silicon wafers solar cells (PSSC) utilised in solar roof panels of the automotive sector. It also exhibits superior light transmittance and least light reflectance, which eventually leads to the increase EPC. Erbium oxide helps to convert low energy photons into high energy photons. The incident photons, which lies on the solar cell, gradually losses its energy to travel in a denser medium and dissipate in the form of heat energy. In order to overcome the rate of reflection, current research aims in synthesis of erbium oxide nanosheets using electrospinning deposition technique for varying deposition timings such as 1, 1.5 and 2 hours.

Range anxiety is one of the major factors to be dealt with for increasing penetration of EVs in current Automotive market. The major reasons for range anxiety for customers are sparse charging infrastructure availability, limited range of Electric vehicles and range uncertainty due to diverse real-world usage conditions. The uncertainty in real world range can be reduced by increasing the correlation between the testing condition during vehicle development and real-world customer usage condition. This paper illustrates a more accurate test methodology development to derive the real-world range in electric vehicles with experimental validation and system level analysis. A test matrix is developed considering several variables influencing vehicle range like different routes, drive modes, Regeneration levels, customer drive behavior, time of drive, locations, ambient conditions etc.

As a car OEM, we continuously strive to set the bar for competitors with every product. Consumer travel experiences are enhanced by increasing passenger cabin silence. There is only one steering system opening in the firewall panel, which is used for allowing intermediate shaft's fitment on the pinion shaft of the steering gear. The steering grommet is the sole component that covers the firewall cut-out without disrupting steering operations, which has a substantial impact on the NVH performance of the vehicle. It is typically used in cars to eliminate engine noise and dust entering to passenger compartment. The part is assembled inside the vehicle where the steering intermediate shaft passing through BIW firewall panel. We use a bearing, plastic bush, or direct rubber interference design in the steering grommet to accommodate the rotational input the driver provides to turn the automobile.

As we all know, automotive headliners are an essential component of any car’s interior as they cover all the internal components and provide a clean and finished look. Headliners not only increase the aesthetic appeal of a car’s interior, but also acts as an insulation and sound absorption source. As per the latest Government norms, Curtain Airbag (henceforth called as CAB) has been made mandatory and this change calls for the corresponding changes in the Headliner packaging of all passenger vehicles. In general, curtain air-bag deployment calls for a twist open of Headliner at lateral sides (a portion below Hinge-line) during the deployment. This enables the inflated airbag to flow inside the passenger cabin to protect the passenger from any injury. Conventionally no components are packaged below the hinge-line area of headliner to avoid obstruction for CAB deployment and any part fly-off concerns.

Restraint systems in automotives are inevitable for the safety of passengers. Seat belts are one such restraint system in automotives that prevent drivers and passengers from being injured during a crash by restraining them back. Seatbelt on automotives has interface with Body-in-white (henceforth called as BIW) and Trim parts in-order to serve its purpose at vehicle level. One such interface part of seat belt is the web guide, which assists and ensures the nylon web’s smooth motion at different seat track positions. Web-guides on automotives ensure the flawless motion of seat belt web at pillar trim areas. In this paper, we are discussing alternate ways of assisting the seat belt web without the web-guide as a separate part. In-order to assist and ensure the motion of nylon web in its trajectory, we have extended the flange of the pillar trim involved.

Restraint systems in automotives are inevitable for the safety of passengers. Curtain airbag is one such restraint system in automotives that reduces the risk of injury to passengers during crash, without which head injury is inevitable during side crash of a vehicle. So successful deployment of curtain airbag (henceforth called as CAB) is very important in automotive safety during crash. This paper dwells about the optimization done in ramp bracket angle with successful deployment of curtain airbag. This optimization has paved the way for increasing the head-roominess by ~15% and to respect the safety and styling intent in the vehicle successfully. Providing a ramp bracket at the lower bottom side of CAB guides the airbag successfully during deployment. Ramp bracket angle plays a vital role in guiding the airbag inside the passenger’s cabin without any obstruction.

The increasing demand for higher specific power, fuel economy, Operating Costs as well as meeting global emission norms have become the driving factors of today’s product development in the automotive market. Substitution of high-density materials and more precise adjustment of material parameters help in significant weight decrease, but it is accompanied by undesirable cost increase and manufacturing complexity. This becomes a challenge for every automotive engineer to balance the above parameters to make a highly competitive design. This work is a part of the Design and Development of 2.2 L, 4 Cylinder TCIC Diesel Engine for a whole new vehicle platform, concentrated on automotive passenger car operation. This paper explains the selection of a suitable cylinder head gasket technology for a lightweight engine that acts as a sealing interface between the cylinder block and cylinder head.

As customers are inching towards adoption of electric vehicles as an alternative to internal combustion engines, automotive OEM’s will have to embrace this change and equip with new product development process. When it comes to Electric Vehicle (EV) in comparison with Internal Combustion Engine (ICE), NVH plays a major differentiator for vehicle refinement. Squeak and rattles will account for 20-25% of overall in-cabin noise source in an electric vehicle, most of which is observed from interior trims. Trims are mounted using small plastic clips which function as attachments and play a significant role in part retention and part integrity during normal operation and in case of any transient events. The engineering specifications for selecting a clip is force in newtons and it is mostly driven by ease of assembly, serviceability, and durability. A single DOF system with a specimen mass is developed and stiffness and damping are calculated based on transmissibility.

Automotive crash data analysis and reconstruction is vital for ensuring automotive safety. The objective of vehicle crash reconstruction is to determine the vehicle's motion before, during, and after the crash, as well as the impact on occupants in terms of injuries. Simulation approaches, such as PC CrashTM, have been developed to understand pre-crash and post-crash vehicle motion, rather than the crash phase behavior. Over the past few decades, crash phase simulations have utilized vehicle finite element models. While multibody simulation tools are suitable for crash simulations, they often require detailed crash test data to accurately capture vehicle behavior, which is not always readily available. This paper proposes a solution to this limitation by incorporating crash test data from databases, such as NHTSA, Global NCAP, consumer rating reports, and videos, along with a multibody-based approach, to conduct crash phase simulations.

In developing countries, manual transmissions are leading the market due to their efficiency and low cost. In a manual transmission, the synchronizers play a vital role in defining the gear shift quality. Manual transmission vehicles are getting refined for a pleasant driving experience. The gear shift quality is one of the unique selling points for the vehicle, so the automakers are focusing on the reduction of the gear shift forces. In a manual transmission, the synchronizers are used to match the speed difference between the upstream and downstream inertia for the gear-shifting process. The synchronizers have conical friction surfaces to generate friction and cone torque. The increase in cone torque reduces the gear shift impulse. The cone torque can be increased with mismatch tolerance in the frictional surfaces. In this technique, two cone angles are used for the frictional surfaces.

Internal combustion engine vehicles are major contributors to many environmental and health hazardous emissions and sometimes consume more fuel. New regulations like Corporate Average Fuel Efficiency (CAFÉ) norms are coming up and demand lower emissions. Original Equipment Manufacturers (OEMs) are committed to bringing various technological advancements in Internal Combustion Engine (ICE)powered vehicles to maximize their efficiency. Hence it is important to reduce the loss and improve the fuel economy. This paper explains a new approach methodology used for reducing the gearbox drag by 5- 10 %. This improvement can significantly contribute to the overall efficiency improvement thus carbon footprints of vehicle getting reduced.

Electric Vehicle is the need of an hour, as due to excessive usage of IC Engine vehicles has resulted in the depletion of the ozone layer to a significant level and fuel cost is increasing. With new technologies coming into the market, challenges come hand in hand because of Electric Vehicle. In comparison to IC Vehicle, areas of thermal management or the number of components for which thermal management needs to be done is higher and rather complex. As the thermal management system is the second highest energy consuming source after the powertrain of the electric vehicle, an efficient and reliable design is mandatory to ensure better range in an Electric Vehicle. Thermal Management of the Electric Vehicle has been identified as one of the critical parameters for balancing both cabin comfort as well as Battery temperature. One of the major concerns is meeting the Cabin comfort during colder weather with minimum energy consumption.

Highly competitive automotive market demands shorter product development cycle while maintaining higher standards of performance in terms of durability and Noise Vibration & Harness (NVH). Engine cranktrain system is one of the major vibration sources in engine and first torsional mode frequency is a key parameter which influences vibration characteristics. Current CAE (Computer Aided Engineering) workflow for evaluating cranktrain system performance is time-consuming and takes around 55 Hrs. It involves crankshaft geometry cleanup, stiffness calculation, 1D model building and post processing. Over the time, significant historical data has been created while performing this virtual simulation during the product development cycle. Having a trained Machine Learning (ML) model based on this historical data, which can predict first torsional mode frequency accelerates the virtual validation. In this paper, prediction of first torsional frequency of cranktrain system using ML is presented.

Modern day automotive market demands shorter time to market. Traditional product development involves design, virtual simulation, testing and launch. Considerable amount of time being spent on virtual validation phase of product development cycle can be saved by implementing machine learning based predictive models for key performance predictions instead of traditional CAE. Durability oil canning loadcase for vehicle hood which impacts outer styling and involves time consuming CAE workflow takes around 11 days to complete analysis at all locations. Historical oil canning CAE results can be used to build ML model and predict key oil canning performances. This enables faster decision making and first-time right design. In this paper, prediction of buckling behaviour and maximum displacement of vehicle hood using ML based predictive model are presented. Key results from past CAE analysis are used for training and validating the predictive model.

For decades, customer complaints on Squeak & Rattle issues have come as a question of quality for the automotive industry. Squeak and rattle sounds are customer irritants due to their non-patterned and transient nature. Squeak is a friction induced noise that generally occurs because of rubbing of the two materials that are incompatible with each other. While rattle is a phenomenon that occurs due to the impact between the two parts having unintended gap. They are no more secondary noises and avoiding or elimination of these become significant for brand building and warranty cost reduction. Chucking is a form of squeak noise that occurs due to the interaction between uncoated seal to seal. In Swing gate, this phenomenon is seen when seal bulb inner layers are completely compressed. Swing gate have fore-aft modes that are excited due to dynamic responses from different road profiles.

The passenger car segment has been extremely competitive and automotive OEMs are thriving to provide superior customer experience. Door closing is an event that requires slamming of the door with a certain velocity to get the door latched. A good latching provides that thud sound and assurance of the door getting closed for an SUV. While the door is closed, it pushes the volume of air inside the cabin. As the amount of air moved in is proportionate to the size of the door it becomes more critical for the SUV segment of vehicles to ensure the air extraction path is efficient. Else, steep pressure rise inside the cabin causes severe discomfort to the passengers sitting inside the vehicle. Current work focused on the process of simulation of cabin pressure while door closing, implementing changes based on results and validating with test results. Test results are in close correlation with simulation predictions.

Computer Aided Engineering (CAE) simulations are an integral part of the product development process in an automotive industry. The conventional approach involving pre-processing, solving and post-processing is highly time-consuming. Emerging digital technologies such as Machine Learning (ML) can be implemented in early stage of product development cycle to predict key performances without need of traditional CAE. Oil Canning loadcase simulates the displacement and buckling behavior of vehicle outer styling panels. A ML model trained using historical oil canning simulation results can be used to predict the maximum displacement and classify buckling locations. This enables product development team in faster decision making and reduces overall turnaround time. Oil canning FE model features such as stiffness, distance from constraints, etc., are extracted for training database of the ML model. Initially, 32 model features were extracted from the FE model.