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To meet different target of light-weighting, lower fuel economy, crash safety and emission requirement, advanced high strength steel (AHSS) is commonly used in automotive vehicles and has become popular now a days. AHSS material up-to 1500 MPa is commonly used for structural components and major reinforcement of automotive BIW. Manufacturing of AHSS material requires precise control of chemical composition, and subsequent rolling and heat treatment to get optimum combination of required phases In most of the AHSS material microstructure, martensite is present along with ferrite or other phases. Hot stamp steel with strength level 1500 MPa strength also have martensite phase in microstructure after press hardening. However during heating and cooling cycle in resistance spot welding, martensite phase tempering affects hardness at Heat Affected Zone (HAZ).

The auto industry is one of the major contributors for noise pollution in urban areas. Specifically, highly populated heavy commercial diesel vehicle such as buses, trucks are dominant because of its usage pattern, and capacity. This noise is contributed by various vehicle systems like engine, transmission, exhaust intake, tires etc. When the pass by noise levels exceeds regulatory limit, as per IS 3028, it is important for NVH automotive engineer to identify the sources & their ranking for contribution in pass by noise. The traditional methods of source identification such as windowing technique, sequential swapping of systems and subsystems which are time consuming.Also advanced method in which data acquisition with a synchronizing technology like telemetry or Wi-Fi for source ranking are effective for correctness.However they are time and resource consuming, which can adversely impact product development timeline.

Nowadays, friction welding is recognised as a highly productive and economic joining process for similar as well as dissimilar welding of automobile and aerospace components. Friction welding is the viable solution to offset the challenges of dissimilar fusion welding due to varying thermal and physical properties as well as limited mutual solubility. This study investigated interface microstructure and bonding strength of dissimilar rotary friction welding of 3.15 mm E46 plate and 45 mm AA6061-T6 rod. The direct drive rotary friction welding of E46 and AA6061-T6 is performed at combinations of two different friction times (4 sec and 7 sec) and forging pressure (108 MPa and 125 MPa). Mechanical bonding strength at the interface is evaluated based on the push-off and multistep shear tests. Further, a fractured steel surface was visually examined to understand the failure mechanism of welded joints.

High strength aluminium alloys are an ideal material in the automotive sector leading to a significant weight reduction and enhancement in product safety. In recent past extensive development in the field of high strength steel and aluminium was undertaken. This development has been propelled due to demand for light weight automotive parts. The high strength to weight ratio possessed by Al alloy helps in reducing the total weight of the vehicle without effecting the overall performance, thereby increasing the fuel economy, and reducing the carbon emission level. Joining of high strength aluminium alloy is critical to develop durable automotive products. Joining of high strength aluminium alloy for mass production in automobile industry is a challenging task. Laser welding is recognized as an advanced process to join materials with a laser beam of high-power, high- energy density.

The stress concentration at welded joints and small crack propagation from some pre-existing discontinuities at notched regions control the fatigue life of typical welded structures. There are numerous FEM stress-based weld fatigue assessment approaches available commercially which unify FEM stresses with various fatigue software codes embedded with international weld standards. However, FEM stress-based approaches predict extensively conservative results. Considerable efforts & subjective decision making is required to arrive at desired level of weld life correlation with physical test results, in terms of weld life and failure location. This is majorly because of inconsistency & inaccuracy in capturing the hot spot stress results due to stress singularities occurring at the notched regions owing to the mesh sensitivity, modeling complexity.

The art of rubber formulation science always has a scope for fine-tuning with changing the parameters like base polymer grade selection, filler selection, curing system/cross link density, manufacturing methods, and many. Hence forth the filler manufacturer arrived differentiation of the filler already, this paper provides a description of rubber formulation tuning for damped vibration automotive applications. Acicular spiky spherical and hollow spherical nano silica selected as filler. With the thorough knowledge of elastomeric formulation and with doping different new selected silica grades, an optimized DOE was done. New formulation development was focused on isolation characteristics without affecting other necessary properties. The different inputs for finite element calculations was studied with the effects of doping different fillers and also studied the resultant virtual output in damping coefficients.

This paper focuses on developing an application to extract insights from Android app reviews of Connected Car Applications and Twitter conversations related to OEM’ PV & EV Vehicles and features. Analyzing user sentiments and preferences in real-time can drive innovation and elevate OEMs' customer satisfaction. These insights have the potential to enhance vehicle performance and the manufacturing process. The application employs data collection and Natural Language Processing (NLP) techniques, including User-Driven Sentiment Classification and topic modeling, to analyze user sentiments and identify key discussion topics visually.

With India achieving the BSVI milestone, the diesel particulate filter (DPF) has become an imperative component of a modern diesel engine. A DPF system is a device designed to trap soot from exhaust gas of the diesel engine and demands periodic regeneration events to oxidize the accumulated soot particles. The regeneration event is triggered either based on the soot mass limit of the filter or the delta pressure across it. For a Heavy Duty Diesel Engine (HDDE), pressure difference across the DPF is not usually reliable as the size of the DPF is large enough compared to the DPF used ina passenger vehicle diesel engine. Also, the pressure difference across DPF is a function of exhaust mass flow and thus it makes it difficult to make an accurate call for active regeneration. This demands for a very accurate soot estimation model and it plays a vital role in a successful regeneration event.

Welding is one of the most convenient and extensively used manufacturing process across every industry and is recognized as a cost effective joining technique. The root cause of most of the fabricated structural failures lies in the uncertainties associated with the welding process. It is prone to generate high residual stresses due to non-volumetric changes during heating and cooling cycle. These residual stresses have a significant impact on fatigue life of component leading to poor quality joints. To alleviate these effects, designers and process engineers rely upon their experience and thumb rules but has its own limitations. This approach often leads to conservative designs and pre-mature failures. Recent advances in computational simulation techniques provide us opportunity to explore the complex phenomenon and generate deep insights. The paper demonstrates the methodology to evaluate the residual stresses due to welding in virtual environment.

The basic function of steering system is to control the direction of the vehicle. The driver applies effort on the steering wheel and receives feedback through the steering system as a result of tire to road interaction. This feedback consists of a haptic (force) feedback which is directly felt by the driver and it is termed as steering feel. Precise steering feel gives better driving experience and is decisive factor for customer to buy a vehicle as well as for OEMs in building brand image. Along with steering parameters, suspension and tire parameters also has significant impact on steering feel. In past, modelling of the steering system was done at component level or with simplified vehicle system. Such approaches had not given accurate results of steering feel metric and resulted in incorrect steering design parameter selection. In order to replicate actual vehicle characteristics, complex and detailed modelling of steering, tire and suspension subsystems is necessary.

Automotive OEMs are launching multiple products with ever reducing development time, balancing costs, quality and time to market, with clear focus on performance and weight. Platform architecture concepts, modular designs for differentiation etc. are strategies adopted by automotive OEMs towards shorter development cycles. Thus, concept generation phase of the digital product development process is expected to enable generation and evaluation of multiple concept architectures, carry out performance studies and largely focus on optimization, upfront. This Front loading of engineering and call for simultaneous engineering requires support in terms of quick and good CAD modeling with maturity. This paper proposes a process that focuses on generation and evaluation of multiple concepts, besides enabling optimization of concept before the detailed design phase kicks in.

Structural adhesive is a good alternative to provide required strength at joinery of similar and dissimilar materials. Adhesive joinery plays a critical role to maintain structural integrity during vehicle crash scenario. Robust adhesive failure definitions are critical for accurate predictions of structural performance in crash Computer Aided Engineering (CAE) simulations. In this paper, structural adhesive material characterization challenges like comprehensive In-house testing and CAE correlation aspects are discussed. Considering the crash loading complexity, test plan is devised for identification of strength and failure characteristics at 0°, 45°, 75°, 90°, and Peel loading conditions. Coupon level test samples were prepared with high temperature curing of structural adhesive along with metal panels. Test fixtures were prepared to carryout testing using Instron VHS machine under quasi-static and dynamic loading.

Spot welding is the primary joining method used in automobiles. Spot-weld plays a major role to maintain vehicle structural integrity during impact tests. Robust spot weld failure definitions is critical for accurate predictions of structural performance in safety simulations. Spot welds have a complex metallurgical structure, mainly consisting of fusion and heat affected zones. For accurate material property definitions in simulation models, huge number of inputs from test data is required. Multiple tests, using different spot weld joinery configurations, have to be conducted. In order to accurately represent the spot-weld behavior in CAE, detailed modeling is required using fine mesh. The current challenge in spot-weld failure assessment is developing a methodology having a better trade-off between prediction accuracy, testing efforts and computation time. In view of the above, cohesive zone models have been found to be very effective and accurate.

Brake drum is an important component in automotive, which is a link between axle and wheel. It performance is of utmost importance as it is related to the safety of the car as well to the passengers. Many design parameters are taken into consideration while designing the brake drum. The sensitivity of these parameters is studied for optimum design of brake drum. The critical parameters in terms of reliability, safety & durability could be the cross section, thickness of hub, interference & surface roughness between bearing and hub, wheel loading, heat generation on drum, manufacturing and assembly process. The brake drum design is derived by considering these parameters. Hence the sensitivity of these parameters is studied both virtually & physically, in detail. The optimum value of each parameter could be chosen complying each other's values.

Micro Hybrid Systems are a premier approach for improving fuel efficiency and reducing emissions, by improving the efficiency of electrical energy generation, storage, distribution and consumption, yet with lower costs associated with development and implementation. However, significant efforts are required while implementing micro hybrid systems, arising out of components like Intelligent Battery Sensor (IBS). IBS provides battery measurements and battery status, and in addition mission critical diagnostic data on a communication line to micro hybrid controller. However, this set of data from IBS is not available instantly after its initialization, as it enters into a lengthy learning phase, where it learns the battery parameters, before it gives the required data on the communication line. This learning period spans from 3 to 8 hours, until the IBS is fully functional and is capable of supporting the system functionalities.

Use of adhesives in automotive require in-depth material, design, manufacturing & engineering knowledge. It is also necessary to understand functional requirements. For perfect and flawless adhesive joinery, the exact quantity of adhesive, its material composition, thickness of adhesive layer, substrate preparation methods for adhesive bonding, handling and curing time of the adhesive have to be studied & optimized. This paper attempts to describe different aspects of adhesive bonding in automotive industry to include: Selection of adhesives based on application and design of the components, surface preparation of adherend, designing of adhesive joint, curing conditions of adhesives, testing and validation of adhesive joints. Emphasis was given to study & verify the performance of different adhesive joints to meet end product requirements. Samples were prepared with a variety of adhesive and adherend combinations.

Shock tube is used to simulate blast loading conditions on materials for studying the failure behavior of different materials under blast pressures on smaller scale. This paper describes CAE method developed for simulating shock tube experiment in LS-DYNA3D environment. The objective of shock tube simulation is to characterize material failure parameters so as to predict risk of material failure in full vehicle blast simulations while developing vehicle for blast protection applications. The paper describes modeling of shock wave and its interaction with test specimen in shock tube environment. Arbitrary Lagrangian-Eulerian (ALE) techniques are applied to simulate shock tube experiment in LS-DYNA3D and simulation predictions are compared with experimental test data. CAE correlation studies were carried out with respect to incident and reflected pressures in shock tube, deformation and plastic strains on test specimen, shock wave velocity etc.

Computer Aided Engineering (CAE) plays an important role in the product development. Now a days major decisions like concept selection and design sign off are taken based on CAE. All the Original Equipment Manufacturers (OEMs) are putting consistent efforts to improve accuracy of the CAE results. In recent years confidence on CAE prediction has been increased mainly because of good correlation of CAE predictions with the test results. Defining proper correlation criteria and using a systematic approach helps significantly in building the overall confidence level for predictions given by CAE simulations. Representation of manufacturing effects on material properties and material failure in the simulation is still a big challenge for achieving a good CAE correlation. This paper describes side impact test vs CAE correlation. The important parameters affecting the CAE correlation were discussed.

There has to be a good co-relation/ relationship between the pedal effort applied, pedal travel, deceleration level achieved and stopping distance for “good brake feel”. Brake feel also depend upon the time lag between the force applied on brake pedal and the response of braking system. Hence “brake feel” can be improved by reducing the response time of the brake system. Many vehicles are having “poor brake feel” complaints, pertaining to the above mentioned reasons. This paper relates to an improved brake system for automobile in which reduction in reaction time was done by artificially increasing differential pressure head across vacuum booster diaphragm. Brake booster is given an input of compressed air to the valve body during actuation, thereby increasing the differential pressure across the diaphragm. The compressed air is bled from turbocharger-intercooler of the vehicle which is stored in a reservoir, with one way valve, while cruising.

Passive safety regulations specify minimum safety performance requirements of vehicle in terms of protecting its occupants and other road users in accident scenarios. Currently for majority cases, the compliance of vehicle design to passive safety regulations is assessed through physical testing. With increased number of products and more comprehensive passive safety requirements, the complexity of certification is getting challenged due to high cost involved in prototype parts and the market pressures for early product introduction through reduced product development timelines. One of the ways for addressing this challenge is to promote CAE based certification of vehicle designs for regulatory compliance. Since accuracy of CAE predictions have improved over a period of time, such an approach is accepted for few regulations like ECE-R 66/01, AIS069 etc which involves only loadings of the structures.