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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.

Jerk in a vehicle is a feel of user which appears due to sudden acceleration changes. The amplitude and frequency components of the jerk defines quality of an engine or an AMT calibration tuning. Traditional jerk evaluation methods use amplitude (peak) of the jerk as a performance index and its frequencies are either used as weighing factor with amplitude or not taken into account. A method is proposed in this paper to quantify and differentiate the non-acceptable level of jerk which is perceivable to human body. Jerk is obtained by differentiating the acceleration data which contains the frequencies in the lower to higher range. Differentiation of such signal causes an amplification of undesired noise in both analog and digital circuits. This results in significant loss or disturbances in the useful data.

It is customary to select a twist beam rear suspension for front wheel driven small and medium range passenger cars. Besides better primary / secondary ride comfort, roll stiffness tuning ability, ease of assembly & good packaging solutions than the conventional semi trailing arm/ rigid axle suspensions, twist beam suspension system accentuate the concentration required in placing & orienting the cross beam to achieve certain imperative kinematical characteristics. In order to make the solutions of the required kinematical targets viable, it is vital to have the packaging space and stress concentration within yield limits given the weight & cost targets. This paper presents the work done on twist beam type suspension for a new generation entry level B-Class hatchback vehicle developed. To reduce the time consumed in validation of different design proposals a virtual validation process was developed.

Design of a Cabin Tilting System of heavy trucks, a multi degree of freedom mechanism, is a challenge. Factors like adequate tilting angle, cabin styling, packaging, non interference of tilting system with ride comfort, forces in the system, specifications of the hydraulic system, are all very important for designing the system. Numerous considerations make the design process highly iterative hence longer design time. This paper primarily focuses on Kinematics and Dynamic analysis of the system in ADAMS and validation of system with real time testing results. Intention of this work is to make a parametric ADAMS model and link it to a Knowledge Based Engineering application to facilitate designer to quickly carry out design iterations for reducing development time. The Knowledge Based Engineering software is made using object oriented language called ‘Object Definition Language’ which has been developed using C and C++ software languages.

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.

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.

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.

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.

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.

Fuel efficiency is one of the most important customer requirement in Indian market as well as very crucial to meet the upcoming regulation like CAFÉ for Indian Automotive manufacturers. Most of the technology changes to meet this challenge, always come with a cost penalty with hardware addition. To counter the above challenge, a strategy has been identified in the EMS software that will dynamically adapt the spark timing based on fuel octane rating. This strategy has resulted in fuel efficiency improvement on Modified Indian Drive Cycle on chassis dynamometer test and as well as on real life road tests using fuels with various octane number.

With the rise of worldwide trends towards light weighting and the move towards electric vehicles, it is now more important than ever for the automotive industry to develop and implement lightweight materials that will result in significant weight reduction and product improvements. A great deal of research has been done on how to best combine and configure honeycomb cores with the right face sheets for Truck-Mounted Container Applications. Honeycomb structures possess the ability to bring about superior structural rigidity when the core parameters are selected and optimized based on the automotive application requirements.

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).

To meet future emission levels, the automotive industry is trying to reduce tailpipe emissions through both possible pathways, i.e. emission from engines as well as and the development of novel catalytic emission control concepts. The present study will focus on the close coupled SCR on Filter commonly known as SDPF which is a main pathway to reduce NOx along with particulate mass and number for light duty passenger cars and sport utility vehicles for BS 6 RDE/OBD 2 and future legislation like BS-7. The SDPF is a challenging technology as it is critical component in exhaust after treatment system involving in NOx and PM/PN reductions hence careful optimization of this technology is necessary in terms of space velocity requirements, temperature, feed NOx emission levels, particulate mass and ash holding capacities, NH3 storage on the SDPF, and back pressure.

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.