Search Results

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).

Worldwide automotive sector regulatory norms have changed and become more stringent and complex to control environmental noise and air pollution. To continue this trend, the Indian Ministry of Road Transport is going to impose new vehicle exterior pass-by noise regulatory norms IS 3028:2023 (Part2) to control urban area noise pollution. This paper studies the synthesis of M1 category vehicle driving acceleration, dominant noise source, and frequency contribution in exterior PBN level. A vehicle acceleration analysis study was carried out to achieve an optimized pass by noise (PBN) level based on the vehicle’s PMR ratio, reference, and measured test acceleration data. Based on the analysis, test gear strategy was decided to achieve a lower PBN level. This strategy involved increasing the effective final drive ratio and optimizing engine calibration, resulting in improvement with acceleration in the ith gear.

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.

Vehicle transmission gear rattle is one of the most critical NVH irritants for refined vehicles. It is perceived more dominantly in lower gears of vehicle running. It depends on various design parameters like engine input torque amplitude & fluctuations, driveline torsional vibrations, gear micro & macro geometry, shaft flexibility, etc. Establishing exact contribution of each of these parameters to transmission rattle, thru experimental or simulation technique, is very challenging. Current paper explains the NVH CAE benchmark approach deployed to understand difference in rattle behavior of two transmission designs. Paper focuses on simulation of gear impact power and its sensitivity to transmission shaft deflections.

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.

Climate change due to global warming are major concerns. Electric vehicles are one of the promising technologies to curb the climate change by reducing CO2 emissions significantly. Electric vehicle component selection is a complex process, which has to fulfil multiple requirements with trade-off between performance & efficiency, efficiency & cost, performance & NVH, packaging & performance etc. In addition, E-drive selection in passenger & commercial vehicle is different due to application difference. Hence, it is a great challenge to select right E-Drive comprising motor, MCU and overall gear ratio to meet EV program constraints and targets. This study focuses on criterion used for selecting an E-Drive system comprising motor, MCU and overall gear ratio for electric vehicles in commercial and passenger vehicle segments.

In comparison to traditional gasoline-powered vehicles, Electric vehicles (EVs) development and adoption is driven by several factors such as zero emissions, higher performance, cost effective in maintenance, smoother and quieter ride. Global OEMs are competing to provide a reduced in-cab noise for ensuring a smooth and quiet driving experience. Short project timelines for EV demands quick design and development. In initial stages of project, input data availability of EV is limited and a simplified approach is necessary to accelerate the development of vehicle. This paper focuses on simulation methodology for predicting structure borne noise from powertrain deploying Transfer Path Analysis approach. Current simulation methodology involves full vehicle model with multiple flexible bodies and full BIW flexible model which leads to complex modelling and longer simulation times.

Advent of EV powertrain has considerable effect on transmission development activities as competed to regular ICE transmission. Conventional ICE transmission and the transmission for an e-powertrain differ on fundamental level. The conventional transmission has number of gear ratios, shift mechanism which enables the transmission to deliver a smooth power output as per demand from the driver. Whereas the e-powertrain transmission is mostly a single gear ratio transmission (reducer) which primarily depends on speed and torque variation from the motor to cater the driver requirement. Hence, the operating speeds of such e-transmissions can vary from 0 to 20000 rpm in both forward and reverse directions. Such a large speed variation as compared with conventional transmission calls for special attention towards the lubrication of internal components. High speeds and lower oil viscosities tend to disrupt the oil films in between contact surfaces causing metal to metal contact.

Sustainability has evolved from being just a niche engagement to a fundamental necessity. The reduction of carbon emissions from aspects of human activity has become desirable for its ability to mitigate the impact of climate change. The Transportation industry is a critical part of the global economy – any effort to curb emissions will have a significant impact on CO2 reduction. Engine lubricant can play an efficient and key role to enhance powertrain performance that have undergone significant hardware changes to reduce emissions. As part of a significant collaborative programme between Tata Motors and Infineum, a new engine oil formulation SAE 5W-30 API FA-4 has been developed and commercially introduced for use in the modern Bharat Stage 6 Phase 2 engines.

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.

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.

The traditional method of collecting the Road Torque Data of a vehicle is by instrumenting and running the vehicle on different road terrains. Every time, physical testing becomes tedious & most challenging task due to unavailability of unit under tests, kind of resource required and so on. However, in view of response to the fast emerging technology & limit less competition, it has become mandatory to develop & launch products in market within no time. In recent times, there is increased demand for physical road torque data measurements for a vehicle program based on its application and different powertrain configurations, which clearly shows that unless we front load the data to design it is practically impossible to meet the deadlines. Each of these measurements cost and consumes valuable resources of the company in collecting and analyzing the data.

Now a day’s automated manual transmissions (AMT) are getting popular because of hassle-free gear shifting and improved fuel economy. OEMs are converting their existing manual gearbox to AMT gearbox with solution like hydraulic or electric AMT kit that replaces the manual shift mechanism to automated actuators. Generally, in manual gearbox, the operational principal of reverse gear is sliding mesh. Due to sliding mesh gear arrangement, it can create interruption for gearshift while controlling shift actuators. In this paper, reverse gear shift arrangement and its operational dynamics at different operating condition has been studied and analyzed in detail. Based on status of vehicle, to ease the gearshift, engagement flow process proposed. The control methods that increases probability of smooth and easier shifting in all operating condition discussed in detail. The developed control algorithm discussed along with its implementation on real vehicle and results.

Drive components of live axle undergoes different loading conditions during field usage depending upon terrain conditions, vehicle loading and traffic conditions etc. During vehicle running, drive components of axle experiences variable torque levels, which results in the fatigue damage of the components. Testing of these drive components of axle on test rig for endurance life is an imperative part of axle development, owing to limitations of vehicle testing because of time and cost involved. Similarly, correlating field failures with rig testing is equally critical. In such situation, if a test cycle is derived correlating the field usage, rig testing can be effectively used for accelerated life testing and reliability prediction of these components. An approach is presented in the paper wherein test cycle is derived based on the data collected on vehicle in the field under service road and loading conditions.

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.

Pneumatic brake system is widely used in heavy truck, medium and heavy buses for its great superiority and braking performance over other brake systems. Pneumatic brake system consists of various valves such as Dual Brake Valve (DBV), Quick release Valve (QRV), Relay Valve (RV), Brake chambers. Dynamics of each valve is playing a crucial role in overall dynamic performance of the braking system. However, it is very difficult to find the contribution of each valve and pipe diameters in overall braking performance. Hence, it is very difficult to arrive a best combination for targeted braking performance as it is not possible to evaluate all combination on the actual vehicle. Hence, it is very important to have a mathematical model to optimize and evaluate the overall braking performance in early design phase. The present study is focusing on the mathematical model of a pneumatic brake circuit.