Search Results

Reduction of NOx (Oxides of Nitrogen) and particulates from engine exhaust is one of the prime considerations in current research and development in automotive industry. The present paper describes the combustion optimization done on a four cylinder, 4 liter DI diesel engine to meet stringent Euro-III emission norms. The engine FIE (Fuel Injection Equipment) and injector geometry was optimized for performance and emission. Smoke measurements were considered as indicative of soot, to predict particulate emissions. This was done to simplify the overall process and save development time. It was concluded that by combining the flexibility of electronically controlled fuel injection begin, with improved nozzle technologies, with higher spray velocities and spray penetration, a considerable reduction in NOx and particulate emissions can be achieved. This can serve as a low cost solution, without any exhaust after-treatment systems.

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.

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.

ISOFIX anchorage plays a critical role in restraining child occupants during crashes. Effective design of ISOFIX anchorages is essential for achieving controlled child occupant kinematics. CAE simulations are extensively used for the development of ISOFIX anchorages. Comprehensive material characterization of ISOFIX wires play a vital role for achieving desired prediction accuracy. This paper covers the detailed process of ISOFIX material characterization for material failure prediction. ISOFIX wires are case hardened to exhibit required strength characteristics. Due to its material characteristics, the conventional material models don't give desired prediction accuracy for failure prediction. Therefore, advanced material models are developed in LS Dyna environment, which can accurately predict plastic and fracture behavior of ISOFIX wires.

With the current state of ever rising fuel prices and unavailability of affordable alternate technologies, significant research and development efforts have been invested in recent times towards improving fuel efficiency of vehicles powered with conventional internal combustion engines. To achieve this, a varied approach has been adopted by researchers to cover the entire energy chain including fuel quality, combustion quality, power generation efficiency, down-sizing, power consumption efficiency, etc. Apart from energy generation, distribution and consumption, another domain that has been subjected to significant scrutiny is energy recuperation or recovery. A moving vehicle and a running engine provide a number of opportunities for useful back-recovery and storage of energy. The most significant sources for recuperation are the kinetic energy of the moving vehicle or running engine and to a lesser extent the thermal energy from medium such as exhaust gas.

Global concerns over availability and environmental impact of conventional fuels in recent years have resulted in evolution of Electric Vehicles. Research and development focus has shifted towards one of its main components, Lithium-ion battery. Development of high performing, long lasting batteries within challenging timelines is the need of the industry. Lithium-ion batteries undergo “battery ageing”, limiting its energy storage and power output, affecting the EV performance, cost & life span. It is critical to be able to predict the rate of battery ageing & the impact of different environmental conditions on battery lifetime/capacity. Conventionally, extensive physical vehicle level testing is carried out on batteries to map the battery capacity in various conditions. This is a lengthy & expensive process affecting the product development cycle, paving the way for an alternative process.

Due to continuous demands from OEM's to reduce weight and make more compact vehicles, high heat generation from vehicle has become common phenomenon. Thermal insulation is a need of the hour to cater to such demands. The temperature rise is more critical around engine areas. OEM's use many design solutions to cater to such heat build up's. One of the design solutions includes use of thermally insulating materials e.g. Foams, insulating fabrics etc… First section of this paper deals with comparative study of polyurethane (PU) soft foam and rigid skin polyurethane foam. To define the base line, the samples were subjected to various tests to determine physical, thermal and chemical properties. Also both the types of foams were subjected to high temperature and low temperature heat ageing. From the experiments, it was observed that soft PU foam provides better re-bounce property than rigid skin PU foam.

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.

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.

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.

The dynamic response of structures to operating or occasional loads is crucial for design considerations, as it directly impacts the cumulative fatigue life. In practice, accurately discerning the precise loads and structural conditions, which involve considerations such as boundary conditions, geometry, and mechanical properties, can be quite challenging. Significant efforts are invested in identifying these factors and developing suitable prediction models. Nonetheless, the estimated forces and boundary conditions remain approximations, leading to uncertainties which affects the overall predictions and the analysis of how stress and strain develop in the structure during subsequent evaluations. Many researchers frequently employ a method where they estimate the forces acting on the system based on measurement data obtained at limited number of locations over the structure.

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).

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.

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.

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.

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.

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.

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.

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.

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.