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Attaining better acoustic performance and back-pressure is a continuous research area in the design and development of passenger vehicle exhaust system. Design parameters such as tail pipe, resonator, internal pipes and baffles, muffler dimensions, number of flow reversals, perforated holes size and number etc. govern the muffler design. However, the analysis on the flow directivity from tail pipe is limited. A case study is demonstrated in this work on the development of automotive muffler with due consideration of back pressure and flow directivity from tail pipe. CFD methodology is engaged to evaluate the back pressure of different muffler configurations. The experimental and numerical results of backpressure have been validated. The numerical results are in close agreement with experimental results.

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.

Achieving higher emission norms involves various techniques and it has always been a challenging task on meeting the same. Improving the exhaust temperature is indispensable in order to enhance better conversion efficiency on the after-treatment systems. This paper clearly investigates on the various strategies involved to improve the exhaust temperatures of selective catalytic reduction and post injection strategies to meet the emission norms. On the basis of MIDC operation, key load points were selected and split injections with three pulses were implemented. The variation of both the post injection timing and quantity were performed in this paper in order to evaluate the optimum output. The effect of post injection timing and quantity variation on hydrocarbon emissions, carbon monoxide, diesel oxidation catalyst temperatures was observed on all load points. The above strategy was also evaluated on generating the pressure crank angle data.

For meeting the stringent BS VI emissions in a 3-cylinder diesel engine the Exhaust after treatment system (EATS) was upgraded from a single brick DOC (diesel oxidation catalyst) to 2 brick DOC+sDPF (Diesel Particulate Filter) configuration. To meet the demands of emission regulation and sDPF requirements, changes were also required in the Fuel injection system. Major changes were done to the fuel injector and fuel pump. This paper primarily discusses the Fuel injector change from 1.1 to 2.2 family with changes in nozzle geometry, Nozzle tip protrusion (NTP), and injector cone angle and the effects on the emission and performance parameters. The various design values of NTP, cone angle, and Sac values are tested in an actual engine to meet the required power, torque and verified to meet NOx, HC, PM values as required by the new BS (Bharat Stage) VI regulation. Other boundary conditions are also checked - BSFC (Brake Specific Fuel Consumption), temperature, etc.

The emission norms around the world are continuously changing and getting stringent with every revision. India is on its way to make its emission norms at par with that prevailing in the developed nations. The cold-start condition is an important factor affecting vehicle emissions from gasoline direct injection (GDI) and port fuel injection (PFI) vehicles. In this paper, the effects of change in torque converter losses on emissions are experimentally investigated in a TGDI AT vehicle. The instant engagement of the torque converter puts a sudden load on the engine and thus affects its stability. Thus, to overcome the stability issue, Engine Torque has to be simultaneously increased for smooth engagement. As a result, the likelihood of the slightly leaner air-fuel mixture in the cylinder, which results in higher NOx formation, is much greater in an AT vehicle than that of a similar MT vehicle.

Aerodynamics of on-road vehicles has come to the limelight in the recent years. Better aerodynamic design of vehicle would improve vehicle fuel efficiency with increased acceleration performance. To obtain best aerodynamic body, the series of design modifications and different testing methodologies must be involved in vehicle design and validation phase. Wind tunnel aerodynamic force measurement, road load determination and computational fluid dynamics were the common methods used to evaluate the aerodynamic behavior of the vehicle body. As a novel approach, the present work discusses about the on-road (Real time) testing methodology that is aimed to evaluate the aerodynamic performance of vehicle body using surface pressure mapping. A 64-Channel digital pressure scanner has been utilized in this work for mapping the pressure at different locations of the typical vehicle body.

With the increase in the number of automobiles on road, there is a very strong emphasis on reducing the air pollution which led to evolution of stringent emission norms. To meet these stringent emission norms, the ideal solution is to optimize the engine hardware and the combustion system to reduce the emission at source thereby reducing the dependency on exhaust after treatment system. Gasoline Direct Injection (GDI) engines are gaining popularity worldwide as they provide a balance between fun to drive and fuel efficiency. Controlling the particle emissions especially Particle Number (PN) is a challenge in GDI engines due to the nature of its combustion system. In this study, experiments were performed on a 1.2Litre 3-cylinder 250bar GDI engine to capture the effect of injection strategies on PN.

The trace of rotavator blade is trochoidal path which depends both on tractor forward speed and rotational speed of rotavator. Since this path plays an important role in pulverization, hence pulverization also depends on both factors. In present days system, Rotavator an active tillage implements drawn by tractor is operated by drivers experience and driver set up the speed by throttling the tractor to reach the rated 540 PTO rpm mark in instrumentation cluster. Thus, there is no indication system available to farmer/ Tractor driver to operate the tractor connected rotavator at optimal forward tractor speed and rotational speed of rotavator. Thus, leading to decrease in field quality and performance.

Rotavator is an active tillage implement for breaking the Soil and for the preparation of seed bed for cultivation. The Farmers are currently facing problem due to usage of sub optimal speed of Rotavator which results in more fuel consumption, takes more time for completion of operation. Also, the Current Rental models work on Tractor + Implement as rental combination and customer not able to rent Rotavator as a standalone implement due to non-availability of Tracking information such as hours of utilization on Rotavator. Farmers not able to maintain the service periodicity, if oil change not done in prescribed duration then it may result in improper maintenance and breakdown of the Rotavator. To overcome these problems a smart Rotavator developed consists of an electronic unit fitted on the Rotavator shaft to measure the speed of the shaft rotation and in turn convert to Rotavator speed and also able to convert into Hours of usage based on the starting and stopping of the rotavator.

To meet future emission levels the industry is trying to reduce tailpipe emissions by both, engine measures and the development of novel catalytic emission control concepts. The present study will focus on the Phosphorous impact on Pt based Diesel Oxidation Catalyst after exposure to it over time based on engine oil consumption for lifetime to meet the durability requirements of Indian legislations and Indian OEMs. With BSVI announcement India along with US/Europe will ply their Automobile/Non-Road(>56Kw) engines with Diesel Oxidation Catalysts (DOC), Diesel Particulate Filters (DPF), devices for Selective Catalytic Reduction (SCR) and last but not least an Ammonia Slip Catalyst (ASC). This entire chain of After Treatment system elements play a vital role in emission reduction. Apart from this, these system elements are very much dependent on their preceding system and their performance strongly depend on the previous Catalytic function.

The present study investigates the challenges on performing the on-road regeneration process in Indian road conditions for meeting BS6 emission. There are different types (DPF and SCR) of aftertreatment systems used for meeting BS6 emission. In which, active regeneration (on-road demand) is used to burn the particulate matter accumulated in the diesel particulate filter (DPF). This process must be performed frequently in order to prevent DPF system from over soot loading which leads to damage the DPF. This process is dependent on exhaust temperature, flow of exhaust and availability of oxygen etc. As we know, Indian roads are different from other countries such as European countries. The abnormal soot loading and frequent regeneration lead to many concerns such as oil dilution, performance of the engine and life of DPF system etc.

The present work discusses the developed simulation model aimed to predict the heat rejection (HR) performance and external pressure drop characteristics of automotive charge air cooler (CAC). Heat rejection and airside pressure drop characteristics of CAC were predicted for the conditions of different charge air mass flow rates and different cooling air velocities. The lack of detailed research on CAC performance prediction has motivated the development of the proposed simulation model. The present 1-D simulation has been developed based on the signal library of AMESIM application tool. Input parameters for this simulation such as core size, tube pitch, tube height, number of tubes, fin density, louver angle, louver pitch, charge air mass flow rate, cooling air velocity, charge air inlet temperature, and ambient temperature. Heat rejection curve and airside pressure drop of CAC were the output of the present simulation.

It is imperative that all automobile manufacturers conduct vehicle level benchmarking at the initial stage of any new project. From the benchmark information, the manufacturers can set relevant targets for their own vehicles under development. In this regard, an accurate prediction of the engine operating points can improve the correlation of the measured fuel economy of the benchmark vehicle. The present work describes a novel method that can be used for the accurate prediction of the engine operating points of any benchmark vehicle. Since the idea of instrumenting the crankshaft/driveshaft with torque transducers is a costlier and time-consuming process, the proposed method can be effective in reducing the benchmarking. Hence, the objective of this work is to develop a mathematical model to calculate the real-time engine operating points (engine speed and torque) using parameters like vehicle speed, accelerator pedal map, driveline inertia, vehicle coastdown force and gradient.

The front air-dam diverts the airflow flowing through the underbody, thereby reducing aerodynamic drag. The height, shape and position of air-dam must be optimized to get improved drag. Extensive iterations are carried out to finalize the front air-dam size and position until the target is achieved. Researchers used to study the effect of air-dam height, then with fixed height will work to finalize position. Studies with interactive effect of front air-dam height and position are scanty. The existing process is time consuming as the front air-dam size and position is adjusted manually and simulation is being performed for each design and requires detailed analysis for all design iterations. The objective of this study is to couple CFD solver with design optimization software to reduce overall manual design iterations to choose the effective front air-dam geometry.

Tractor weight transfer is the most common farm-related cause of fatalities nowadays. As in India it is getting mandatory for all safety devices across all HP ranges. Considering any changes in the weight from an attachment such as Rops, PTO device, tow hook and draw bar etc. can shift the center of gravity towards the weight. center of gravity is higher on a tractor because the tractor needs to be higher in order to complete operations over crops and rough terrain. Terrains, attachments, weights, and speeds can change the tractor’s resistance to turning over. This center of gravity placement disperses the weight so that 30 percent of the tractor’s weight is on the front axle and 70 percent is on the rear axle for two-wheel drive propelled tractors and it must remain within the tractor’s stability baseline for the tractor to remain in an upright position.

In recent times, Battery electric vehicles (BEV) have gained a lot of popularity since they can contribute immensely to control the urban air pollution. However, to consider the BEVs as a sustainable mobility solution, a significant improvement is needed in several aspects including performance, range, cost, weight and recharging time. In the present work, the acceleration performance of an electric vehicle is improved to match with its diesel variant by optimizing the accelerator pedal map strategy. Due to weight and cost constraints, the battery and electric machine capacity of the electric variant of the vehicle was considerably lower (41 % lesser power and 44% lesser torque). However, the expectation from the customers is to have no noticeable difference in the low-end performance feel between the variants.

To comply with the stringent future emission mandates of light-duty diesel engines, it is essential to deploy a suitable combination of emission control devices like diesel oxidation catalyst (DOC), diesel particulate filter (DPF) and DeNOx converter (LNT or SCR). Arriving at optimum size and layout of these emission control devices for a particular engine through experiments is both time and cost-intensive. Thus, it becomes important to develop suitable well-tuned simulation models that can be helpful to optimize individual emission control devices as well as arrive at an optimal layout for achieving higher conversion efficiency at a minimal cost. Towards this objective, the present work intends to develop a one-dimensional Exhaust After Treatment Devices (EATD) model using a commercial code. The model parameters are fine-tuned based on experimental data. The EATD model is then validated with experiment data that are not used for tuning the model.

Automotive Original Equipment Manufacturers (OEMs) are always striving to deliver fast Air-Conditioning (AC) pulldown performance with consistent distribution of cabin temperature to meet customer expectations. The ultimate test is the OEM standard, called “AC Pull Down,” conducted at high ambient temperature and solar load conditions with a prescribed vehicle drive cycle. To determine whether the AC system in the vehicle has the capacity to cool the cabin, throughout the drive cycle test, cabin temperature measurements are evaluated against the vehicle target. If the measured cabin temperatures are equal or lower than the required temperatures, the AC system is deemed conventional for customer usage. In this paper, numerical predictions of the cabin temperatures to replicate the AC pulldown test are presented. The AC pulldown scenario is carried out in a digital Climatic Wind Tunnel simulation. The solution used in this study is based on a coupled approach.

Climate change is primary driver in the current discussions on CO2 reduction in the automotive industry. Current Type approval emissions tests (BS III, BS IV) covers only tailpipe emissions, however the emissions produced in upstream and downstream processes (e.g. raw material sourcing, manufacturing, transportation, vehicle usage, recycle phases) are not considered in the evaluation. The objective of this project is to assess the environmental impact of the product considering all stages of the life cycle, understand the real opportunities to reduce environmental impact across the product life cycle. As a part of environmental sustainability journey in business value chain, lifecycle assessment (LCA) technique helps to understand the environmental impact categories. To measure overall impact, a cradle to grave approach helps to assess entire life cycle impact throughout various stages.

The air velocity achieved at driver and passenger aim point is one of the key parameters to evaluate the automotive air-conditioning system performance. The design of duct, vent and vanes has a major contribution in the cabin air flow directivity. However, visual appearance of vent and vane receives higher priority in design because of market demand than their performance. More iterations are carried out to finalize the HVAC duct assembly until the target velocity is achieved. The objective of this study is to develop an automated process for vane articulation study along with predicting the optimized velocity at driver and passengers. The automated simulation of vane articulation study is carried out using STAR-CCM+ and SHERPA optimization algorithm which is available in HEEDS tool. The minimum and maximum vane angle are defined as parameters and face level velocity is defined as response.