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Currently the Automotive industry demands highly competitive product to survive in the global tough competition. The engine cooling system plays a vital role in meeting the stringent emission norms and improving the vehicle fuel economy apart from maintaining the operating temperature of engine. The airflow through vehicle subsystems like the grille, bumper, the heat exchangers, the fan and shroud and engine bay are called as front-end flow. Front end flow is crucial factor in engine cooling system as well as in determining the aerodynamic drag of vehicle. The airflow through the engine compartment is determined by the front-end vehicle geometry, the CRFM and CAC package, the engine back restriction and the engine compartment geometry including the inlet and outlet sections. This paper discusses the 1D modelling method for front-end airflow rate prediction and thermal performance by 1D method. The underbody components are stacked using heat stack and simulated in pressure mode.

Diesel Engines are known for its low fuel consumption coupled with high specific power output. Downsizing the engines with turbocharging and common rail injection technologies are the recent trends in improving the efficiency and performance of diesel engines. It is very challenging to match the torque targets at low speed and power targets at high speed range of a diesel engines due to system hardware limitation. Torque at lower engine speed will improve a greater extent to the drivability of a vehicle. Formation of black smoke is a major problem in lower engine speeds due lack of air availability. The use of variable geometry, two stage turbocharging and four valves per cylinder are some of the solutions which make the task simpler, also involves additional cost and fundamental design changes. At the same time commonly used waste gate turbocharger for boosting the airflow, fails to deliver required air flow at lower engine speeds.

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.

Hardware-in-the-loop (HIL) test benches are indispensable for the development of modern vehicle dynamics controllers (VDCs). They can be regarded as a standard methodology today, because of the extremely safety critical nature of the multi-sensor and multi-actuator systems used in vehicle dynamics control. The required high quality standards can only be ensured by systematic testing within a virtual HIL environment before going into a real car. The steering system is an important aspect of the automobile from operational safety and driver enjoyment perspectives. Current Problem/Opportunity is realistic subjective steering feel prediction before vehicle build. And upfront predict the handling characteristics more accurately with subjective feel before proto build. Current Issue is difficult to convert the objective data into subjective feel and difficult to incorporate the nonlinear steering characteristics with hysterics, friction and power assist curves using virtual simulation.

A four-wheeled automobile during braking event in which left and right wheels of the vehicle are on different mu surfaces, has high chances of experiencing spin, which may lead to stability issues on vehicle. This paper intends to provide a mathematical approach to predict the deceleration at which vehicle will spin during braking in a differential mu surface, and determine the effect of influencing parameters on the extent of the vehicle spin tendency. This paper also provides a correlation between theoretical vs actual decelerations for vehicles to exhibit vehicle spin tendency. This paper helps in providing sufficient aid/tool for system designer to predetermine the vehicle spin at early level of system designs and make necessary amendments at initial stage of prototype development rather than late changes, to create a product which gives safe driving experience.

The side door closing effort is one of the main evaluating parameters which demonstrates the build quality of the vehicle. The side door hinge axis inclination is one of the key attributes that affect the side door closing effort. Commonly, the hinge axis is inclined in two directions of a vehicle to have necessary door rise during the door opening event. Due to the process and assembly variations in the door assembly, the upper and lower hinge axis of the side door deviates from the design axis. In this paper, the deviations in the side door hinge axis and its effects on the side door closing velocity is discussed. The deviations of the side door hinge axis are studied with a coordinate measuring machine. The side door closing velocity of the vehicle is measured with the velocity meter. The study revealed that side door closing velocity is increasing with an increase in the deviation of the top and bottom door hinge axis from the design hinge axis.

The contribution of engine borne noise is the major source of vehicle noise in diesel powered vehicles. The engine noise can be minimized by modification of engine components design and also with different acoustic abatement techniques. The research activities were carried out on 4-cylinder CRDe engine for SUV application. All the emission and performance parameters along with combustion noise was captured continuously for all the part load points from 1000 RPM to 2750 RPM with respect to the different road conditions and driving cycle. This paper targets on reducing the combustion noise at the noise prone zones only on the basis of the injection strategies ensuring no ill effect on the emissions and fuel economy. The first step was the reduction of rail pressure which helped noise levels to be reduced by almost 6 dB at noise zones. Main injection timing retardation was tried at all possible zones which influenced in considerable noise reduction at various zones.

Costlier engine exhaust gas treatment systems as a result of stringent emission norms and increasing awareness about industrial effects on climate have pushed the automotive industry around the globe to shift its focus from fossil fuel driven vehicles to electrically powered ones. While Battery Electric Vehicles (BEVs) have some problematic issues such as lower range, lesser energy density and higher cost owing to not fully mature battery technology, they do provide some benefits such as lower carbon footprint and simpler transmission systems. The torque and power characteristics vary greatly between IC engines and electric motors. The longitudinal dynamics of a vehicle depends greatly on the nature of its powertrain. As a result, new challenges have emerged for simulation engineers who were until very recently accustomed only to IC engine driven vehicles.

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.

Oil pump is one of the important engine parasitic loads which takes up engine power through crankshaft to deliver oil flow rate according to engine demand to maintain required oil pressure. The proper functioning of oil pump along with optimum design parameters over various operating conditions is considered for required engine oil pressure. Pressure relief passage is also critical from design point of view as it maintains the required oil pressure in the engine. Optimal levels of oil pressure and flow are very important for satisfied performance and lubrication of various engine parts. Low oil pressure will lead to seizure of engine and high oil pressure leads to failure of oil filters, gasket sealing, etc. Optimization of pressure relief passage area along with other internal systems will also reduce the power consumed by the pump.

Oil pump is one of the important engine parasitic loads which takes up engine power through crankshaft to deliver oil flow rate according to engine demand to maintain required oil pressure. The proper functioning of oil pump along with optimum design parameters over various operating conditions is considered for required engine oil pressure. Pressure relief passage is also critical from design point of view as it maintains the required oil pressure in the engine. Optimal levels of oil pressure and flow are very important for satisfied performance and lubrication of various engine parts. Low oil pressure will lead to seizure of engine and high oil pressure leads to failure of oil filters, gasket sealing, etc. Optimization of pressure relief passage area along with other internal systems will also reduce the power consumed by the pump.

Current high rating thermal loaded engines must have super-efficient lubrication system to provide clean oil at appropriate pressure and appropriate lube oil temperature to every part of the engine at all engine RPM speeds and loads. So oil pump not only have to satisfy above parameters but also it should be durable till engine life. Gerotor pumps are internal rotary positive-displacement pumps in which the outer rotor has one tooth more than the inner rotor. The gear profiles have a cycloidal shape. Both are meshed in conjugate to each other. Gerotor takes up engine power through crankshaft and deliver to various engine consumers at required pressure and required time. Over the complete engine rpm speed and loads range, oil pump need to perform efficiently to provide proper functioning of the engine. Otherwise low oil pressure leads to more friction in the pump, seizure of bearings and final failure of the engine .High oil pressure can lead to failure in oil filter, gaskets and seal.

The automotive industries around the world is undergoing massive transformation towards identifying technological capabilities to improve vehicle performance. In this regard, the engine dynamic torque plays a crucial role in defining the transient performance and drivability of a vehicle. Moreover, the dynamic torque is used as a visualization parameter in performance prediction of a vehicle to set the right engineering targets and to assess the engine potential. Hence, an accurate measurement and prediction of the engine dynamic torque is required. However, there are very few methodologies available to measure the engine dynamic torque with reasonable accuracy and minimum efforts. The measurement of engine brake torque using a torque transducer is one of the potential methods. However, it requires a lot of effort and time to instrument the vehicle. It is also possible to back-calculate the engine torque based on fuel injection quantity and other known engine parameters.

In recent time, with inception of BS VI emission regulation with more focus on fuel economy and emission, many engine parts which were conventionally made from metal are getting replaced with plastic components for reducing weight to attain better fuel economy. EGR is commonly used technique to reduce emissions in diesel engine along with after treatment devices. EGR reduces peak combustion temperature inside the combustion chamber thereby reducing NOx. EGR is bypassed from the exhaust manifold, cooled down in EGR cooler and mixed with intake air at upstream of the intake manifold. Throttle valve is used for controlling the charged air flow to cylinders for different vehicle operating conditions. With compact engine layout EGR mixer are often located near to throttle valve thereby increasing the possibility of soot deposition on throttle valve.

Body in White (BIW) of an automobile serves as the shell, on which all the components that make up a vehicle, are mounted. The BIW is an assembly of press formed sheet metal components. The sheet metal composition of each component varies based on the form and functionality requirement of that component. The resulting assembly has multiple weld joineries with dissimilar compositions. The weld integrity of the joineries is crucial in maintaining the geometrical and structural integrity of the BIW. The primary welding method used in BIW assembly is Resistance Spot Welding (RSW). The quality of the weld is an outcome of a combination of multiple weld parameters. These parameters are majorly estimated based on the joinery thicknesses and material combinations. Multiple welding and testing iterations are done to fine tune the parameters for an optimum weld joinery. This is a very tedious process which increases the process time of a BIW assembly.

Condition Monitoring is the process of identifying any significant change in operating parameters of a machine, which can be indicative of a failure in future. This paper discuss a non-invasive condition monitoring methodology for sensing and investigating the problems which could be identified by noise and vibrations. This could be an easy solution for predicting failures in tractors which are operational in the field. An example of engine tappet is used to demonstrate the methodology. A disturbed setting causes a distinguishable noise, referred to as “tappet rattle”. Android smartphones (with inbuilt sensors - accelerometer, gyroscope and microphone) are used to record noise and vibration from tractors in good condition as well as in disturbed condition. Time series data analysis is done to extract relevant features and then Fourier Transform is applied to the signals for extracting frequency domain signatures.

Ride is an important attribute which must be accounted in the passenger segment vehicles. Excessive H point acceleration, Steering wheel acceleration, Pitch acceleration can reduce the comfort of the driver and the passengers during high frequency and low frequency rough road events. Excessive Understeer gradient, roll gradient, roll acceleration and Sprung mass lift could affect the Vehicle driver interaction during Steady state cornering, Braking and Step steer events. The concept architecture of the vehicle plays an important role in how comfort the vehicle will be. This paper discusses how to improve SUV ride performances by keeping handling performance attributes same or better than base vehicle. Multi Objective Optimization was carried out by keeping spring, bushing and damper characteristic as the design variables to avoid new system or component development time and cost.

Connected vehicles technology is experiencing a boom across the globe. Vehicle manufacturers have started using telematics devices which leverage mobile connectivity to pool the data. Though the primary purpose of the telematics devices is location tracking, the additional vehicle information gathered through the devices can bring in much more insights about the vehicles and its working condition. Cloud computing is one of the major enabled for connected vehicles and its data-driven solutions. On the other hand, machine learning and data analytics enable a rich customer experience understanding different inferences from the available data. From a fleet owner perspective, the revenue and the maintenance costs are directly related to the usage conditions of the vehicle. Usage information like load condition could help in efficient vehicle planning, drive mode selection and proactive maintenance [1].

Fuel economy, performance and drivability are the three important parameters for evaluating the vehicle performance. Powertrain matching plays a major role in meeting the above targets. Fuel economy is measured based on city, highway and some user defined driving cycles which can be considered as real world usage profiles. Performance and Drivability is evaluated based on the in-gear, thru-gear (acceleration performance) and grade-ability performance. The load collective points of the engine greatly influence the engines performance, fuel economy and emissions, which in-turn depends on the N/V ratio of the vehicle. The optimal selection of gear and final drive ratios plays a key role in the optimization of the Powertrain for a particular vehicle. The current study involves dynamic simulation of the vehicle performance and fuel economy at transient engine test-bed for different gear and final drive ratio combinations using AVL DynoExcat-dynamometer.

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.