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Air conditioning systems are one of the significant auxiliary loads on the vehicle powertrain. In an Electric Vehicle (EV) where the available energy is limited, it becomes crucial to optimize the overall energy consumption of the auxiliary loads. The major power consuming components in an automotive HVAC system (Heating, Ventilation and Air Conditioning) are: Compressor, Cabin blower, Condenser cooling fan and the Control devices. Significant progress is already made in enhancing the energy efficiency of the above-mentioned power consuming components part of vehicle HVAC system. Alternate energy sources are being explored recently, to reduce the energy demand from vehicle. One such proposal is to harness the abundant solar energy available, through solar panels and consume this energy to supplement the power required for HVAC system components. Solar panels convert solar energy to electrical energy by the principle of the photovoltaic effect.

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.

This paper discusses the methodology setup for grill opening area prediction at the early development phase of the product development lifecycle, using a commercially available 1D simulation tool- AMESIM. Representative under hood has been modeled using Grill, Condenser, Radiator, intercooler, fan, and engine components. Vehicle velocity is used as an input to derive the airflow passing through the grill and other under-hood components based on ram air coefficient, pressure drop through different components (Grill, Heat exchanger, Fan & Engine). This airflow is used to predict the top tank temperature of the radiator. Derived airflow is correlated with airflow obtained from CFD simulation. A balance has been achieved between cooling drag & fan power consumption at different grill opening areas for target top tank temperature. Top tank temperature has been predicted at two different extreme engine heat rejection operating points.

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.

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.

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.

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.

In any industry, early detection and mitigation of a failure in component is vital for feasible design changes or development iterations or saving money. So it becomes pivotal to capture the failure mode in an accelerated way. This theory poses many challenges in devising the methodology to validate the failure mode. In real world, vehicle head lamp is exposed to all possible kinds of harsh environments such as variable daily ambient, rain, dust and engine compartment temperature …etc. This brings rapid thermal stress onto headlamp resulting into warpage cracks. At vehicle level on particular model, this failure is typically observed after 20,000-25,000 kms in a span of 3-4 months of running. Any corrective action to revalidate the design change or improvement will need similar timelines in regular way to test, which is quite high in product development cycle.

Lean approaches are being implemented in various manufacturing facilities across the globe. The application of lean approaches are extended to Body proto build shop to maximize the efficiency of the shop with lesser floor space and optimized equipment. Weld fixture, Weld equipment and assembly tools are the major tools required essentially for proto BIW assembly. This paper explains how the Weld equipment planning was carried out with lean approaches and implemented effectively in proto body assembly shop. The implemented lean concepts are compared with Italy and Japanese proto body build makers to validate the frugal planning of the facility for the said intent. The implemented facility is capable of producing more than a model at a time. Weld parameter selection for weld gun, gun movement to the fixture with minimized change over time and movable weld gun gantry are the lean approaches implemented.

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.

Lubrication system is a critical factor for engine health. But it creates parasitic load and increased fuel consumption of the engine. The oil demand of an engine depends on engine speed, load, bearing clearances, operating temperature and engine's state of wear. Ideally, the oil pump should adapt the delivery volume flow to actual engine oil demand and should avoid unnecessary pumping of oil which causes increased power and fuel consumption. However in a conventional mechanical oil pump, there is no control on the oil flow and it is purely a function of operating speed. A variable discharge oil pump (VDOP) is an approach to reduce the parasitic losses wherein the oil flow is regulated based on the mechanical needs of the engine. This study is based on the results of a two stage VDOP installed on a 1.2 litre, 3 cylinder MPFI engine. The oil supply is regulated by a solenoid control which receives command from Engine Control Unit (ECU). The study was done in two stages.

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.

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.

Body in White (BIW) is an assembly of multiple sheet metal components. BIW is a major contributor to the dimensional and structural integrity of an automobile. The accuracy and precision of the BIW is influenced by multiple factors involved in the manufacturing lifecycle of the BIW, of which component development and assembly strategy are the most significant contributors. Weld fixtures are the tools used for accurately locating and holding, sheet metal components for joining. The primary motive of the locating and holding strategy is to arrest all degrees of freedom of a component. Geometric repeatability of the components is also of high importance. Component location is typically achieved by standardized locator pins that maintain the Principal Location Points (PLP). Mylars provided at Master Control Patches (MCP) ensure the resting and clamping of the component. Low volume BIW builds employ non-automated clamping methodologies, either with manual clamps or toggle clamps.

Air conditioning systems are one of the significant auxiliary loads on the vehicle powertrain. In an Electric Vehicle (EV) where the available energy is limited, it becomes crucial to optimize the overall energy consumption of the auxiliary loads. The major power consuming components in an automotive HVAC system (Heating, Ventilation and Air Conditioning) are: Compressor, Cabin blower, Condenser cooling fan and the Control devices. Significant progress is already made in enhancing the energy efficiency of the above-mentioned power consuming components part of vehicle HVAC system. Alternate energy sources are being explored recently, to reduce the energy demand from vehicle. One such proposal is to harness the abundant solar energy available, through solar panels and consume this energy to supplement the power required for HVAC system components. Solar panels convert solar energy to electrical energy by the principle of the photovoltaic effect.

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.

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.

The tough emission limits of BSVI norms with very low levels of NOx and PM emissions presents major techno economic challenges for the automobile industry. Combined efforts of pollutants reduction by combustion modification as well as the exhaust after treatment devices could only facilitate to achieve the desired emission targets. selective catalytic reduction technology is a mandatory system which uses ammonia from the aqueous urea solution to react with NOx forming nontoxic by products. The cost spent on aqueous urea solution in addition to the cost of BSVI diesel encounters high operating cost for the vehicle. NOx reduction by SCR too requires adequate quantity of ammonia from the AdBlue. Hence sensible utilization of DEF is essential for reduced running cost of the SCR system. SCR efficiency is higher for higher exhaust temperature and it requires minimum exhaust temperature above which only it operates.

Body in White (BIW) is one of the critical aggregates of an automobile. Establishing the quality parameters during body manufacturing is essential to achieve robust BIW structure. Spot weld integrity and dimensional accuracy are the two major quality parameters of a BIW. Weld integrity plays an important role in achieving dimensional accuracy and structural stability. Various combinations of sheet metals are joined together to form a BIW structure. Spot weld parameter selection is one of the critical activity and needs to be programmed for the various combinations of sheet metals. Weld parameter for the various combinations are calculated with the resistance of the joining sheet metals thicknesses. The calculated parameters are validated with the coupon test (or) peel test and it requires several iterations to establish weld integrity of the different combinations and the selected parameters get registered in the weld controller.