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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.

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.

Drive cycles have been an integral part of emission tests and virtual simulations for decades. A drive cycle is a representation of running behavior of a typical vehicle, involving the drive pattern, road characteristics and traffic characteristics. Drive cycles are typically used to assess vehicle performance parameters, perform system sizing and perform accelerated testing on a test bed or a virtual test environment, hence reducing the expenses on road tests. This study is an attempt to design a relatively robust process to generate a real world drive cycle. It is based on a Six Sigma design approach which utilizes data acquired from real world road trials. It explicitly describes the process of generating a drive cycle which closely represents the real world road drive scenario. The study also focuses on validation of the process by simulation and statistical analysis.

The cabin cool down performance is influenced by heat load, AC system components and Air handling components. The air handling components are AC duct, vane and vent. Design of AC duct vane plays a crucial role in the airflow directivity in cabin which enhances the cabin cool down performance. Simulations are carried out by rotating the vanes manually and requires post process for every iteration. It leads to more time consuming and more number of simulations to achieve the target value. Research articles focusing on automation and optimization of vane articulation studies are scanty. Thus, the objective of this work is to execute the vane articulation study with less manual intervention. A parametric approach is developed by integrating ANSA and ANSYS FLUENT tools. With Direct Fit Morphing and DoE study approach from ANSA delivers the surface mesh model for the different vane angle configurations.

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.

Tensile Testing is one of the most used and highly reliable method of mechanical testing to evaluate the tensile properties of the material. However, there is a large scope for discussing the behavior of the metals based on the direction of rolling and the tensile specimen size used for testing. This paper discusses the variation observed in the tensile values along the direction of rolling and traverse to the direction of rolling for S460MC. It also evaluates the variation observed in the values based on the various gauge lengths (GL) commonly used in testing as per international standards (80mm, 50mm and 25mm GL). It is observed that perpendicular to the direction of rolling, the Yield and Tensile strength of the material increase marginally while the Elongation percentage (%E) decreases by a small margin irrespective of the gauge length taken into consideration.

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.

In an off-road vehicle, Vehicle Structure plays a major role in passenger safety, Aesthetics, Durability, through a validated construction of canopy structure. This structure is to maintain the shape of the vehicle and to support various loads acting on the vehicle. In present market a safe, Durable, Robust, Waterproof, Noise less, Light weight and cost-effective off-road vehicle will always be a delight for any customer. However, the current conventional way of Soft top vehicle structure use metal brackets and formed sheet parts to create a structure to retain the canopy shape in place. These conventional structures are often heavier and would have many demerits such as heavy weight, Corrosion, Risk of canopy tear due to metallic structure edges and inappropriate draining, water management. Considering this we replaced the heavy metal brackets in to blow molded plastic parts.

Steering returnability while driving is one of the most important parameter which affects the drive pleasure and handling of a vehicle. Steering returnability refers to the automatic returning response of the steering wheel after taking a full turn while vehicle is being steered during driving. Evaluating steering response characteristics of any vehicle in a virtual environment at early stage of a product development saves significant development time and cost. Through this paper an attempt has been made to develop a methodology for selection of suspension hard points which influences steering returnability characteristics of a vehicle at an early product design stage. Conventionally, suspension kinematic parameters such as Caster angle, Steering axis inclination (SAI), etc. are iterated during vehicle design stage to achieve desired Steering returnability.

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.

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.

Crush box in an automotive passenger car has become an integral part of structural design performing various functions like optimizing energy absorption in high speed impacts, replaceable part during low speed impacts etc. Design of crush box for high speed impacts is very important as it is the first major energy absorbing component in the load path and its deformation significantly affects the overall vehicle crash behavior. The present paper explains development of a hydro-formed crush box in the front end of a sports utility vehicle. Hydro-formed components have residual plastic strains and non - uniform thickness variation throughout their length which is difficult to measure from a physical test coupon. It is critical to add hydro-forming effects onto crash FE models as it significantly affects the deformation under high speed impact. But detailed forming simulations need mature design and material data which is not available during early phases of product development.

Tractor roll over is the most common farm-related cause of fatalities nowadays. ROPS (Roll-Overprotective Structures) are needed to prevent serious injury and death. It creates a protective zone around the operator when a rollover occurs. In India the ROPS is getting mandatory across all HP ranges except narrow track. In the present study states the customized ROPS application for configurable design such as Automated safety zone for all homologation standards, ROPS A0-D excel calculator for selection of material at concept stage and bolt calculator for selection of size. For the above applications below aspects need to consider such as Tractor weight, Rear housing mounting, Operator seat index position (SIP), Seat reference points (SRP) and all ROPS homologation standards. This ROPS application is to reduce the timeline, manual error and ensure the reliability of the modular optimal design for various platforms and variants.

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.

The complexity of Urban driving conditions and the human behavior introduces undesired variabilities while establishing Fuel economy for a vehicle. These variabilities pose a great challenge while trying to determine that single figure for assessment of vehicle’s fuel efficiency on an urban driving cycle. This becomes even more challenging when two or more vehicles are simultaneously evaluated with respect to a reference vehicle. The attempt to fit a generalized linear model, between Fuel Economy as predicted variable and components of a driving cycle as predictor variables produced oxymoronic and counter-institutive results. This is primarily due to existence of multi-collinearity among the predictor variables. The context of the study is to consider the event of driving on a cycle as a random sampling experiment. The outcome of a driving cycle is summarized into a list of predictor variables or components.