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In present study a comparative investigation and correlation attempted on small scale vehicle model for aerody-namic drag performance at small scale wind tunnel test facility in India vs full vehicle tested at globally know and accepted full scale test facility in Pininfarina, Italy. Current investigation aims to assess the small-scale wind tunnel suitable for testing 1:3 small scale car models A scale model of 1:3 scale size was tested in small scale wind tunnel (at IISC,Bengaluru, India) having test section area of 11.68 Sq. m. To understand the overall vehicle aerodynamic drag performance small scale model was test-ed for different configurations such as baseline, spoiler removal, underbody cover and different yaw condition. To understand the correlation between small scale vs full vehicle’s aerodynamic performance one actual vehicle was also tested at full scale wind tunnel Pinifarina Italy.

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.

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) 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.

This paper presents a comprehensive model of a hydraulic power steering system for predicting the transient responses under various steering inputs. The hydraulic system model, which integrates together all fluid line elements and hydraulic components, is formulated using the MSC Easy5 software. A full vehicle model is developed in ADAMS/Car. Functional Mock up Interface (FMI), a tool independent standard is used for co-simulation of ADAMS and Easy5 Dynamic models. This paper describes a co-simulation methodology developed using FMI interface for full vehicle Simulations using hydraulic power steering. A virtual simulation scheme is developed to obtain the system transient responses and the results are compared with those measured from the tests. In general, the simulation results agree with those obtained from the tests under the same steering inputs and operating conditions.

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.

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.

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.

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.

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.