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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.

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.

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.

The need for eco-friendly vehicle powertrains has increased drastically in recent years. The most critical component of an electric vehicle is the battery pack/cell. The choice of the appropriate cell directly determines the size, performance, range, life, and cost of the vehicle. Lithium-ion batteries with high energy density and higher cycle life play a crucial role in the progress of the electric vehicle. However, the packaging of lithium-ion cells is expected to meet lots of assembly demands to increase their life and improve their functional safety. Due to their low mechanical stability, the lithium-ion cell modules must have external pressure on the cell surface for improved performance. The cells must be stacked in a compressed condition to exert the desired pressure on the cell surface using compression foam/pads. The compression pads can be either packaged between each cell or once in every set of cells based on the cell assembly requirements.

Accurate ride and handling prediction is an important requirement in today's automobile industry. To achieve the same, it is imperative to have a good estimation of damper model. Conventional methods used for modelling complex vehicle components (like bushings and dampers) are often inadequate to represent behaviour over wide frequency ranges and/or different amplitudes. This is difficult in the part of OEMs to model the physics-based model as the damper’s geometry, material and characteristics property is proprietary to part manufacturer. This is also usually difficult to obtain as a typical data acquisition exercise takes lots of time, cost, and effort. This paper aims to address this problem by predicting the damper force accurately at different velocity/ frequency and amplitude of measured data using Artificial Neural Networks (ANN).

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.

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.

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.

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.

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.

Diesel engines have occupied a significant position in passenger car applications in the present automotive sector. Turbochargers find a very prominent role in diesel engines of all applications in order to achieve desired power and better fuel economy. Gaining higher torque at lower engine speeds with low smoke levels is a very tough task with fixed geometry turbochargers due to availability of lower air mass resulting in higher smoke emissions. Variable geometry turbochargers are capable of providing better torque at lower speeds and reduced smoke emissions on Common Rail Diesel engines. The Variable Geometry Turbocharger types used in this study are straight profile nozzle vanes (sample A) and curved profile nozzle vanes (sample B). The curved profile vanes as seen in sample B results in reduced variation of circumferential pressure distortions.

Differential in Gear Box play vital role in Tractors for assisting it in turning and also to take straight path. Light weight machine always have advantage in terms of fuel economy and performance. Weight optimized rotating part have additional benefits of saving power loss, against stationary dead weight. Differential Housing is such a part, which rotates during the vehicle motion and torque transmission. [1] This paper describes a method by which weight of the Differential Housing is optimized. In this particular body of work, additional constraints of avoiding any change in existing cold forged parts like Bevel Gear & Pinion. This also have additional benefit of enhanced flow of Oil inside Differential Housing for better lubrication of Bevel Gears and Pinion. This resulted in weight saving of Differential Housing and finally fuel economy of Tractor.

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 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.

In the present scenario, when the vehicle is maneuvering in the gradient, more clutch and accelerator pedal modulations is needed during stop and go condition. These kinds of pedal modulations are not desirable for many customers as it requires more skilled driving. Failure of doing such actions will even result in engine stalling which becomes an annoyance to such customers. In order to overcome this problem, the low idle speed of the engine can be increased only during the drive-off condition. In this paper, we proposed the development and real-time testing of the control algorithm to increase the engine low idle speed during drive-off. This proposed algorithm detects the drive-off condition and then an offset value is added to increase the low idle speed. Various input conditions are considered to enable or disable the increment of engine low idle speed. The control algorithm has been developed using MATLAB/Simulink tool and tested using ETAS EHOOKS tool.

Objective metrics for performance evaluation of ride, handling and steering are required to compare, validate and optimize dynamic behavior of vehicles. Some of these objective metrics are recommended and defined by International Organization for Standardization (ISO) and Society of Automotive Engineers (SAE), which involve data processing, statistical analysis and complex mathematical operations on acquired data through simulation or experimental testing. Due to the complexity of operations and volume of data, evaluation is often time consuming and tedious. Process automation using existing tools such as MS Excel, nCode, Siemens LMS, etc. includes several limitations and challenges, which make it cumbersome to implement. This work is about development of a centralized platform for quantification, visualization and comparison of ride, handling and steering performance metrics obtained from testing and simulation data as per relevant ISO standards.

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.

Improving the fuel economy of the vehicle resulting in energy conservation on long run is a challenging task in the automotive field without compromising the emission margins. Fuel economy improvement by effective driving is the main focus of this paper by the proper utilization of gears which can enable good fuel economy even when the vehicle is driven by different drivers. GSI technique was implemented on Sports utility vehicle operating with 2.2 l engine. Tests were carried with GSI and the effect of fuel consumption and emissions were compared to the regular driving cycle. Optimization of various gear shifting points were analyzed and implemented for better fuel economy keeping the drivability in mind, meeting the BS4 emission norms comfortably. The experiments were carried out in both cold and hot conditions to check the effect of GSI and positive results of fuel economy improvement was yielded.

The combustion strategies play a key role in emission improvisation and noise reduction on diesel engines equipped for higher emission norus. This paper clearly discussed on the selection of various operating points for optimization and employing of proper calibration strategies like pilot strategy, Main injection timing, EGR type and rail pressure variation for best emission and noise output. Various optimization techniques have been implemented in our study. Since the pilot injection quantity as well as timing are varied in our paper, careful matrix formulation is required to determine the best optimum point. Around 340 points were obtained on varying pilot quantity and pilot separation sweep chosen at single engine speed and load for both the pilots. Out of the above points, 5 sensitive points were selected ensuring the sensitivity of the emissions and noise.