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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.

The trace of rotavator blade is trochoidal path which depends both on tractor forward speed and rotational speed of rotavator. Since this path plays an important role in pulverization, hence pulverization also depends on both factors. In present days system, Rotavator an active tillage implements drawn by tractor is operated by drivers experience and driver set up the speed by throttling the tractor to reach the rated 540 PTO rpm mark in instrumentation cluster. Thus, there is no indication system available to farmer/ Tractor driver to operate the tractor connected rotavator at optimal forward tractor speed and rotational speed of rotavator. Thus, leading to decrease in field quality and performance.

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.

The adoption of BSVI emission norms for Indian domestic market brought a very stringent window for pollutants. For CI engines, the major impact was in the reduction of NOx by 68% and PM by 82% from BSIV norms. Technologically advanced after treatment systems like SCR / DPF / LNT aid to meet the stringent emission norms. Implementation of high-end after treatment systems in vehicles, requires precise monitoring and fool proof feedback systems. On Board Diagnostics (OBD) makes this possible. OBD is used to monitor the performance of after treatment systems and warn the user in case of deterioration. The challenges in framing OBD strategy increases with more electronic hardware and complex algorithms taking control, to monitor precise information on system performance. For a fool proof OBD monitoring of the exhaust system, a complete understanding of the SCR system and its components in terms of hardware specifications and software functionality is critical.

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.

This paper deals with the study of the phenomenon of crevice corrosion of aluminium by using an example of a corrosion failure of a joint in the automobile coolant circuit. A number of joint failures were studied to understand the corrosion pattern and for various metallurgical aspects like chemistry, hardness and microstructure. The corrosion products were analyzed using Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray Spectroscopy (EDS). This analysis indicated that the corrosion products mostly contained Aluminium Oxides with other contaminants like chlorides. The studies revealed that the clamped joint of the aluminium part and rubber hose led to the formation of a crevice with the engine coolant acting as the corrosive medium. The corrosion behavior at the location was affected by environmental factors like temperature, pH and chloride contamination.

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.

This paper makes an attempt to focus on a study to evaluate angle of vision and obstruction in a vehicle, it is an objective assessment through different percentiles of population. In a view of Safety and comfort of a driver, a good perception of environment in which his vehicle is operating will be a determining component. Driver visibility and hidden corner in vehicle is a major safety area for passengers and pedestrian. Driver eye vision is an important key factor to design vehicle windshield, rear window and A-Pillar/ B-Pillar, positioning of side view mirror and IRVM based on anthropometry data. This study focuses on method of capturing and measuring the i) Driver's Direct field of vision that the driver sees directly by moving his/her eyes ii) Driver's Indirect field of vision in which driver views indirectly by using imaging devices Rear View mirror, Display cameras. iii) Driver's Angle of obstruction - by A pillar, B pillar.

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 farm tractors, front end loaders are becoming popular attachments for primarily material handling such as loading, moving and unloading of woodchips, sand, gravels etc. It is also used for some severe load application such as tree uprooting and ripping operation which requires validation of loader frame and tractor as well. To validate the design, a standard pull-push test is carried out on tractor with loader in a laboratory. In this test front loader bucket is pushed against a rigidly clamped fixture with full engine throttle and maximum hydraulic cylinder pressure of loader. To avoid surprise failures during the test, a virtual simulation method needs to be developed and validated. In this paper, a method has been proposed by authors for the above objective. A multi-body dynamics model of tractor with loader is created in MSC ADAMS and actual event is simulated using test loads & boundary conditions.

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].

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.

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.

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.

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.

Several studies in the field of hedonics using subjective responses to gauge the nature and influence of odors have attempted to explain the complex psychological and chemical processes. Work on the effect of odors in alleviating driver fatigue is limited. The potential to improve road safety through non-pharmacological means such as stimulating odors is the impetus behind this paper. This is especially relevant in developing countries today with burgeoning economies such as India. Longer road trips by commercial transport vehicles with increasingly fatigued drivers and risk of accidents are being fuelled by distant producer - consumer connections. This work describes a two stage comparative study on the effects of different odors typically obtainable in India. The stages involve administration of odorants orthonsally and retronasally after the onset of circadian fatigue in test subjects. This is followed by a small cognitive exercise to evaluate hand-eye coordination.

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.