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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.

During the vehicle launch (i.e. moving the vehicle from “0” speed), the clutch would be slowly engaged by the Driver or Transmission Control Unit (in Automatic Transmission/Automatic Manual Transmission vehicle) for smooth torque transfer between engine and transmission. The clutch is designed to transfer max engine torque with min heat generation. During the clutch engagement, the difference in flywheel and gearbox input shaft speed is called the clutch slipping phase which then leads to a huge amount of energy being dissipated in terms heat due to friction. As a result, clutch surface temperature increases consistently, when the surface temperature crosses the threshold limit, the clutch wears out quickly or burns spontaneously. Hence it is crucial to predict the energy dissipation and temperature variation in various components of clutch assembly through virtual simulation.

To comply with the stringent future emission mandates of light-duty diesel engines, it is essential to deploy a suitable combination of emission control devices like diesel oxidation catalyst (DOC), diesel particulate filter (DPF) and DeNOx converter (LNT or SCR). Arriving at optimum size and layout of these emission control devices for a particular engine through experiments is both time and cost-intensive. Thus, it becomes important to develop suitable well-tuned simulation models that can be helpful to optimize individual emission control devices as well as arrive at an optimal layout for achieving higher conversion efficiency at a minimal cost. Towards this objective, the present work intends to develop a one-dimensional Exhaust After Treatment Devices (EATD) model using a commercial code. The model parameters are fine-tuned based on experimental data. The EATD model is then validated with experiment data that are not used for tuning the model.

Turbocharging of diesel engines have undergone various phases of technological advancements proving merits with engine performance. Since VGTs are finding their applications in many automotive engines, it is also crucial on finding out ways to extract maximum benefits from the system. Pneumatic actuated VGTs control the vanes positioning with the help of mechanical linkages and don’t prove good in transient response with relatively slower boost build up. The electronic controlled VGT operates with the aid of DC motor which is linked to the engine management system. The position sensor senses the current position of the actuator which is controlled by the engine management system for delivering the desired boost pressure. The eVGT system thus provides very quick response and accurate control of boost pressure in all the vehicle driving conditions.

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.

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.

With the advancement in vehicle technology over the years, many intuitive technologies are coming in automotive passenger vehicles to improve the safety aspects during vehicle driving in night conditions. In addition to headlamps, cornering lamps or infrared camera with head up display etc. are evolving as a part of AFS (Advanced Front Lighting Systems) to aid driver vision. Many OEMs are following conventional methodology of subjective assessments with the ratings on different numerical scale mapped with customer acceptance to validate head lamps and its tech updates. These methods lag in getting repeatability of results, acceptance reliability and not knowing the limitations of the installed system due to high dependency on the selected evaluators. This paper emphasizes on robust test methodology development to validate the complete performance of cornering lamps with the objective test data analysis.

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.

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.