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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.

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.

Major focus was given on the Comfort, Fuel efficiency & Safety during the development of the passenger cars, which certainly drives the vehicle business of Original Equipment Manufacturer (OEM’s). The air Conditioning in a car, plays an important role in the area of comfort of the passengers and fuel efficiency point of view. Especially Heat Exchanger plays a pivotal role in the air conditioning system. So, it’s a challenge for the OEM’s to select and design the optimal heat exchanger from the supplier, which meets the performance and packaging requirements during the design phase of the product development cycle. The objective of this paper to focus on analytical calculation or framework was developed using an excel tool considering the effect of variable geometry of fin which includes louver pitch, louver angle and louver length in a multi-pass condenser. Further, this theoretical calculation was validated using experimental data and CFD simulation.

In today’s automobile industry where BS6 emission is posing a high challenge for aggregate development, cost control and with limited timeline. The main target is to provide the cooling system to have less impact on the in terms of cost, weight and to meet the challenging engineering requirement. Thus, the frugal engineering comes into the picture. This paper shows the application of thermosyphon principle for UDM injector cooling thereby reducing the rotation parts and power consumption such as an electric pump. Thermosyphon is a method of passive heat exchange and is based on natural convection, which circulates a fluid without the necessity of a mechanical or electric pump. The natural convection of the liquid commences when heat transfer to the liquid gives rise to a temperature difference from one side of the loop to the other.

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.

Till recently supercharging was the most accepted technique for boost solution in gasoline engines. Recent advents in turbochargers introduced turbocharging technology into gasoline engines. Turbocharging of gasoline engines has helped in powertrains with higher power density and less overall weight. Along with the advantages in performance, new challenges arise, both in terms of thermal management as well as overall acoustic performance of powertrains. The study focuses mainly on NVH aspects of turbocharging of gasoline engines. Compressor surge is a most common phenomenon in turbochargers. As the operating point on the compressor map moves closer to the surge line, the compressor starts to generate noise. The amplitude and frequency of the noise depends on the proximity of the operating point to the surge line. The severity of noise can be reduced by selecting a turbocharger with enough compressor surge margin.

The cylinder block for the power train has always been a classic example of concurrent engineering in which disciplines like NVH, Durability, thermal management and lubrication system layout contribute interactively for concept design. Since the concept design is based on engineering judgment and is an estimated design, the design iterations for optimization are inevitable. This paper aims at outlining a systematic approach for design of crankcase for fatigue which would eliminate design iterations for durability. This allows a larger scope for design improvement at the concept stage as the design specifications are not matured at this stage. A process of stress optimization is adopted which gives accurate dimensional input to design. The approach is illustrated with a case study where an existing crankcase was optimized for fatigue and significant weight reduction was achieved.

Twist beam is a type of suspension system that is based on an H or C shaped member typically used as a rear suspension system in small and medium sized cars. The front of the H member is connected to the body through rubber bushings and the rear portion carries the stub axle assembly. Suspension systems are usually subjected to multi-axial loads in service viz. vertical, longitudinal and lateral in the descending order of magnitude. Lab tests primarily include the roll durability of the twist beam wherein both the trailing arms are in out of phase and a lateral load test. Other tests involve testing the twist beam at the vehicle level either in multi-channel road simulators or driving the vehicle on the test tracks. This is highly time consuming and requires a full vehicle and longer product development time. Limited information is available in the fatigue life comparison of multi-axial loading vs pure roll or lateral load tests.

Batteries have become increasingly important in automotives with increase in vehicle electrical loads. Therefore the reliability of battery is a critical issue in automotive applications. It has been noticed that most batteries have limited cycle durability, that is, the total capacity drops when a battery is charged and discharged for a number of cycles. If a battery is too weak to offer sufficient energy, it should be replaced at the right time. But current problem is that there is no reliable method to quantify the capacity loss and to estimate the remaining capacity of battery. Complete discharge, which is the only way of capacity estimation, which will effect the battery plates therefore it cannot be used too frequently. This paper summarizes the experimental work in the development of the battery status estimation algorithm.

This paper discusses design and optimization process for the integration of exhaust manifold with turbocharger for a 3 cylinder diesel engine, simulation activities (CAE and CFD), and validation of manifold while upgrading to meet current BS6 emissions. Exhaust after-treatment system needs to be upgraded from a simple DOC (Diesel Oxidation Catalyst) to a complex DOC+sDPF (Selective catalytic reduction coated on Diesel Particulate Filter) to meet the BS6 emission norms for this engine. To avoid thermal losses and achieve a faster light-off temperature in the catalyst, the exhaust after-treatment (EATS) system needs to be placed close to the engine - exactly at the outlet of the turbocharger. This has given to challenges in packaging the EATS. The turbocharger in case of BS4 is placed near the 2nd cylinder of the engine, but this position will not allow placing the BS6 EATS.

Model based calibration is extensively used by the automotive OEMs (Original Equipment manufacturers) because of its correlation accuracy with test data and freezing the operating parameters such as injection timings, EGR rates, fuel quantity etc. The prediction of Brake specific Fuel consumption (BSFC), Exhaust and intake temperatures are very close to test data. The prediction of Brake specific NOx is directionally reliable with acceptable tolerance.

Modern day automotive market demands shorter time to market. Traditional product development involves design, virtual simulation, testing and launch. Considerable amount of time being spent on virtual validation phase of product development cycle can be saved by implementing machine learning based predictive models for key performance predictions instead of traditional CAE. Durability oil canning loadcase for vehicle hood which impacts outer styling and involves time consuming CAE workflow takes around 11 days to complete analysis at all locations. Historical oil canning CAE results can be used to build ML model and predict key oil canning performances. This enables faster decision making and first-time right design. In this paper, prediction of buckling behaviour and maximum displacement of vehicle hood using ML based predictive model are presented. Key results from past CAE analysis are used for training and validating the predictive model.

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.

Piston is a critical component of the engine as it exposed to high inertial and thermal loads. With the advent of high performance engines, the requirement of the piston to perform in extreme conditions have become quintessential. Piston scuffing is a common engine problem where there is a significant material loss at the piston and the liner, which could drastically affect the performance and the longevity of the components. This detrimental phenomenon would occur if the piston is not properly designed taking into consideration the thermal and structural intricacies of the engine. A water-cooled gasoline engine which had significant wear pattern on its piston skirt and liner was considered for this study. The engine block was made of aluminum alloy with a cast iron sleeve acting as liner. The piston-liner system was simulated through a commercially available numerical code which could capture the piston's primary and secondary motion.

Development of Hybrid Electric Vehicles (HEVs) and Battery Electric Vehicles (BEVs) is gaining traction across all geographies to help meet increasing fuel economy regulations and as a pathway to offset concerns due to climate change. But HEVs and EVs have so far been a nascent market for India. These technologies have primarily shifted towards Lithium-ion batteries (LIB) for energy storage due to its high energy and power densities. In order to make actual business sense of these technologies, of which, battery is a major cost driver, it is necessary for these batteries to provide similar performance and life expectancy across the operating boundary of the vehicles, as well as provide the requirements at a competitive cost. In other words, the LIBs have to sustain the normal life cycle requirements and withstand wide range of storage temperatures that the conventional gasoline/diesel vehicles have been good at and still ensure good life.

The Indian automotive industry has migrated from BS IV (Bharat stage IV) to BS VI (Bharat Stage VI) emission norms from 1st April 2020. This two-step migration of the emission regulations from BS IV to BS VI demands significant engineering efforts to design and integrate highly complex exhaust after-treatment system (EATS). In the present work, the methodology used to evaluate the EATS of a high power-density 1.5-liter diesel engine is discussed in detail. The EATS assembly of the engine consists of a diesel oxidation catalyst (DOC), a diesel particulate filter with selective catalytic reduction coating (sDPF), urea dosing module and urea mixer. Typically, all these components that are needed for emission control are integrated into a single canning of shell thickness ~1.5mm. Moreover, the complete EATS is directly mounted onto the engine with suitable mounting brackets on the cylinder block and cylinder head.

Electric Vehicle is the need of an hour, as due to excessive usage of IC Engine vehicles has resulted in the depletion of the ozone layer to a significant level and fuel cost is increasing. With new technologies coming into the market, challenges come hand in hand because of Electric Vehicle. In comparison to IC Vehicle, areas of thermal management or the number of components for which thermal management needs to be done is higher and rather complex. As the thermal management system is the second highest energy consuming source after the powertrain of the electric vehicle, an efficient and reliable design is mandatory to ensure better range in an Electric Vehicle. Thermal Management of the Electric Vehicle has been identified as one of the critical parameters for balancing both cabin comfort as well as Battery temperature. One of the major concerns is meeting the Cabin comfort during colder weather with minimum energy consumption.

Range anxiety is one of the major factors to be dealt with for increasing penetration of EVs in current Automotive market. The major reasons for range anxiety for customers are sparse charging infrastructure availability, limited range of Electric vehicles and range uncertainty due to diverse real-world usage conditions. The uncertainty in real world range can be reduced by increasing the correlation between the testing condition during vehicle development and real-world customer usage condition. This paper illustrates a more accurate test methodology development to derive the real-world range in electric vehicles with experimental validation and system level analysis. A test matrix is developed considering several variables influencing vehicle range like different routes, drive modes, Regeneration levels, customer drive behavior, time of drive, locations, ambient conditions etc.

New trend in steering system such as EPS is coming up, but still hydraulic power steering system is more prevalent in today’s vehicles. Power steering pump is a vital component of hydraulic power steering system. Failure of steering pump can lead to loss of power assistance. Prediction of hub load on pump shaft is an important design input for pump manufacturer. Higher hub loads than the actual designed load of pump bearing may lead to seizure of pump. Pump manufacturer has safe limits for hub load. Simulations can assist for optimization of belt layout and placement of accessories to reduce the hub load. Lower hub load can have direct effect on improvement of pump durability. This paper deals with dynamic simulation of belt drive system in MSC.ADAMS as well as vehicle level measurement of hub load on power steering pump.