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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.

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.

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.

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.

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.

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.

In the event of a frontal car crash, occupant sitting in a car meets various types of injuries like Head injury, Chest compression, Neck injury etc. These injuries may lead to the death of an occupant if exceeded beyond biomechanical limits. Seat belt is a primary restraint system, which when worn controls the motion of occupant sitting inside the car during the event of a car crash. An Anchorage location of three point seat belt system has significant effect on occupant injuries during the crash event. By changing the mount locations of a seat belt anchor points i.e. D-ring, Anchor & Buckle, performance of seatbelt system can be enhanced further thereby reducing occupant injuries to certain extent. As per regulation AIS015, locations of safety belt anchorage points should be within prescribed zone.

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.

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.

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.

With continuous pressure for reducing vehicle development time and cost, without compromising on system reliability, it is imperative to move from Road to Lab to Model (RLM) based development. Every OEM is currently using virtual environment to complete functional checks of systems during development. The method of developing control functions and calibration in virtual environment brings repeatability and reproducibility which typically is challenging in real world testing. This process is cost effective and optimizes the time for development and brings high level of system maturity before testing it in the vehicle. This paper focuses on defining a front-loading approach for setting up of virtual test environment. Development of virtual test environment and its validation with respect to real vehicle data will be discussed, with focus on vehicle plant model and driver model.

OEMs these days are focusing on front loading the activities to Virtual Test Environment (VTE) based development owing to high development cost and complexity in achieving repeatability during testing phase of vehicle development,. This process not only helps in reducing the cost and time but also helps in increasing the maturity and confidence level of the developed system before actual prototype is built. In the past, extensive research has happened for increasing the fidelity of VTE by improving plant model efficacy which involves powertrain and other vehicle systems. On the other hand, improving the precision of driver model which is one of the most complex nonlinear systems of virtual environment still remains a challenge. It is apparent that various drivers show different behavior in real world for a given drive profile. While modelling a driver for a VTE, the real world driver attributes are seldom considered.

Achieving higher emission norms involves various techniques and it has always been a challenging task on meeting the same. Improving the exhaust temperature is indispensable in order to enhance better conversion efficiency on the after-treatment systems. This paper clearly investigates on the various strategies involved to improve the exhaust temperatures of selective catalytic reduction and post injection strategies to meet the emission norms. On the basis of MIDC operation, key load points were selected and split injections with three pulses were implemented. The variation of both the post injection timing and quantity were performed in this paper in order to evaluate the optimum output. The effect of post injection timing and quantity variation on hydrocarbon emissions, carbon monoxide, diesel oxidation catalyst temperatures was observed on all load points. The above strategy was also evaluated on generating the pressure crank angle data.

Reducing material wherever there is a possibility in automobile industry is inevitable for weight and cost saving. This paper explains about the possibilities of optimizing the material composition of automotive Headliners (also called as Roof liners) without affecting the performance and safety criteria. In this paper, we are targeting at optimizing the individual constituents of a composite Headliner. A conventional Headliner comprises of many sandwich layers of which PU foam shares the major percentage of the composition contributing to 80% of the Headliner thickness. In this paper, we are discussing about the optimization done in Headliner sandwich constituents without affecting the core performance parameters of headliner such as curtain airbag deployment, ergonomic regulations, drop test etc. By incorporating this change, without significant changes in other layers, overall weight reduction of ~24% and overall cost reduction of ~24% is achieved.

Ride is an important attribute which must be accounted in the passenger segment vehicles. Excessive H point acceleration, Steering wheel acceleration, Pitch acceleration can reduce the comfort of the driver and the passengers during high frequency and low frequency rough road events. Excessive Understeer gradient, roll gradient, roll acceleration and Sprung mass lift could affect the Vehicle driver interaction during Steady state cornering, Braking and Step steer events. The concept architecture of the vehicle plays an important role in how comfort the vehicle will be. This paper discusses how to improve SUV ride performances by keeping handling performance attributes same or better than base vehicle. Multi Objective Optimization was carried out by keeping spring, bushing and damper characteristic as the design variables to avoid new system or component development time and cost.