Search Results

In recent years, the push for reduced product development timelines has been more than ever with significant changes in the automotive market. High electrification, intelligent vehicle systems and increased number for car manufacturers are a few key drivers to the same. The front loading of development activities is now a key focus area for achieving faster product development. From vehicle dynamics point of view availability of subjective evaluation feedback plays a key role in optimization various system specifications. This paper discusses an approach for front loading through parallel development of the tire and vehicle chassis system, using advanced simulation and driving simulator technology. The proposed methodology uses virtual tire models which in combination with real-time vehicle model enables subjective evaluation of vehicle performance in driver-in-loop simulators.

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.

The increasing demand for higher specific power, fuel economy, Operating Costs as well as meeting global emission norms have become the driving factors of today’s product development in the automotive market. Substitution of high-density materials and more precise adjustment of material parameters help in significant weight decrease, but it is accompanied by undesirable cost increase and manufacturing complexity. This becomes a challenge for every automotive engineer to balance the above parameters to make a highly competitive design. This work is a part of the Design and Development of 2.2 L, 4 Cylinder TCIC Diesel Engine for a whole new vehicle platform, concentrated on automotive passenger car operation. This paper explains the selection of a suitable cylinder head gasket technology for a lightweight engine that acts as a sealing interface between the cylinder block and cylinder head.

As customers are inching towards adoption of electric vehicles as an alternative to internal combustion engines, automotive OEM’s will have to embrace this change and equip with new product development process. When it comes to Electric Vehicle (EV) in comparison with Internal Combustion Engine (ICE), NVH plays a major differentiator for vehicle refinement. Squeak and rattles will account for 20-25% of overall in-cabin noise source in an electric vehicle, most of which is observed from interior trims. Trims are mounted using small plastic clips which function as attachments and play a significant role in part retention and part integrity during normal operation and in case of any transient events. The engineering specifications for selecting a clip is force in newtons and it is mostly driven by ease of assembly, serviceability, and durability. A single DOF system with a specimen mass is developed and stiffness and damping are calculated based on transmissibility.

In developing countries, manual transmissions are leading the market due to their efficiency and low cost. In a manual transmission, the synchronizers play a vital role in defining the gear shift quality. Manual transmission vehicles are getting refined for a pleasant driving experience. The gear shift quality is one of the unique selling points for the vehicle, so the automakers are focusing on the reduction of the gear shift forces. In a manual transmission, the synchronizers are used to match the speed difference between the upstream and downstream inertia for the gear-shifting process. The synchronizers have conical friction surfaces to generate friction and cone torque. The increase in cone torque reduces the gear shift impulse. The cone torque can be increased with mismatch tolerance in the frictional surfaces. In this technique, two cone angles are used for the frictional surfaces.

Internal combustion engine vehicles are major contributors to many environmental and health hazardous emissions and sometimes consume more fuel. New regulations like Corporate Average Fuel Efficiency (CAFÉ) norms are coming up and demand lower emissions. Original Equipment Manufacturers (OEMs) are committed to bringing various technological advancements in Internal Combustion Engine (ICE)powered vehicles to maximize their efficiency. Hence it is important to reduce the loss and improve the fuel economy. This paper explains a new approach methodology used for reducing the gearbox drag by 5- 10 %. This improvement can significantly contribute to the overall efficiency improvement thus carbon footprints of vehicle getting reduced.

Highly competitive automotive market demands shorter product development cycle while maintaining higher standards of performance in terms of durability and Noise Vibration & Harness (NVH). Engine cranktrain system is one of the major vibration sources in engine and first torsional mode frequency is a key parameter which influences vibration characteristics. Current CAE (Computer Aided Engineering) workflow for evaluating cranktrain system performance is time-consuming and takes around 55 Hrs. It involves crankshaft geometry cleanup, stiffness calculation, 1D model building and post processing. Over the time, significant historical data has been created while performing this virtual simulation during the product development cycle. Having a trained Machine Learning (ML) model based on this historical data, which can predict first torsional mode frequency accelerates the virtual validation. In this paper, prediction of first torsional frequency of cranktrain system using ML is presented.

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.

For decades, customer complaints on Squeak & Rattle issues have come as a question of quality for the automotive industry. Squeak and rattle sounds are customer irritants due to their non-patterned and transient nature. Squeak is a friction induced noise that generally occurs because of rubbing of the two materials that are incompatible with each other. While rattle is a phenomenon that occurs due to the impact between the two parts having unintended gap. They are no more secondary noises and avoiding or elimination of these become significant for brand building and warranty cost reduction. Chucking is a form of squeak noise that occurs due to the interaction between uncoated seal to seal. In Swing gate, this phenomenon is seen when seal bulb inner layers are completely compressed. Swing gate have fore-aft modes that are excited due to dynamic responses from different road profiles.

The passenger car segment has been extremely competitive and automotive OEMs are thriving to provide superior customer experience. Door closing is an event that requires slamming of the door with a certain velocity to get the door latched. A good latching provides that thud sound and assurance of the door getting closed for an SUV. While the door is closed, it pushes the volume of air inside the cabin. As the amount of air moved in is proportionate to the size of the door it becomes more critical for the SUV segment of vehicles to ensure the air extraction path is efficient. Else, steep pressure rise inside the cabin causes severe discomfort to the passengers sitting inside the vehicle. Current work focused on the process of simulation of cabin pressure while door closing, implementing changes based on results and validating with test results. Test results are in close correlation with simulation predictions.

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.

PVC (polyvinylchloride) synthetic leather or called leatherette is being widely used for automotive interior applications for seat cover, gear boot, gap hider, steering wheel and roof liner due to their leather like feel and texture, flexibility, sewability, affordability, and wide design freedom. However, the leatherette construction such as top coating, backing fabric and fabric weaving pattern plays a critical role in the finished leatherette performance for the specific application. This study provides the influence of different coating material and different backing fabric in squeak behavior of gear boot PVC leatherette. The squeak behavior was studied by stick slip test as per automotive engineering requirements, and the response of these coating and fabric surface was measured in the form of Risk Priority Number (RPN).

Vehicle pull during braking can be defined as the deviation of vehicle travel from intended path of the vehicle by a margin of half a wheel track or more. It is a dynamic phenomenon with very complex inter-dependencies among the combined functioning of various aggregates such as steering system, suspension system, axles, and brakes. The problem is aggravated with shorter wheelbase & higher CG (Centre of Gravity) height, where the instantaneous load transfers are sudden and of relatively high magnitude which can lead to a combination of forces that are responsible for vehicle drifting or pulling to anyone side of centre-line travel. Vehicle with shorter wheelbases, high GVW and high CG heights are more prone to this unstable behaviour due to sudden change in dynamic forces acting on the tires while turning and braking.

In the automotive industry the requirement for low emissions has led to the demand for lightweight vehicle structures. Light weighting can be achieved through different iterative approaches but is usually time consuming. Current paper highlights deployment of the multi-loadcase optimization approach for light weighting. This work involves developing a process for multiple loadcase optimization for automotive hood. The main goal is to minimize the weight of a hood assembly by meeting strength and stiffness targets. The design variables considered in this study are thickness of the panels. Design constraints were set for stress and stiffness based on DVP (Design Verification Plan) requirement. Optimization workflow is setup in mode-frontier with design objective of minimizing weight of hood.

Light weighting is an effective strategy in increasing energy efficiency in the automotive industry. In this paper, mass reduction with cost benefit was targeted in an exterior trim panel. Polypropylene copolymer (PPCP) compound was developed for a large exterior trim panel (1400 X 700mm) having an integrated grill mesh. The part had challenging requirements in terms of slow speed impact, structural durability, dimensional stability, aesthetics, thermal ageing resistance, cold impact resistance, scratch resistance and weathering resistance. By having ultra-high flow behavior, optimum tensile strength, modulus, impact strength and thermal properties, the PPCP compound met the requirements for a thin wall exterior trim panel with a thickness of 2.6mm. Structural durability of the design was validated by virtual engineering. Part design and material combinations with better tooling design iterations were analyzed by using mold flow analysis.

In automotive product development, design and development of the chassis plays an important role since all the internal and external loads pass through the vehicle chassis. Durability, NVH, Dynamics as well as overall vehicle performance is dependent on the chassis structure. Even though passenger vehicle chassis has a ladder frame or a monocoque construction, small commercial vehicle chassis is a hybrid chassis with the cabin welded to the ladder frame. As mileage is critical for sale of SCVs, making a light-weight chassis is also important. This creates a trade-off between the performance and weight which needs to be optimized. In this study, a parametric beam model of the ladder frame & the cabin of the vehicle is created in COMSOL Multiphysics. The structure has been parameterized into the long member & crossmember geometry & sections. The model calculates the first 12 natural frequencies, global stiffness, and weight.

The SAE J1100 based standard cargo volume index methods and predefined luggage objects are very specific to United States population. The European luggage volume calculation and standard luggage calculations are primarily based on DIN and ISO standards. Luggage volume declaration by manufacturers are based on any of these methods. The calculations are complicated and there is a possibility of declaring different values for similar luggage compartments. The major purchase decision of vehicle is based on its luggage capacity and current methods are very limited to make an intelligent decision by a customer. Market specific customer usage patterns for luggage requirements and protecting them in vehicle architecture upfront in concept stage is important to retain the market position and buying preference of customers. The usage patterns is collected from customer clinics and marketing inputs.

There is a higher demand for quieter tractors in the agri-industry, as the continued exposure to noise levels have disastrous effects on operator’s health. To meet the world-wide regulatory norms and to be the global market leader, its mandatory to develop the comfortable tractor which meets homologation requirements and customer expectations. Typically, Operator Ear Level (OEL) noise has been evaluated in the test, after First Proto has been made. This approach increases cost associated with product development due to late changes of modifications and testing trails causing delay in time-to-market aspect. Hence, there is a need to develop the methodology for Predicting tractor OEL noise in virtual environment and propose changes at early stage of product development. At first, full vehicle comprising of skid, sheet metals and Intake-exhaust systems modelled has been built using Finite Element (FE) Preprocessor.

The automobile industry strives to develop high-quality vehicles quickly that fulfill the buyer’s needs and stand out within the competition. Full utilization of simulation and Computer-Aided Engineering (CAE) tools can empower quick assessment of different vehicle concepts and setups without building physical models. Vehicle execution assessment is critical in the vehicle development process, requiring exact vehicle steering system models. The effect of steering system stiffness is vital for vehicle handling, stability, and steering performance studies. The overall steering stiffness is usually not modeled accurately. Usually, torsion bar stiffness alone is considered in the modeling. The modeling of overall steering stiffness along with torsion bar stiffness is studied in this paper. Another major contributing factor to steering performance is steering friction. The steering friction is also often not considered properly.

The given paper presents the main elements of frictional power loss distribution in an automotive axle for passenger car. For reference two different axles were compared of two different sizes to understand the impact of size and ratio of gear and bearings on power loss characteristics. It was observed that ~50% of total axle power loss is because of pinion head-tail bearing and its seals, which is very significant. Roughly 30% of total power loss is contributed by pinion-ring gear pair and differential bearings and remaining ~20% by wheel end bearing and seals. With this study the automotive companies can take note of the area where they need to focus more to reduce their CO2 emissions to meet the stringent BS6, CAFÉ and RDE emission norms.