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.

The focus on driver and occupant safety as well as comfort is increasing rapidly while designing commercial vehicles in India. Improvements in the road network have enhanced road transport for commercial vehicles. Apart from the cost of operation and fuel economy, the commercial vehicles must deliver goods within stipulated time. These factors resulted in higher speed of operation for commercial vehicles. The design should not compromise the safety of the vehicle at these higher speeds of operation. The vehicle should obey the driver’s intended direction at all speeds and the response of the vehicle to driver input must be predictable without much larger surprises which can lead to accidents. The commercial vehicles are designed with rigid axle and RCB type steering system. This suspension and steering design combination introduce steering errors when vehicle travel over bump, braked and while cornering.

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.

As we all know, automotive headliners are an essential component of any car’s interior as they cover all the internal components and provide a clean and finished look. Headliners not only increase the aesthetic appeal of a car’s interior, but also acts as an insulation and sound absorption source. As per the latest Government norms, Curtain Airbag (henceforth called as CAB) has been made mandatory and this change calls for the corresponding changes in the Headliner packaging of all passenger vehicles. In general, curtain air-bag deployment calls for a twist open of Headliner at lateral sides (a portion below Hinge-line) during the deployment. This enables the inflated airbag to flow inside the passenger cabin to protect the passenger from any injury. Conventionally no components are packaged below the hinge-line area of headliner to avoid obstruction for CAB deployment and any part fly-off concerns.

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.

In automotive manual transmission gearboxes, the synchronizer rings play a vital role in gear shift operations. The efficiency of the synchronizer ring depends upon the frictional surface geometry. The critical parameter is the synchronizer ring frictional surface circularity. The circularity deviation causes higher synchronizer ring wear and poor cone torque generation. With the current manufacturing methods and the thickness of the synchronizer ring, circularity improvement is a challenge. The synchronizer ring thread turned part is lapped to improve the circularity. Reduction in circularity can be improved by optimizing the lapping operation. In this work, an optimal lapping condition was developed using statistical methods. Taguchi DOE was used to analyze the different parameter combinations along with the noise parameter – different ranges of circularity variation in turning operation. This helps to find the best lapping parameter settings to improve the reduction in circularity.

Gears are one of the vital components to transmit torque efficiently. Helical gears are chosen as they transmit higher torque with lesser noise compared to spur gears of same size. All new age gearboxes require to transmit maximum torque with minimum packaging space available to improve torque density. Ways of reducing weight are using lesser density material, decreasing centre distance, and thereby reducing pitch circle diameter of all gears, etc. However, they will also affect torque carrying capacity of gearbox which can lead to gear failure in conventional transmission architecture gearboxes with input reduction method. In input reduction method, torque gets multiplied from input shaft to countershaft. Countershaft torque is multiplied to output shaft gears requiring higher torque capacity gears on output shaft. In this research, output shaft reduction architecture is proposed to avoid torque multiplication from input shaft to countershaft gears.

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 bolted joints in suspension systems are subjected to severe external service loads during vehicle operation. To prevent the loaded joint from loosening and allowing it to retain its potential energy stored during assembly, a holistic design approach is needed. This paper explains the methodology to design and optimize bolted joints for the suspension systems of a modern 7-seater sports utility vehicle.

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 order to sustain in automobile industry, fuel economy and robustness are playing vital role in vehicle. Every gram of weight will have an impact on fuel economy, thus burning a hole in consumers pocket and contributing heavily to the carbon footprint. Composite material development plays important role in meeting the stringent self-imposed targets of the automotive manufacturers and light weighting is becoming a prime option for improving Fuel Economy. The main objective of this paper is to optimize the weight of the luggage lid floor and reduce its cost without compromising on the strength by changing the raw material and manufacturing process. This part is in trunk compartment of the vehicle. Main function of this part is to withstand the luggage load under various user loading patterns at varied temperature and while driving on different road conditions.

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).

The tractor usage is growing in the world due to derivative of rural economy and farming process. It needed wide range of implements based on the applications of the customer. The tractor plays a major role in Agricultural and Construction applications. In a tractor, hydraulic system is act as a heart of the vehicle which controls the draft and position of the implement. Hydraulic system consists of Powertrain assembly, 3-point linkage and DC sensing assembly. The design of hydraulic powertrain assembly is challenging because the loads acting on the system varies based on the type of implement, type of crop, stage of farming and soil conditions etc., Hydraulic powertrain assembly is designed based on standards like IS 12207-2019 which regulates the test methods for the system based on the lift capacity of the tractor. In this paper, virtual simulation has been established to optimize the design and perform the test correlation.

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.

Suspension plays a crucial role in stabilizing, comfort and performance of a vehicle. During vehicle braking operation, load transfer happens from rear axle to front axle resulting in shifting of vehicle’s center of gravity towards vehicle front for a momentarily duration which is called diving. This phenomenon leads to dropping of traction at rear wheel end resulting in lifting of rear axle with front wheel as pivot. This causes increase in front to rear weight ratio of vehicle system and compromising driver safety due to skidding and locking of rear wheel-end. To minimize this phenomenon’s affect, optimum anti-dive suspension geometry is used to have better rear wheel end traction resulting in improved braking stability.