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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.

In farm tractors, the available drawbar power, and Power Take-Off (PTO) power are generally lower than the engine power due to parasitic losses. These losses are caused by engine-driven auxiliary loads such as cooling fans, hydraulic pumps for power steering, alternators, etc. Minimizing these parasitic losses can increase the available drawbar power and PTO power, resulting in direct fuel savings by reducing fuel consumption. The continuous increase in fuel costs and the environmental impact of emitted gases from burned fuel into the atmosphere have necessitated the replacement of hydraulic power steering and mechanical fans with Electric Power Steering (EPS) and electric fans, respectively, to improve efficiency. The existing battery has been replaced with a higher capacity battery to provide power to the electric fan, electric power steering, and other electrical components.

The BS6 norms (phase 1) were implemented in India from April 1, 2020 and replaced the previous BS4 norms. Phase 2 of the BS6 norms, which came into effect on April 1, 2023. In accordance with the regulation requirement, effective performance of after treatment systems like DPF and SCR demands critical hardware implementation and robust monitoring strategies in the extended operating zone. Effective OBD monitoring of DPF, which is common to all BSVI certified vehicles, such that the defined strategy detects the presence or absence of the component is imperative. A robust monitoring strategy is developed to detect the presence of the DPF in the real world incorporating the worst possible driving conditions including idling, and irrespective of other environmental factors subject to a location or terrain. The differential pressure sensor across the DPF is used to study the actual pressure drop across the DPF.

The automobile industry is going through one of the most challenging times, with increased competition in the market which is enforcing competitive prices of the products along with meeting the stringent emission norms. One such requirement for BS6 phase 2 emission norms is monitoring for partial failure of the component if the tailpipe emissions are higher than the OBD limits. Recently PM (soot) sensor is employed for partial failure monitoring of DPF in diesel passenger cars.. PM sensor detects soot leakage in case of DPF substrate failure. There is a cost factor along with extensive calibration efforts which are needed to ensure sensor works flawlessly. This paper deals with the development of an algorithm with which robust detection of DPF substrate failure is achieved without addition of any sensor in the aftertreatment system.

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.

Restraint systems in automotives are inevitable for the safety of passengers. Seat belts are one such restraint system in automotives that prevent drivers and passengers from being injured during a crash by restraining them back. Seatbelt on automotives has interface with Body-in-white (henceforth called as BIW) and Trim parts in-order to serve its purpose at vehicle level. One such interface part of seat belt is the web guide, which assists and ensures the nylon web’s smooth motion at different seat track positions. Web-guides on automotives ensure the flawless motion of seat belt web at pillar trim areas. In this paper, we are discussing alternate ways of assisting the seat belt web without the web-guide as a separate part. In-order to assist and ensure the motion of nylon web in its trajectory, we have extended the flange of the pillar trim involved.

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.

Manual transmission (MT) is still the most preferred solution for emerging markets due to the lower cost of ownership and maintenance coupled with a higher transmission efficiency. In this regard, continuous improvement of the transmission shift quality is quite essential to meet the growing customer expectations. In the present work, a detailed evaluation of the gear-shift impulse (experienced at the gear-shift knob) is conducted between two different architectures of a manual, high-torque (450 Nm input torque) inline transmission meant for a sports utility vehicle (SUV). The conventional manual inline transmission architecture comprises a common gear pair at the input of the transmission. While this input reduction architecture is the most widely used architecture, having the common gear pair at the output of the transmission is also another option. The synchronizers of the manual transmission need to match the speed of the rotating components just before the gear-shifting event.

The brass synchronizers are not resistant to abusive conditions of gearbox operations, but they are very durable and cheap when used on their favorable material property working limit. The main failure which can occur in the gearbox due to the synchronizer is crash noise. During gear shifting the gear crash will create high discomfort for the driver and must apply high force to change the gears. The main factors which contribute to the crash phenomenon are the insufficient coefficient of friction, high drag in the system, and high wear rate of the synchronizer rings before the intended design life of the synchronizer. The brass synchronizers were tested on the SSP-180, ZF synchronizer test rig to know the effect of the synchronizer performance parameters like the coefficient of friction, sleeve force, slipping time as well as durability parameters like wear rate when the operating temperature of the oil is changed.

In most cases, the properties of a metal are evaluated in their as rolled condition, prior to any work hardening or bake hardening. But in the Automotive World, these steels get work hardened during the forming process and bake hardened in the paint shop. The goal of this paper is to evaluate the variations in the performance of Dual Phase (DP) steels and understand the most optimized method of testing and property generation. This method can then be used to extrapolate to real automotive components. Dual Phase Steels or DP Steels contain a mixture of Ferrite & Martensite from which they derive their name. They are a part of the advanced high strength and ultra-high strength steels steel family according to World Auto Steels. The Ferrite phase, with its iron content contributes to the material displaying an increased level of ductility whilst, the martensitic phase provides the steel with increased mechanical strength.

Globally, automotive sector is moving towards improving off-road performance, durability and safety. Need of off-road performance leads to unpredictable overload to powertrain system due to unpaved roads and abuse driving conditions. Generally, shafts and gears in the transmission system are designed to meet infinite life. But, under abuse condition, it undergo overloads in both torsional and bending modes and finally, weak part in the entire system tend to fail first. This paper represents the failure analysis of one such an incident happened in output shaft under abuse test condition. Failure mode was confirmed as torsional overload using Stereo microscope and SEM. Application stress and shear strength of the shaft was calculated and found overstressing was the cause of failure. To avoid recurrence of breakage, improvement options were identified and subjected to static torsional test to quantify the improvement level.

Original Equipment Manufacturers (OEMs) should innovate ways to delight customers by creating affordable products with improved drive experience and occupant comfort. Vehicle refinement is an important initiative that is often take-up by the project teams to ensure that the product meets the customer’s expectations. A few important aspects of vehicle refinement include improving the Noise Vibration Harshness (NVH), ride and handling performance pertaining to the Functional Image (FI) of the product. Optimizing the suspension design variables to meet both ride and handling performance is often challenging as improving the ride will have a deteriorating effect on handling and vice-versa. The present work involves Multi-Objective Design Optimization (MDO) of the suspension system of an automotive Sports Utility Vehicle (SUV) platform considering both ride and handling requirements, simultaneously.

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.

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.

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.

Accurate ride and handling prediction is an important requirement in today's automobile industry. To achieve the same, it is imperative to have a good estimation of damper model. Conventional methods used for modelling complex vehicle components (like bushings and dampers) are often inadequate to represent behaviour over wide frequency ranges and/or different amplitudes. This is difficult in the part of OEMs to model the physics-based model as the damper’s geometry, material and characteristics property is proprietary to part manufacturer. This is also usually difficult to obtain as a typical data acquisition exercise takes lots of time, cost, and effort. This paper aims to address this problem by predicting the damper force accurately at different velocity/ frequency and amplitude of measured data using Artificial Neural Networks (ANN).

The stringent emission regulations demand highly complex after-treatment systems. The packaging and functional requirements of the after-treatment system demand very close coupling of the diesel oxidation catalyst (DOC) with the turbocharger outlet. The sealing effectiveness between the turbocharger and DOC is ensured by the V-band grooved clamp along with the suitable gasket. This V-band grooved clamp is widely used in diesel engines due to its ease of assembly and low cost. Since the V-band grooved clamp is subjected to a very high temperature, vibration, thermal shock, a robust and holistic validation is required to ensure the functional and safety requirements. Despite its wide range of applications, the testing and validation methodologies required to effectively validate the strength and other aspects of the clamp are not fully defined. In the present work, the authors discuss the various design validation methods involved during the development of the V-band grooved clamp.

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.