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The auto industry is one of the major contributors for noise pollution in urban areas. Specifically, highly populated heavy commercial diesel vehicle such as buses, trucks are dominant because of its usage pattern, and capacity. This noise is contributed by various vehicle systems like engine, transmission, exhaust intake, tires etc. When the pass by noise levels exceeds regulatory limit, as per IS 3028, it is important for NVH automotive engineer to identify the sources & their ranking for contribution in pass by noise. The traditional methods of source identification such as windowing technique, sequential swapping of systems and subsystems which are time consuming.Also advanced method in which data acquisition with a synchronizing technology like telemetry or Wi-Fi for source ranking are effective for correctness.However they are time and resource consuming, which can adversely impact product development timeline.

Sound signature design is gaining more importance within global auto manufacturers. ‘Sportiness’ is one of the important point to consider while designing a sound character of a car for passionate drivers and those who love aggressive driving. Nowadays automobile manufacturers are more focused in developing a typical sound signature for their cars as a ‘unique design strategy’ to attract a niche segment of the market and to define their brand image. Exhaust system is one of the major aggregate determining the sound character of ICE vehicles which in turn has the direct influence on the customer perception of the vehicle and the Brand image and also the human comfort both inside and outside the cabin. This research work focuses on novel approaches to identify frequency range and order content by a detailed study of subjective feelings based on psycho-acoustics. Sound samples of various benchmark sporty vehicles have been studied and analyzed based on sound quality parameters.

In the modern and fast growing automotive sector, reliability & durability are two terms of utmost importance along with weight & cost optimization. Therefore it is important to explore new technology which has less weight, low manufacturing cost and better strength. The new technology developed always seek for a quick, cost effective and reliable methodology for its design validation so that any modification can be made by identifying the failures. This paper presents the rig level test methodology to validate and to correlate the CAE derived strain levels, life cycle & failure mode of newly developed light weight stabilizer link for EV Bus suspension

In automotive industry, testing and validation teams are highly dependent on availability of prototype vehicles for testing and evaluation of ride & comfort behavior of vehicles. Special test tracks surfaces are also used (namely Tar road, Express way and driving over a Cleat) to evaluate the ride & comfort through subjective evaluation. Ride is largely affected by transmissibility of road excitations to the driver and other occupant’s seats, influence of suspension, bushes and tire are the major contributors in the transfer path of vibrations. A configurable 1–D simulation model of a Two Axle Truck is developed for quick evaluation of the ride & comfort behavior which is need of the hour for the testing team in optimizing the number of iterations in physical testing. These simulations will help in understanding the ride & comfort behavior and its sensitivity to changes in the component’s characteristics in absence of physical test vehicles.

One of the very first customer touchpoint in a vehicle is quality of gear shifting. Gearshift quality is perceived as a symbol of refinement of a vehicle. Globally, lot of efforts are taken to refine the gearshift quality. Design improvements in internal components of transmission, cable and shifter assembly, knob design iterations are carried out to arrive at optimum gearshift quality at the vehicle level. Current practice for this activity includes processes such as design modification, manufacturing of proto components, assembly of components and fitment in the vehicle. This vehicle is then instrumented with sensors and data acquisition units to capture the parameters which determine the gearshift quality. This is an iterative process which goes on until necessary refinement/improvement is achieved. This process requires investment of lot of time, efforts and the budget. This paper describes a virtual approach to arrive at optimum design of components.

Climate change due to global warming calls for more fuel-efficient technologies. Parallel Full hybrids are one of the promising technologies to curb the climate change by reducing CO2 emissions significantly. Different parallel hybrid electric vehicle (HEV) architectures such as P0, P1, P2, P3 and P4 are adopted based on different parameters like fuel economy, drivability, performance, packaging, comfort and total cost of ownership of the vehicle. It is a great challenge to select right hybrid architecture for different vehicle segments. This paper compares P2 and P3 HEV with AMT transmission to evaluate most optimized architecture based on vehicle segment. Vehicles selected for study are from popular vehicle segments in India with AMT transmission i.e. Entry segment hatch and Compact SUV. HEV P2 and P3 architectures are simulated and studied with different vehicle segments for fuel economy, performance, drivability and TCO.

The art of rubber formulation science always has a scope for fine-tuning with changing the parameters like base polymer grade selection, filler selection, curing system/cross link density, manufacturing methods, and many. Hence forth the filler manufacturer arrived differentiation of the filler already, this paper provides a description of rubber formulation tuning for damped vibration automotive applications. Acicular spiky spherical and hollow spherical nano silica selected as filler. With the thorough knowledge of elastomeric formulation and with doping different new selected silica grades, an optimized DOE was done. New formulation development was focused on isolation characteristics without affecting other necessary properties. The different inputs for finite element calculations was studied with the effects of doping different fillers and also studied the resultant virtual output in damping coefficients.

In developing nations, most passenger vehicles are equipped with mobile air conditioning (MAC) systems that work on Hydro Fluoro Carbons (HFC) based refrigerants. These refrigerants have a high global warming potential (GWP) and hence adversely affect the environment. According to the Kigali amendment to Montreal Protocol, Article-5 Group-2 countries including India must start phasing down HFCs from 2028 and replace them with low Global Warming Potential (GWP) refrigerants. One such class of low GWP refrigerant is Hydro Fluoro Olefins (HFO) In order to replace HFCs with HFOs in existing MAC systems, the various system performance parameters with the new refrigerant are required to be evaluated. Performance evaluation of MAC system is rendered quicker and cost-effective by deploying a digital simulation tool. There is good correlation and confidence established for MAC performance prediction with HFCs through 1D CAE.

The dynamic response of structures to operating or occasional loads is crucial for design considerations, as it directly impacts the cumulative fatigue life. In practice, accurately discerning the precise loads and structural conditions, which involve considerations such as boundary conditions, geometry, and mechanical properties, can be quite challenging. Significant efforts are invested in identifying these factors and developing suitable prediction models. Nonetheless, the estimated forces and boundary conditions remain approximations, leading to uncertainties which affects the overall predictions and the analysis of how stress and strain develop in the structure during subsequent evaluations. Many researchers frequently employ a method where they estimate the forces acting on the system based on measurement data obtained at limited number of locations over the structure.

Advent of EV powertrain has considerable effect on transmission development activities as competed to regular ICE transmission. Conventional ICE transmission and the transmission for an e-powertrain differ on fundamental level. The conventional transmission has number of gear ratios, shift mechanism which enables the transmission to deliver a smooth power output as per demand from the driver. Whereas the e-powertrain transmission is mostly a single gear ratio transmission (reducer) which primarily depends on speed and torque variation from the motor to cater the driver requirement. Hence, the operating speeds of such e-transmissions can vary from 0 to 20000 rpm in both forward and reverse directions. Such a large speed variation as compared with conventional transmission calls for special attention towards the lubrication of internal components. High speeds and lower oil viscosities tend to disrupt the oil films in between contact surfaces causing metal to metal contact.

Sustainability has evolved from being just a niche engagement to a fundamental necessity. The reduction of carbon emissions from aspects of human activity has become desirable for its ability to mitigate the impact of climate change. The Transportation industry is a critical part of the global economy – any effort to curb emissions will have a significant impact on CO2 reduction. Engine lubricant can play an efficient and key role to enhance powertrain performance that have undergone significant hardware changes to reduce emissions. As part of a significant collaborative programme between Tata Motors and Infineum, a new engine oil formulation SAE 5W-30 API FA-4 has been developed and commercially introduced for use in the modern Bharat Stage 6 Phase 2 engines.

Global concerns over availability and environmental impact of conventional fuels in recent years have resulted in evolution of Electric Vehicles. Research and development focus has shifted towards one of its main components, Lithium-ion battery. Development of high performing, long lasting batteries within challenging timelines is the need of the industry. Lithium-ion batteries undergo “battery ageing”, limiting its energy storage and power output, affecting the EV performance, cost & life span. It is critical to be able to predict the rate of battery ageing & the impact of different environmental conditions on battery lifetime/capacity. Conventionally, extensive physical vehicle level testing is carried out on batteries to map the battery capacity in various conditions. This is a lengthy & expensive process affecting the product development cycle, paving the way for an alternative process.

Welding is one of the most convenient and extensively used manufacturing process across every industry and is recognized as a cost effective joining technique. The root cause of most of the fabricated structural failures lies in the uncertainties associated with the welding process. It is prone to generate high residual stresses due to non-volumetric changes during heating and cooling cycle. These residual stresses have a significant impact on fatigue life of component leading to poor quality joints. To alleviate these effects, designers and process engineers rely upon their experience and thumb rules but has its own limitations. This approach often leads to conservative designs and pre-mature failures. Recent advances in computational simulation techniques provide us opportunity to explore the complex phenomenon and generate deep insights. The paper demonstrates the methodology to evaluate the residual stresses due to welding in virtual environment.

This paper highlights the transition of multi-axis suspension test rig from fixed reacted type to semi-inertial type and the benefits derived thereof in simulation accuracies. The critical influence of ‘Mx’ and ‘Mz’ controls on simulation accuracies has been highlighted. The vital role of ‘Mz’ control in the resonance of wheel pan along ‘Z’ axis and thereof arresting unwanted failures modes in spindle has been duly emphasized. Finally, the role of constraints and boundary conditions on simulation accuracies has been demonstrated by replacing the reaction frame with vehicle body.

The basic function of steering system is to control the direction of the vehicle. The driver applies effort on the steering wheel and receives feedback through the steering system as a result of tire to road interaction. This feedback consists of a haptic (force) feedback which is directly felt by the driver and it is termed as steering feel. Precise steering feel gives better driving experience and is decisive factor for customer to buy a vehicle as well as for OEMs in building brand image. Along with steering parameters, suspension and tire parameters also has significant impact on steering feel. In past, modelling of the steering system was done at component level or with simplified vehicle system. Such approaches had not given accurate results of steering feel metric and resulted in incorrect steering design parameter selection. In order to replicate actual vehicle characteristics, complex and detailed modelling of steering, tire and suspension subsystems is necessary.

Automotive OEMs are launching multiple products with ever reducing development time, balancing costs, quality and time to market, with clear focus on performance and weight. Platform architecture concepts, modular designs for differentiation etc. are strategies adopted by automotive OEMs towards shorter development cycles. Thus, concept generation phase of the digital product development process is expected to enable generation and evaluation of multiple concept architectures, carry out performance studies and largely focus on optimization, upfront. This Front loading of engineering and call for simultaneous engineering requires support in terms of quick and good CAD modeling with maturity. This paper proposes a process that focuses on generation and evaluation of multiple concepts, besides enabling optimization of concept before the detailed design phase kicks in.

Engine Stop/Start System (ESS) promises to reduce greenhouse emissions and improve fuel economy of vehicles. Previous work of the Authors was concentrated on bridging the gap of improvement in fuel economy promised by ESS under standard laboratory conditions and actual driving conditions. Findings from the practical studies lead to a conclusion that ESS is not so popular among the customers, due to the complexities of the system operation and poor integration of the system design with the driver behavior. In addition, due to various functional safety requirements, and traffic conditions, actual benefits of ESS are reduced. A modified control algorithm was proposed and proven for the local driving conditions in India. The ways in which a given driver behaves on the controls of the vehicles like Clutch and Brake Pedals, Gear Shift Lever were not uniform across the demography of study and varied significantly.

Authors were challenged with a task of developing a full vehicle simulation model, with a target to simulate the electrical system performance and perform digital tests like Battery Charge Balance, in addition to the fuel efficiency estimation. A vehicle is a complicated problem or domain to model, due to the complexities of subsystems. Even more difficult task is to have a control algorithm which controls the vehicle model with the required control signals to follow the test specification. Particularly, simulating the control of a vehicle with a manual transmission is complicated due to many associated control signals (Throttle, Brake and Clutch) and interruptions like gear changes. In this paper, the development of a full vehicle model aimed at the assessment of electrical system performance of the vehicle is discussed in brief.

Important vehicle performance parameters such as, fuel economy and high speed stability are directly influenced by its aerodynamic drag and lift. Wind tunnel testing to asses these parameters requires heavy investment especially when test wind tunnel is not available in the country where vehicle development center is present. Hence to save cost and to compress development time, it is essential to asses and optimize parameters of a vehicle in very early stages of development. Using numerical flow simulations optimization runs can be carried out digitally. Industry demands prediction of aerodynamic drag and lift coefficients (CD,CL) within an accuracy of a few counts, consuming minimal HPC resources and in a short turnaround time. Different OEMs deploy different testing methods and different softwares for numerical simulations.

Steering pull during high speed braking of heavy commercial vehicles possesses a potential danger to the occupants. Even with negligible wheel-to-wheel brake torque variation, steering pull during the high speed braking has been observed. If the steering pull (i.e. steering rotation) is forcibly held at zero degree during high speed braking, the phenomena called axle twist, wheel turn and shock absorber deflection arise. In this work the data have been collected on the mentioned measures with an intention to develop a mathematical model which uses real time data, coming from feedback mechanism to predict the values of the measures in coming moments in order to aid steering system to ‘auto-correct’. Driven by the intention, ‘Time Series Analysis’, a well-known statistical methodology, has been explored to see how suitable it is in building the kind of model.