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With the rise of worldwide trends towards light weighting and the move towards electric vehicles, it is now more important than ever for the automotive industry to develop and implement lightweight materials that will result in significant weight reduction and product improvements. A great deal of research has been done on how to best combine and configure honeycomb cores with the right face sheets for Truck-Mounted Container Applications. Honeycomb structures possess the ability to bring about superior structural rigidity when the core parameters are selected and optimized based on the automotive application requirements.

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.

Customer preference towards quieter vehicles is ever-increasing. Exhaust tailpipe noise is one of the major contributors to in-cab noise and pass-by-noise of the vehicle. This research proposes a silencer with an integrated acoustic valve to reduce exhaust tailpipe noise. Incident exhaust wave coming from the engine strikes the acoustic valve and generates reflected waves. Incident waves and reflected waves cancel out each other which results in energy loss of the exhaust gas. This loss of energy results in reduced noise at the exhaust tailpipe end. To evaluate the effectiveness of the proposed silencer on the vehicle, NVH (Noise, vibration, and harshness) performance of the proposed silencer was compared with the existing silencer which is without an acoustic valve. A CNG (Compressed natural gas) Bus powered by a six-in-line cylinder engine was chosen for the NVH testing.

Underrun Protection devices (UPDs) are specially designed barriers fitted to the front, side, or rear of heavy trucks. In case of accidents, these devices prevent small vehicles such as bikes and passenger cars going underneath and thus minimizing the severity of such accident. Design and strength of UPD is such that it absorbs the impact energy and offers impact resistance to avoid the vehicle under run. Compliance to UPD safety regulations provides stringent requirements in terms of device design, dimensions, and its behavior under impact loading. Since accuracy of Computer Aided Engineering (CAE) predictions have improved, numerical tools like Finite element method (FEM) are extensively used for design, development, optimization, and performance verification with respect to target regulatory performance requirements. For improved accuracy of performance prediction through FEA, correct FE representation of sub-systems is very important.

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.

Road infrastructure in India is being upgraded at a rapid pace. Quality of life of people has also improved significantly in the last decade. Such trends have significantly impacted design of commercial vehicles and vehicular systems in the country. This paper deals with the design and development of a modern futuristic instrument panel for trucks. Methodology to arrive at product features and solutions which retain their novelty and appeal for a longer term has also been illustrated. Regulatory scenario, modularity, HMI, Perceived Quality, Driver Comforts, evolving technologies, trends and materials are some of the considerations which have discussed in detail. International benchmarks and customer requirement have been analyzed for setting Performance targets. A digital approach for evaluating these considerations evolved during the design and development process has been elaborated in detail.

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.

The automotive world is rapidly moving towards achieving shorter lead time using high-end technological solutions by keeping up with day-to-day advancements in virtual testing domain. With increasing fidelity requirements in test cases and shorter project lead time, the virtual testing is an inevitable solution. This paper illustrates method adopted to achieve best approximation to emulate driver behavior with 1-D (one dimensional) simulation based modeling approach. On one hand, the physical testing needs huge data collection of various parameters using sensors mounted on the vehicle. The vehicle running on road provides the real time data to derive durability test specifications. One such example includes developing duty cycle for powertrain durability testing using Road Torque Data Collection (RTDC) technique. This involves intense physical efforts, higher set-up cost, frequent iterations, vulnerability to manual errors and causing longer test lead-time.

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.

The brake systems are given top priority by automotive OEMs in the development of medium and heavy commercial trucks and buses, which can carry increased loads. When trucks and buses are travelling at high speeds or crossing downhill, during braking operations, the friction faces (brake drum and liner) experience a significant rise in temperature due to the conversion of kinetic energy into heat energy within seconds. This lowers the friction coefficient at the interface, resulting in distortions, thermal cracks, hub grease burning, and overheating. Drum brake system designs must be improved and optimized to dissipate more heat from the brake drum assembly and prevent brake failure. Nowadays advance transient numerical simulations assist in the design, development and optimization of the brake system to visualize 3D flow physics and temperature variations throughout the brake duty cycles. In the current study, different Cases of drum brakes to improve cooling efficiency are evaluated.

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.

The goal of reducing fuel consumption and CO2-Emission is leading to turbo-charged combustion engines that deliver high torque at low speeds (down speeding). To meet NVH requirements damper technologies such as DMF (Dual Mass Flywheel) are established, leading to reduced space for the clutch system. Specific measures need to be considered if switching over from SMF (Single Mass Flywheel) to DMF [8]. Doing so has an impact on thermal behavior of the clutch system, for example due to reduced and different distribution of thermal masses and heat transfer to the surroundings. Taking these trends into account, clutch systems within vehicle powertrains are facing challenges to meet requirements e.g. clutch life, cost targets and space limitation. The clutch development process must also ensure delivery of a clutch system that meets requirements taking boundary conditions such as load cycles and driver behavior into account.