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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.

With the revolutionary advancements in modern transportation, offering advanced connectivity, automation, and data-driven decision-making has put the intelligent transportation systems (ITS) to a high risk from being exposed to cyber threats. Development of modern transportation infrastructure, connected vehicle technology and its dependency over the cloud with an aim to enhance safety, efficiency, reliability and sustainability of ITS comes with a lot more opportunities to protect the system from black hats. This paper explores the landscape of cyber threats targeting ITS, focusing on their potential impacts, vulnerabilities, and mitigation strategies. The cyber-attacks in ITS are not just limited to Unauthorized Access, Malware and Ransomware Attacks, Data Breaches, Denial of Service but also to Physical Infrastructure Attacks.

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.

High strength aluminium alloys are an ideal material in the automotive sector leading to a significant weight reduction and enhancement in product safety. In recent past extensive development in the field of high strength steel and aluminium was undertaken. This development has been propelled due to demand for light weight automotive parts. The high strength to weight ratio possessed by Al alloy helps in reducing the total weight of the vehicle without effecting the overall performance, thereby increasing the fuel economy, and reducing the carbon emission level. Joining of high strength aluminium alloy is critical to develop durable automotive products. Joining of high strength aluminium alloy for mass production in automobile industry is a challenging task. Laser welding is recognized as an advanced process to join materials with a laser beam of high-power, high- energy density.

Vehicle transmission gear rattle is one of the most critical NVH irritants for refined vehicles. It is perceived more dominantly in lower gears of vehicle running. It depends on various design parameters like engine input torque amplitude & fluctuations, driveline torsional vibrations, gear micro & macro geometry, shaft flexibility, etc. Establishing exact contribution of each of these parameters to transmission rattle, thru experimental or simulation technique, is very challenging. Current paper explains the NVH CAE benchmark approach deployed to understand difference in rattle behavior of two transmission designs. Paper focuses on simulation of gear impact power and its sensitivity to transmission shaft deflections.

This paper aims at analysing the effect of regeneration braking on the amount of energy harnessed during vehicle braking, coasting and its effect on the drive train components like gear, crown wheel pinion, spider gear & bearing etc. Regenerative braking systems (RBS) is an effective method of recovering the kinetic energy of the vehicle during braking condition and using this to recharge the batteries. In Battery Electric Vehicles (BEV), this harnessed energy is used for controlled charging of the high voltage batteries which will help in increasing the vehicle range eventually. Depending on the type of the powertrain architecture, components between motor output to the wheels will vary, i.e., in an e-axle, motor is coupled with a gear box which will be connected with differential and the wheels. Whereas in case of a central drive architecture, motor is coupled with gearbox which is connected with a propeller shaft and then the differential and to the wheels.

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.

Transmission of a vehicle, being driven by an internal combustion engine is susceptible to torsional vibrations which are inherent property of an internal combustion engine. Torsional are produced in the engine because of multiple power strokes happening in multiple cylinders of the engine at regular intervals. These torsional vibrations affect each and every rotating component in the powertrain. A lot of work has been done in past in the area of ECU calibration, flywheel inertia, clutch dampener springs etc. to reduce the vibrations. These methods have limitations for the extent of damping that can be introduced into the system. Un-damped torsional vibrations when transferred further it affect rotating / oscillating components of transmission. Inside the transmission, it leads to rattle issues and affect the life of synchronizers or engaging gears. This paper describes the methodology to address the effect of high torsional vibration on synchronizer of commercial vehicle.

This paper focuses on developing an application to extract insights from Android app reviews of Connected Car Applications and Twitter conversations related to OEM’ PV & EV Vehicles and features. Analyzing user sentiments and preferences in real-time can drive innovation and elevate OEMs' customer satisfaction. These insights have the potential to enhance vehicle performance and the manufacturing process. The application employs data collection and Natural Language Processing (NLP) techniques, including User-Driven Sentiment Classification and topic modeling, to analyze user sentiments and identify key discussion topics visually.

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.

Tire inflation pressure has a significant impact over vehicle driving dynamics, fuel consumption as well as tire life. Therefore, continuous monitoring of tire pressure becomes imperative for ride comfort, safety and optimum vehicle handling performance. Two types of tire pressure monitoring systems (TPMS) used by vehicles are - direct and indirect TPMS. Direct systems deploy pressure sensors at each wheel and directly send pressure value to the vehicle Controller Area Network (CAN). Indirect sensors on the other hand use the information from already existing sensors and some physics-based equations to predict the value of tire pressure. Direct TPMS tend to be more accurate but have higher cost of installation while indirect TPMS comes with a minimum cost but compromised accuracy. A digital proof-of-concept study for indirect TPMS development of a non-ESP vehicle based on machine learning (ML) technique is elaborated in this paper.

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.

The vehicle Heating, Ventilation and Air conditioning (HVAC) system is designed to meet both the safety and thermal comfort requirements of the passengers inside the cabin. The thermal comfort requirement, however, is highly subjective and is usually met objectively by carrying out time dependent mapping of parameters like the velocity and temperature at various in-cabin locations. These target parameters are simulated for the vehicle interior for a case of hot soaking and its subsequent cool-down to test the efficacy of the AC system. Typically, AC performance is judged by air temperature at passenger locations, thermal comfort estimation along with time to reach comfortable condition for human. Simulating long transient vehicle cabin for thermal comfort evaluation is computationally expensive and involves complex cabin material modelling.

The automotive world has seen an increase in customer demands for vehicles having low noise and vibrations. One of the most important source of noise and vibrations associated with vehicles is the vibration of driveline systems. For commercial vehicles, the refinement of drivelines from NVH point of view is complex due to the cost and efficiency constraints. The typical rear wheel drive configuration of commercial vehicles mostly amplifies the torsional vibrations produced by engine which results into higher noise in the vehicle operating speed range. Theoretically, there are various options available for fine tuning the torsional vibration performance of the vehicle drive train. The mass moments of inertia and stiffness of the drivetrain components play significant role in torsional vibration damping, however, except minor changes to flywheel mass, it is hardly possible to change other components, subject to design limitations.

This research paper is dealing with development of a Hybrid Exhaust muffler with four different shell configurations (Internal design unaltered) and investigated the impact on noise performance and quality (perceived). Noise performance has been evaluated by measurement of Pass by Noise and near exhaust noise Level on a typical 16T -6-speeds transmission Truck. The experimental activity conducted based on DOE approach. From this study, it observed single shell with lower thickness have the poor NVH performance and perceived quality as well. Shell or booming noise is also observed with this configuration. Double shell with Ceramic blanket (throughout the length) sandwich configuration exhibited the best performance though this design is most expensive among the four mufflers.

Now a day’s automated manual transmissions (AMT) are getting popular because of hassle-free gear shifting and improved fuel economy. OEMs are converting their existing manual gearbox to AMT gearbox with solution like hydraulic or electric AMT kit that replaces the manual shift mechanism to automated actuators. Generally, in manual gearbox, the operational principal of reverse gear is sliding mesh. Due to sliding mesh gear arrangement, it can create interruption for gearshift while controlling shift actuators. In this paper, reverse gear shift arrangement and its operational dynamics at different operating condition has been studied and analyzed in detail. Based on status of vehicle, to ease the gearshift, engagement flow process proposed. The control methods that increases probability of smooth and easier shifting in all operating condition discussed in detail. The developed control algorithm discussed along with its implementation on real vehicle and results.

Drive components of live axle undergoes different loading conditions during field usage depending upon terrain conditions, vehicle loading and traffic conditions etc. During vehicle running, drive components of axle experiences variable torque levels, which results in the fatigue damage of the components. Testing of these drive components of axle on test rig for endurance life is an imperative part of axle development, owing to limitations of vehicle testing because of time and cost involved. Similarly, correlating field failures with rig testing is equally critical. In such situation, if a test cycle is derived correlating the field usage, rig testing can be effectively used for accelerated life testing and reliability prediction of these components. An approach is presented in the paper wherein test cycle is derived based on the data collected on vehicle in the field under service road and loading conditions.