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In high-end commercial vehicles, technologies like Electronic Braking Systems (EBS) help pull away the vehicle from a standstill on steep gradients with no risk of rolling back. Tata Motors has developed an indigenous Anti-Roll Back (ARB) system that effectively minimizes this risk but without the use of EBS/HSA. The ARB delivers identical functionality to the HSA feature in the EBS but autonomously, and by purely electric means. In the proposed system, the electric traction motor develops a high positive torque when the vehicle tries to roll back upon minimal accelerator pedal press. The system is autonomous in the sense that the driver does not need to press any HSA switch on the dashboard and the system works on relatively flatter road also which otherwise is not the case with HSA as it negatively affects the operation on flatter road by locking wheels and vehicle launches with a very high torque when brakes are automatically released by EBS upon threshold torque build-up.

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.

A robust process of specifying engine mounting systems for internal combustion engines (ICE) has been established through decades of work and countless applications. Vehicle vibration is a critical consideration in the early stage of vehicle development. Apart from comfort, it also affects the overall vehicle's performance, reliability, Buzz-squeak and rattle (BSR), parts durability and robustness. The most dynamic system in a vehicle is the powertrain, a source of vibration inputs to the vehicle over the frequency range. The mounting system supports a powertrain in a vehicle and isolates the vibration generated from the powertrain to the vehicle. In addition, it also controls the overall dynamic movement of the powertrain system when the vehicle is subjected to road load excitations and avoids contact between the powertrain and other adjacent components of the vehicle.

The steering system of an automobile serves as the initial point of contact for the driver and is a crucial determinant in the purchasing choice of the vehicle. The present steering system is equipped with a singular Electric Power Assisted Steering (EPAS) map, resulting in a consistent steering sensation during maneuvers conducted at both low and high velocities. Certain vehicles are equipped with a steering system that includes fixed driving modes that require manual intervention. This paper presents a proposed Machine Learning based Adaptive Steering System that aims to address the requirements and limitations of fixed mode steering systems. The system is designed to automatically transition between comfort and sports modes, providing users with the desired soft or hard steering feel. The system utilizes vehicle response to driver input in order to identify driving patterns, subsequently adjusting steering assist and torque automatically.

This paper addresses the "Grunt Noise" anomaly in Hydraulic Power Assisted Steering (HPAS) systems, detailing an extensive effort to resolve this disruptive issue. HPAS, while cost-efficient, faces challenges as it adapts to customer demands for reduced steering effort and enhanced handling. Intensified HPAS intervention requires components to withstand higher pressures and tighter tolerances, leading to occasional anomalies. "Grunt Noise" arises from Torsion bar (T-bar) resonance with fluid pressure pulsations. A comprehensive study identifies load conditions, transfer paths, and frequency bands, extending from vehicle to Pinion Valve assembly levels. Root cause analysis traces the issue from Steering Wheel to T-bar, validating the approach. The T-bar's twisting operation renders torsional stiffness crucial for Grunt Noise. Lower stiffness T-bar, when overpowered by liquid force, causes microsecond imprecise valve openings, leading to cavitation-induced Rack & Pinion vibrations.

Designing a Passenger vehicles suspension system is a key challenge for all OEMs because balancing buzz, squeak, and rattle (BSR) acoustic performance at low-speed driving and improving ride quality at high-speed driving conditions are bet challenging. Suspension noise deteriorates in-cab acoustic quietness and overall vehicle performance. For this reason, optimizing these noises is becoming increasingly prioritized as a key design issue throughout the development process of suspension system. This paper studies the various components of suspension system and their noises in Passenger vehicles. Based on customer voice index and drive pattern, suspension anomalous Clunking noise was identified in Passenger vehicles. This noise phenomenon was cascaded from the vehicle level to BSR rig and eventually to the suspension rig for root cause analysis.

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.

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 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.

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 comparison to traditional gasoline-powered vehicles, Electric vehicles (EVs) development and adoption is driven by several factors such as zero emissions, higher performance, cost effective in maintenance, smoother and quieter ride. Global OEMs are competing to provide a reduced in-cab noise for ensuring a smooth and quiet driving experience. Short project timelines for EV demands quick design and development. In initial stages of project, input data availability of EV is limited and a simplified approach is necessary to accelerate the development of vehicle. This paper focuses on simulation methodology for predicting structure borne noise from powertrain deploying Transfer Path Analysis approach. Current simulation methodology involves full vehicle model with multiple flexible bodies and full BIW flexible model which leads to complex modelling and longer simulation times.

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.

Groan is a low frequency noise generated when moderate brake pressure is applied between the surfaces of the brake disc and the brake pad at a low-speed condition. Brake groan is often very intense and can cause large numbers of customer complaints. During a groan noise event, vehicle structure and suspension components are excited by the brake system and result in a violent event that can be heard and felt during brake application. The cause of noise is friction variation of stick-slip phenomenon between friction material and disc. Creep groan is the structure-borne noise that is related to dynamic characteristic of the vehicle. However, it has been mainly improved through friction material modifications in the past. In this paper, transfer path of creep groan noise was analyzed by means TPA and structural countermeasure to creep groan noise was suggested. This paper discusses the approach for prediction and mitigation of brake groan noise for passenger vehicles having disc brakes.

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.

Error in suspension asymmetry or tire parameters may lead to vehicle drifting laterally from its intended straight-line path, which is called vehicle pull. Driver then needs to apply constant steering correction to maintain the vehicle in straight line which will lead to high driver fatigue and deteriorate driving experience. Manufacturing a perfectly symmetric suspension system is impractical, however an insight into the manufacturing tolerances of suspension system at the early design stage can be extremely useful. Also tire force and moment parameters at straight line operation and its maximum allowable variations will help in defining the tire parameter specifications and tolerances. The objective of this study was to develop a 1D model of suspension and tire system which can predict the torque experienced in steering and drift of the vehicle from straight line due to the tire force and moment and asymmetric suspension geometry.

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 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.

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.