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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.

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.

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.

Vehicle dynamics is one of the most important vehicle attributes. It is classified into three domains, the longitudinal, vertical, and lateral dynamics. This paper focuses on optimizing the lateral vehicle dynamics which is driven by the straight ahead controllability and cornering controllability of the vehicle. One of the important parameters that dictates these sub-attributes is the steering ratio. Therefore, designing the right steering ratio is critical to meet the vehicle “specific” targets. Significant amount of work has been done by many researchers on variable steering ratio by implementing variable gear ratio (VGR) rack, active steering, and steer-by-wire systems. This paper discusses the methodology and considerations to optimize the steering ratio for a constant gear ratio rack by optimizing the steering column layout, viz., orientation and the phase angle in universal joints.

Gasoline engines with Multi point fuel injection (MPFI) technology are being developed with naturally aspirated and/or turbocharged engines. Wherein a MPFI and turbo charged combination engines have certain challenges during development stages. One of the important challenge is design of air intake and exhaust system. With MPFI turbocharged engine combination, the under bonnet heat management is crucial task for drivability. The heat management of air intake plays a vital role in drivability part therefore a design layout of air intake path is an important aspect. Drivability can be categorized as low end, mid-range and top end drivability. Turbocharged MPFI engines have a typical phenomenon of ‘Lag in response’ in the low-end region. This ‘Lag in response’ phenomenon at low-end drivability region can be overcome through optimization of air intake system and optimization of exhaust back pressure.

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.

Pneumatic brake system is widely used in heavy truck, medium and heavy buses for its great superiority and braking performance over other brake systems. Pneumatic brake system consists of various valves such as Dual Brake Valve (DBV), Quick release Valve (QRV), Relay Valve (RV), Brake chambers. Dynamics of each valve is playing a crucial role in overall dynamic performance of the braking system. However, it is very difficult to find the contribution of each valve and pipe diameters in overall braking performance. Hence, it is very difficult to arrive a best combination for targeted braking performance as it is not possible to evaluate all combination on the actual vehicle. Hence, it is very important to have a mathematical model to optimize and evaluate the overall braking performance in early design phase. The present study is focusing on the mathematical model of a pneumatic brake circuit.

The objective of the work presented in this paper is to provide an overall CFD evaluation and optimization study of cabin climate control of air-conditioned (AC) city buses. Providing passengers with a comfortable experience is one of the focal point of any bus manufacturer. However, detailed evaluation through testing alone is difficult and not possible during vehicle development. With increasing travel needs and continuous focus on improving passenger experience, CFD supplemented by testing plays an important role in assessing the cabin comfort. The focus of the study is to evaluate the effect of size, shape and number of free-flow and overhead vents on flow distribution inside the cabin. Numerical simulations were carried out using a commercially available CFD code, Fluent®. Realizable k - ε RANS turbulence model was used to model turbulence. Airflow results from numerical simulation were compared with the testing results to evaluate the reliability.

Use of adhesives in automotive require in-depth material, design, manufacturing & engineering knowledge. It is also necessary to understand functional requirements. For perfect and flawless adhesive joinery, the exact quantity of adhesive, its material composition, thickness of adhesive layer, substrate preparation methods for adhesive bonding, handling and curing time of the adhesive have to be studied & optimized. This paper attempts to describe different aspects of adhesive bonding in automotive industry to include: Selection of adhesives based on application and design of the components, surface preparation of adherend, designing of adhesive joint, curing conditions of adhesives, testing and validation of adhesive joints. Emphasis was given to study & verify the performance of different adhesive joints to meet end product requirements. Samples were prepared with a variety of adhesive and adherend combinations.

As the vehicle functions are getting distributed over multiple ECUs in order to realize various complex control functions, the need for sophisticated on-board diagnostic strategies are increasing in automotive domain, leading to a significant amount of hardware and software implementations for fault management inside various ECUs in the vehicle. This paper proposes optimized vehicle level approach for fault management strategies, wherein a centralized intelligent Gateway Module is proposed in the vehicle network architecture, which will be responsible for fault management of the complete vehicle in a chronological sequence. This Gateway Module will thereby have the possibility to group a cluster of faults raised by different ECUs and correlate them meaningfully to guide the operator towards root cause of the fault.

Design of a Cabin Tilting System of heavy trucks, a multi degree of freedom mechanism, is a challenge. Factors like adequate tilting angle, cabin styling, packaging, non interference of tilting system with ride comfort, forces in the system, specifications of the hydraulic system, are all very important for designing the system. Numerous considerations make the design process highly iterative hence longer design time. This paper primarily focuses on Kinematics and Dynamic analysis of the system in ADAMS and validation of system with real time testing results. Intention of this work is to make a parametric ADAMS model and link it to a Knowledge Based Engineering application to facilitate designer to quickly carry out design iterations for reducing development time. The Knowledge Based Engineering software is made using object oriented language called ‘Object Definition Language’ which has been developed using C and C++ software languages.