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Driving dynamics performance is one of the key customer attributes to be developed during product development. In the vehicle development process, freezing the hardware of the chassis aggregates is one of the major priorities to kick off the other vehicle development activities. The current work involves the development of a multilink suspension for an SUV class vehicle. Typically, each OEM performs several product development loops for maturing the vehicle design. The driving dynamics performance evaluation and tuning happens on a physical vehicle with the driver in Loop. Tuning of suspension parameter on the physical vehicle entails actual replacement of parts/components. This encompasses multiple tuning cycles in product development associated with increased cost and test time. To reduce the product development time and cost while delivering first time right chassis configuration, we took an approach of getting driver-in-loop through driving simulator in the concept phase.

In the context of vehicular safety and performance, brake pads represent a critical component, ensuring controlled driving and accident prevention. These pads consist of friction materials that naturally degrade with usage, potentially leading to safety issues like delayed braking response and NVH disturbances. Unfortunately, assessing brake pad wear remains challenging for vehicle owners, as these components are typically inaccessible from the outside. Moreover, Indian OEMs have not yet integrated brake pad life estimation features. This research introduces a hybrid machine learning approach for predicting brake pad remaining useful life, comprising three modules: a weight module, utilizing mathematical formulations based on longitudinal vehicle dynamics to estimate vehicle weight necessary for calculating braking kinetic energy dissipation; and temperature and wear modules, employing deep neural networks for predictive modeling.

Enriched ventilation and driver assistance systems which plays vital role in human thermal comfort and safety, are now necessities for the whole automotive sector. For faster cabin thermal comfort, air circulation around occupant’s body reveals higher cabin comfort index. In India natural and forced ventilation system is predominantly used in commercial vehicles as an economical solution for achieving interim cabin comfort over air conditioning system. Presently used forced ventilation system consist of electrically driven blower motor to remove stale air around human body which is adding alternator load and thus affects fuel economy. Remarkably, 22% of such auxiliary electrical load is taken by electrical components from engine generated power. In order to enhance cabin thermal comfort and conceivably reduce power usage, an effective air flow control system is need of hour.

In the modern era of automotive industry, occupant comfort inside the cabin is a basic need and no more a luxury feature. With increase in number of vehicles, the expectations from customers are also changing. One of the major expectations from real world customers is quick cabin cooling thru all seasons, particularly when the vehicle is hot soaked and being used in summer conditions. Occupant thermal comfort inside the vehicle cabin is provisioned by a mobile air conditioning (MAC) system, which operates on a vapor compression-based cycle using a refrigerant. The main components of a direct expansion (DX) based MAC system are, a compressor, condenser, evaporator, and expansion valve. Conditioned air is circulated inside the cabin using a blower, duct system and air vents. The AC condenser is the most critical component in AC circuit as it rejects heat, thereby providing for a cooling effect inside the cabin.

Vehicle aesthetic appearance is critical factor in the perceived quality of a vehicle. Auto OEM focuses on the improvement of perceived quality. The perceived quality of a vehicle is improved by achieving a superior finish on the visible parts. Plastic parts used in visible areas are painted to achieve a superior finish & aesthetic. However, the painting process is very energy intensive, releases a lot of harmful VOCs into the environment, emits carbon di-oxide into the environment & is a very costly process. Also, painted parts pose a challenge for recycling at the end of life. For painting one square meter area, around 6.5 Kg of co2 is released. Additionally, the painting cost contributes to around 60 % of the part cost. As the emphasis has increased on sustainability & reducing the cost, we took the challenge to develop novel mold in color material to eliminate the painting process without compromising the aesthetic & functional requirements of part.

Twist-beam suspensions are an example of design solution presenting acceptable performance when applied to passenger cars & light vehicles and it can provide an optimal between cost & performance in the automotive market. For these reasons, twist beam is quite popular in use in rear suspension of light vehicles. In contrary to other types of suspension, the twist-beam has a flexible torsion beam connecting the swing arms. The study of the deformation of this flexible element becomes important to understand its performance and durability behavior. As the name signifies, twist beam major performance attribute is control of twist or opposite wheel travel arising from vehicle roll or road input. Current approach for the study this deformation is through FEA & Multi-body dynamics software tools.

Automotive suspension system forms the basis for the design of vehicle with durability, reliability, dynamics and NVH requirements. The automotive suspension systems are exposed to dynamic and static loads which in turn demands the highest integrity and performance against fatigue based metallic degradation. The current focus in automotive industry is to reduce the weight of the automotive parts and components without compromising with its static and dynamic mechanical properties. This weight reduction imparts fuel efficiency with added advantages. High-Strength Low Alloy steel (HSLA) offers optimum combination of ductility, monotonic and cyclic mechanical properties. Furthermore, welding processes offer design flexibility to achieve robust and lightweight designs with high strength steels.

Small commercial vehicles (SCVs) are the drivers of a major part of India’s indirect economy, providing the most efficient means of transport. With the introduction of BS-VI norms, some major overhauls have been done to the SCV models to meet BS VI norms in challenging timeline for early market entry. This forced to automotive designers towards challenge of cost competitiveness as well as refinement level to survive in this competitive market. This paper explains the systematic approach used to overcome challenges of higher tactile vibrations, higher in-cab noise because of BS VI requirement in 2 cycle engine required for small commercial vehicle. The solutions were need to be worked out without compromising the other performance attributes like total cost of ownership, fuel economy, ease of servicing and cost effectiveness.

Durability is an important indicator to measure the automobile quality and reliability. Automotive industry is striving to develop products having excellent performance to weight ratios and along with high safety standards. A successful product should have adequate robustness during normal customer operation and the ability to withstand high impact events without impairment of function or safety relevant damage. Road Load Data Acquisition (RLDA) along with efficient design and validation processes are, among others, critical factors for success in the automotive industry. Physical RLDA is expensive and time consuming, the prototype vehicles being costly and only available at a later stage in the vehicle development cycle. Component failures occurring on the proto test vehicles can prove to be a major setback, delaying the product launch by months. In order to overcome above challenge, this paper presents an innovative methodology to carry out Digital RLDA (dRLDA).

Polymers are substituting traditional materials, such as metals, in existing as well as new applications, both for structural and aesthetic applications as they are lightweight, customizable and are easy to mould into complex shapes. With such an extensive use of polymers, there is a need to carefully scrutinize their performance to ensure reliability. This is particularly the case in the automotive and electronic industries where the aesthetic appeal of their products is of prime concern and any visible scratch damage is undesirable. Concern for aesthetics has led to a need for the quantification of visibility due to scratch damage on polymeric surfaces Many painted plastic parts used in vehicles are being replaced with the molded-in color plastics for cost reduction and also due to environmental concerns associated with solvent emissions. There are multiple methods used for scratch evaluation of polymers and paints.

With the introduction of Connected Vehicles, it is possible to extend the limited horizon of vehicles on the road by collective perceptions, where vehicles periodically share their information with other vehicles and servers using cloud. Nevertheless, by the time the connected vehicle spread expands, it is critical to understand the validation techniques which can be used to ensure a flawless transfer of data and connectivity. Connected vehicles are mainly characterized by the smartphone application which is provided to the end customers to access the connectivity features in the vehicle. The end result which is delivered to the customer is through the integrated telematics unit in the vehicle which communicates through a communication layer with the cloud platform. The cloud server in turn interacts with the final application layer of the mobile application given to the customer.

Environmental regulation, operating cost reduction and meeting stringent safety norms are the predominant challenges for the automotive sector today. Automotive OEMs are facing equally aggressive challenges to meet high fuel efficiency, superior performance, low cost and weight with enhanced durability and reliability. One of the key technologies which enable light weighting and cost optimization is the use of fiber reinforced polymer (FRP) composite in automotive chassis systems. FRP composites have high specific strength, corrosion and fatigue resistance with additional advantage of complex near net shape manufacturing and tailor made properties. These advantages makes FRPs an ideal choice for replacing conventional steel chassis automotive components. However, FRP’s face challenges from operating environment, in particular temperature and moisture.

The small commercial vehicle business is driven by demand in logistic, last mile transportation and white goods market. And to cater these businesses operational and safety needs, they require closed container on vehicle. As of now, very few OEM’s provide regulatory certified container vehicle because of constrains to meet inertia class of the vehicle. This paper focuses on design of a durable and extremely reliable container, made of the low-cost economy class glass fibre & core material. The present work provides the means to design the composite container for the N1 category of the vehicle. The weight of after-market metal container ranges between 300-350 Kg for this category of vehicle, which affects the overall fuel economy and emission of the vehicle. A detailed CAE analysis is done to design composite container suitable to meet inertia class targets and to achieve weight reduction of 30-40% as compared to metal container.

With the advent of BS VI regulations, automotive manufacturers are required to innovate the powertrains, fuel systems, exhaust and its after treatment systems to meet the regulatory requirements. The exhaust regulations can be met either by reducing the exhaust gases being generated by the engine (attacking the source) or by treating the exhaust gases in after treatment devices. The choice of the opted system varies with the manufacturer. The after-treatment devices such as catalytic converters are generally mounted in the engine compartment to take advantage of high temperature of exhaust gases to yield the reactions. Such an arrangement imposes a lot of thermal load on the peripheral components such as gearshift cables, bearings, oil seals, driveshafts etc. Thermal shields or thermal sleeve are used to address thermal issue and to protect transmission components.

Various vehicle manufacturers are launching electric vehicles, which are more sustainable and environmentally friendly. The major component in electric vehicles is the battery, and its performance plays a vital role. Usually, the end of life of a battery in the automobile sector is when the battery capacity reaches 80% of its maximum rated capacity. The capacity of a lithium-ion cell declines with the number of cycles. So, a semi-empirical model is developed for estimating the maximum stored capacity at the end of each cycle. The parameters considered in the model explain the changes in battery internal structure, like capacity losses at different conditions. The capacity estimated using the semi-empirical model is further taken as the inputs for estimating capacity using the Artificial Neural Network (ANN) and Machine Learning (ML) techniques i.e., Linear Regression (LR), Gaussian Process Regression (GPR), Support Vector Machine methods (SVM).

The automotive application places very special demands on the air conditioning system. As is the case with any other process, system efficiency is very important and the automotive air-conditioning application is no exception. While the characteristics of all the major components in the air conditioning system like compressor, condenser, evaporator and blower contribute to overall system efficiency, localized inefficiencies do play a part and so must be kept to a minimum, especially in this day and age when extra emphasis is being laid on sustainability. One such phenomenon that contributes to the system inefficiency is heat pick-up in suction line. Since the temperature at the evaporator-outlet is quite lower than ambient and also its surroundings (steering system pipes and hoses, engine, air intake pipes and so on), the refrigerant picks up heat as it moves along the suction line up to the compressor inlet. This heat pick-up is detrimental to the overall system performance.

The interior components of a passenger vehicle are designed to provide comfort and safety to its occupants. In the event of accident, vehicle interiors are primary source of injuries when occupants interact with them. Vehicle interiors consists of Instrument panel (IP), center console, seats and controls in front of seating position etc. Severity of the injuries depends on the energy dissipating characteristics, profiles, projections of different interior components. These are assessed by ECE R21 and IS12553 head form impact tests. To evaluate the Head form impact performance on Interior components, Computer Aided Engineering (CAE) simulations are extensively used during the vehicle development. In order to predict failure of plastic components and snap joints which might lead to expose sharp edges, it is critical to model plastic material and snap joint.

Aerodynamics performance evaluation of passenger cars is important during early vehicle development phase as it influences fuel economy, vehicle stability and drivability. Usually during initial styling phase, scale model is prepared and tested in wind tunnel to check aerodynamic performance like drag coefficient and these are used to predict aerodynamic performance of full scale model as testing on full scale model is costly and time consuming. To ensure its correctness, it is important to understand difference in physics from scale model to full scale model. In predicting full vehicle aerodynamics performance from scale model assessment; importance of Reynolds number, effect of geometric scaling on flow i.e. flow separation and wake zone change needs to be understood and addressed. This paper discusses about effect of scaling on aerodynamic flow behavior and drag.

OEMs are seeking to develop vehicle light weighting strategies that will allow them to meet weight and fuel economy targets hence increasingly shifting their focus towards incorporating lighter material solutions at mass produced scales. Composites are seen by automotive manufacturers as the solution to lightweight vehicles without affecting their performance. More and more parts are made of short fiber reinforced plastics (SFRP) as well as continuous fiber composites. However, replacing metals by composites requires a new design approach and a clear understanding of the composite behavior. This paradigm however requires a dedicated tool for composite design in order to take into account the specific composite behavior. Traditional design tools are not able to state accurately the composite material behavior and sometime leading to use high safety of factors and lack of confidence in the design.

Vehicle manufacturers strive hard to achieve best in class fuel economy. Apart from light weighting of the structures, driveline optimization and reduction of tire rolling resistance, tapping of parasitic losses is also important and helps to optimize the design of auxiliary power consuming systems. One of such system studied in this work is power steering system. The effect of parasitic losses on fuel economy is predominant for small commercial vehicle compare to heavy vehicles. The evaluation of deterioration in the fuel economy due to implementation of power steering system on one of the small commercial vehicle is carried out using multiple virtual simulation tools. Virtual route profile is modelled using longitude, latitude and altitude data captured through GPS and steering duty cycle is mapped in terms of steering rotation angle. A system level model of hydraulic power steering system is developed.