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Rotavator is an active tillage implement for breaking the Soil and for the preparation of seed bed for cultivation. The Farmers are currently facing problem due to usage of sub optimal speed of Rotavator which results in more fuel consumption, takes more time for completion of operation. Also, the Current Rental models work on Tractor + Implement as rental combination and customer not able to rent Rotavator as a standalone implement due to non-availability of Tracking information such as hours of utilization on Rotavator. Farmers not able to maintain the service periodicity, if oil change not done in prescribed duration then it may result in improper maintenance and breakdown of the Rotavator. To overcome these problems a smart Rotavator developed consists of an electronic unit fitted on the Rotavator shaft to measure the speed of the shaft rotation and in turn convert to Rotavator speed and also able to convert into Hours of usage based on the starting and stopping of the rotavator.

Connected vehicle services have come a long way from the early days of telematics, both in terms of breadth of the class of vehicles, and in terms of richness or complexity of the data being handled for Enhancing Customer Experience. The Connectivity Control unit (CCU) is a gateway device for the vehicle to the outside world. While it enables transmission of vehicle data along with the location information. CCU is currently validated in the vehicle to check functionality. It has cost, time drawbacks and prevents effective testing of many scenarios. Bench level validation will not be able to complete functionality validation. There is subset of validation tools or semi-automated solutions are available in the market, but they are not fully functional, and critically cannot perform end to end validation. Automated Test setup for CCU in lab simulating the entire field data of the vehicle with modifiable characteristics.

Being a safety critical aggregate, every aspect of brake system is considered significant in vehicles operations. Along with optimum performance of brake system in terms of deceleration generation, brake pedal feel or brake feel is considered as one of the key elements while evaluating brake system of vehicles. There are many factors such as liner and drum condition, road surface, friction between linkages which impress the pedal feel. Out of these, in this paper we will be discussing the factors which influence the brake pedal feel in relation to the driver comfort and confidence building. Under optimum braking condition, brake operation must be completed with pedal effort not very less or not very high, brake pedal feel must be firm throughout the operation, in such a way that it will not create fatigue and at the same time it will give enough confidence to the driver while operating with acceptable travel.

In automotive Body-In-White (BIW) structures, stiffness and the fatigue behavior is greatly influenced by the properties of its joints. Spot welding is one of the most widely used process for joining of sheet metals in BIW. Spot weld fatigue life under Accelerated Durability Test (ADT) is crucial for durability performance of BIW structures. Experience of BIW validations highlighted more number of spot weld failures in CAE when compared to actual tests. Hence, lot of iterations in the form of design modifications are required to be carried out to make these spot welds meet the targets which increases design & development time as well as cost. Current practice uses force-based approach for predicting spot weld fatigue life in CAE. To improve the spot weld fatigue life correlation, extensive study has been carried out on the approaches used for calculating spot weld fatigue life, namely force & stress-based approaches.

With an intense competitive automotive environment, it becomes imperative for any OEM to launch their products into the market in a short span of time & with a ‘First Time Right’ approach. Within the current scenario in the Automotive Industry, the selection of optimum set of hard points and wheel geometry often becomes an iterative or a trial-and-error process which is both time consuming and involves higher development cost as there may be instances where 2 to 3 sets of iterations are needed before specification is finalized for production. Through this paper, an attempt has been made to develop a methodology for deciding wheel geometry parameters (covered in the later section of this paper like Caster, Camber, Mechanical trail, etc.) [1, 2, 3, 4] for a three wheeled vehicle as a First Time Right (FTR) approach to cut down on conventional, expensive & time-consuming iterative approach.

The ECE R-14, AIS015 safety standard specifies the requirements of the safety belt anchorages namely, minimum numbers, their locations, static strength to reduce the possibility of their failure during accidental crashes for effective occupant restraint and the test procedures. This standard applies to the anchorages of safety belts for adult occupants of forward facing or rearward facing seats in vehicles of categories M and N. ECE R14 ensures the passenger safety during sudden acceleration/retardation and accidents. Early simulations revealed some structural short falls that demanded cabin improvements in order to fulfill regulation requirements for the seal belt anchorage test. This paper describes the innovative design modifications done to meet the seat belt anchorage test. Good correlation with the test is achieved in terms of deformations. These simulation methods helped in reducing the number of intermediate physical tests during the design process.

The present scenario in automobile industry is formed on developing smart vehicles by introducing various feature towards fuel efficient, low emission, weight reduction, and advance safety feature with hybrid and micro-hybrid vehicles. One such feature gaining more popularity is the Belt Driven Starter Generator [1] for its contribution towards fuel efficiency, emission reduction [2], weight reduction and convenient packaging with engine/electrical interface. However this invention puts challenge of integration and increase in loading to various system like power steering pump and crank shaft pulley, as all these systems are interlinked with a common belt. In this interface links we observed the steering pump hub under risk of structural failure due to additional load to support Belt Driven Starter Generator. Failure to identify safe limits of hub load can affect safe vehicle operation [3].

Over the ages of automotive history, expectations of the customers increases vastly starting from driving comfort, better fuel economy and a safe vehicle. Requirement of good vehicle drivability from customers are increasing without any compromise of fuel economy and vehicle features. To enhance the product, it is a must for every OEM’s to have better drivability to fulfill the needs of the customer. This paper explains Objective Drivability Evaluation done on compact SUV vehicle and comparison with subjective drivability. Vehicle manufacturer usually evaluate drivability based on the subjective assessments of experienced test drivers with a sequence of certain maneuvers. In this study, we have used the objective drivability assessment tool AVL drive to obtain the vehicle drivability rating. The vehicle inputs from the accelerometer sensor which captures the longitudinal acceleration and CAN bus signals such as engine speed, vehicle speed, accelerator pedal, are fed into the software.

In any industry, early detection and mitigation of a failure in component is vital for feasible design changes or development iterations or saving money. So it becomes pivotal to capture the failure mode in an accelerated way. This theory poses many challenges in devising the methodology to validate the failure mode. In real world, vehicle head lamp is exposed to all possible kinds of harsh environments such as variable daily ambient, rain, dust and engine compartment temperature …etc. This brings rapid thermal stress onto headlamp resulting into warpage cracks. At vehicle level on particular model, this failure is typically observed after 20,000-25,000 kms in a span of 3-4 months of running. Any corrective action to revalidate the design change or improvement will need similar timelines in regular way to test, which is quite high in product development cycle.

In today's competitive scenario, understanding mental modal map of individual customer perception plays a major role to create the brand image of vehicle. Among them “comfortable sound” is one of the important criteria for customer satisfaction, especially in case of diesel vehicle, where in-cab sound quality plays a crucial factor. Often customer perception concerning comfort in automotive industry relies on subjective comfort evaluation method. Converting the customer perception into objective measurements and to correlate them is often tough task for NVH engineers. It is because of human sensation behavior differs from persons to person, mental map, geographical location and domain knowledge. In addition acoustic & comfort relevant aspects are often subjectively evaluated based on jury trials conducted on the prototype vehicle and class competitive benchmark vehicles to get the feel & confidence of product for different gateways.

The aim is to analyse the various causes of failure of lock clip in Parking Brake Cable which comes out of its place rendering the emergency or the parking brake ineffective and to come up with feasible solutions so that the parking cable doesn't comes out of the rear brake drum.

Batteries have become increasingly important in automotives with increase in vehicle electrical loads. Therefore the reliability of battery is a critical issue in automotive applications. It has been noticed that most batteries have limited cycle durability, that is, the total capacity drops when a battery is charged and discharged for a number of cycles. If a battery is too weak to offer sufficient energy, it should be replaced at the right time. But current problem is that there is no reliable method to quantify the capacity loss and to estimate the remaining capacity of battery. Complete discharge, which is the only way of capacity estimation, which will effect the battery plates therefore it cannot be used too frequently. This paper summarizes the experimental work in the development of the battery status estimation algorithm.

The SAE J1100 based standard cargo volume index methods and predefined luggage objects are very specific to United States population. The European luggage volume calculation and standard luggage calculations are primarily based on DIN and ISO standards. Luggage volume declaration by manufacturers are based on any of these methods. The calculations are complicated and there is a possibility of declaring different values for similar luggage compartments. The major purchase decision of vehicle is based on its luggage capacity and current methods are very limited to make an intelligent decision by a customer. Market specific customer usage patterns for luggage requirements and protecting them in vehicle architecture upfront in concept stage is important to retain the market position and buying preference of customers. The usage patterns is collected from customer clinics and marketing inputs.

Increasing complexity in E/E architecture poses several challenges in developing comfortable, clean and safe cars. This mandates robust processes to mitigate potential hazards due to malfunction of electronic systems throughout the product life cycle. With the advent of ISO 26262 [1] which provides guidelines for developing safe cars, the process is getting standardized towards safer mobility. In this paper, the functional safety process is briefly covered and a case study of Hazard Analysis and Risk Assessment for specific E/E system is presented. An in-house tool developed for functional safety process and management is covered.

Bolted joints are the most used joints in automotive suspension assemblies. They are expected to retain the strength over the course of useful life of the vehicle and contribute to durability in a big way through reduction of stress amplitudes. Any sort of loosening or slip or breakage in these joints can lead to noise or catastrophic failures. In the past, such issues were addressed through thumb rules and design guidelines. However, with the focus on first-time right tests with reduced validation time it has become important to upfront predict the suspension joint integrity through simulation. Toward this objective, a novel approach was developed to simulate the suspension joint integrity for bolted joints. This approach considers various parameters like bolt preload, tolerance stackup of the parts in the joint, coefficients of friction of various interfaces, quality of contact and effect of deformation at the thread interface on joint integrity.

The increasing demand for higher specific power and the need for weight reduction and decrease of emissions have become the driving factors of product development in the automotive market today. Substitution of high-density materials and more precise adjustment of material parameters help in significant weight decrease, but it is accompanied by undesirable cost increase and manufacturing complexity. One of the approaches to optimize the design is through the process of integration which involves integrating the functional elements of two or more components into one and achieving a reduction in weight and cost without impacting required performance. This paper explains a similar approach followed as a part of the Design and Development of 1.5 L, 3 Cylinder CRDI Diesel Engine for a new vehicle platform, developed for automotive passenger car application.

Original Equipment Manufacturers (OEMs) should innovate ways to delight customers by creating affordable products with improved drive experience and occupant comfort. Vehicle refinement is an important initiative that is often take-up by the project teams to ensure that the product meets the customer’s expectations. A few important aspects of vehicle refinement include improving the Noise Vibration Harshness (NVH), ride and handling performance pertaining to the Functional Image (FI) of the product. Optimizing the suspension design variables to meet both ride and handling performance is often challenging as improving the ride will have a deteriorating effect on handling and vice-versa. The present work involves Multi-Objective Design Optimization (MDO) of the suspension system of an automotive Sports Utility Vehicle (SUV) platform considering both ride and handling requirements, simultaneously.

Highly competitive automotive market demands shorter product development cycle while maintaining higher standards of performance in terms of durability and Noise Vibration & Harness (NVH). Engine cranktrain system is one of the major vibration sources in engine and first torsional mode frequency is a key parameter which influences vibration characteristics. Current CAE (Computer Aided Engineering) workflow for evaluating cranktrain system performance is time-consuming and takes around 55 Hrs. It involves crankshaft geometry cleanup, stiffness calculation, 1D model building and post processing. Over the time, significant historical data has been created while performing this virtual simulation during the product development cycle. Having a trained Machine Learning (ML) model based on this historical data, which can predict first torsional mode frequency accelerates the virtual validation. In this paper, prediction of first torsional frequency of cranktrain system using ML is presented.

Modern day automotive market demands shorter time to market. Traditional product development involves design, virtual simulation, testing and launch. Considerable amount of time being spent on virtual validation phase of product development cycle can be saved by implementing machine learning based predictive models for key performance predictions instead of traditional CAE. Durability oil canning loadcase for vehicle hood which impacts outer styling and involves time consuming CAE workflow takes around 11 days to complete analysis at all locations. Historical oil canning CAE results can be used to build ML model and predict key oil canning performances. This enables faster decision making and first-time right design. In this paper, prediction of buckling behaviour and maximum displacement of vehicle hood using ML based predictive model are presented. Key results from past CAE analysis are used for training and validating the predictive model.

Computer Aided Engineering (CAE) simulations are an integral part of the product development process in an automotive industry. The conventional approach involving pre-processing, solving and post-processing is highly time-consuming. Emerging digital technologies such as Machine Learning (ML) can be implemented in early stage of product development cycle to predict key performances without need of traditional CAE. Oil Canning loadcase simulates the displacement and buckling behavior of vehicle outer styling panels. A ML model trained using historical oil canning simulation results can be used to predict the maximum displacement and classify buckling locations. This enables product development team in faster decision making and reduces overall turnaround time. Oil canning FE model features such as stiffness, distance from constraints, etc., are extracted for training database of the ML model. Initially, 32 model features were extracted from the FE model.