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With the increase in the number of automobiles on road, there is a very strong emphasis on reducing the air pollution which led to evolution of stringent emission norms. To meet these stringent emission norms, the ideal solution is to optimize the engine hardware and the combustion system to reduce the emission at source thereby reducing the dependency on exhaust after treatment system. Gasoline Direct Injection (GDI) engines are gaining popularity worldwide as they provide a balance between fun to drive and fuel efficiency. Controlling the particle emissions especially Particle Number (PN) is a challenge in GDI engines due to the nature of its combustion system. In this study, experiments were performed on a 1.2Litre 3-cylinder 250bar GDI engine to capture the effect of injection strategies on PN.

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.

Fuel efficiency is critical aspect for commercial vehicles as fuel is major part of operational costs. To complicate scenario further, fuel efficiency testing, unlike in passenger cars is more time consuming and laborious. Thus, to save on development cost and save time in actual testing, simulations plays crucial role. Typically, actual vehicle speed and gear usage is captured using reference vehicle in desired route and used it for simulation of target vehicle. Limitation to this approach is captured duty cycle is specific to powertrain and driver behavior of reference vehicle. Any change in powertrain or vehicle resistance or driver of target vehicle will alter duty cycle and hence duty cycle of reference vehicle is no more valid for simulation assessment. This paper demonstrates approach which uses combination of tools to address this challenge. Simulation approach proposed here have three parts.

In the conceptualization phase of vehicle development, for achieving reasonable dynamics performance, proper selection of steering system meeting all the requirements is necessary. This requires accurate prediction of major steering performance attributes like steering effort, steering torque, Turning Circle Diameter (TCD), %Ackerman and steering returnability. However, currently available models majorly depend on Computer Aided Engineering (CAE)-analysis or physical trials which requires system detailing and the same cannot be used for early prediction of the steering performances in the concept phase. This paper aims to address this deficiency with the help of a new steering performance calculator. In the calculator, performance attributes namely steering effort, steering torque, TCD and %-Ackerman has been modelled with engineering calculations and other attributes namely steering returnability&precision has been modelled through machine learning techniques.

The given paper presents the main elements of frictional power loss distribution in an automotive axle for passenger car. For reference two different axles were compared of two different sizes to understand the impact of size and ratio of gear and bearings on power loss characteristics. It was observed that ~50% of total axle power loss is because of pinion head-tail bearing and its seals, which is very significant. Roughly 30% of total power loss is contributed by pinion-ring gear pair and differential bearings and remaining ~20% by wheel end bearing and seals. With this study the automotive companies can take note of the area where they need to focus more to reduce their CO2 emissions to meet the stringent BS6, CAFÉ and RDE emission norms.

During the cold start conditions engine must overcome higher friction loss, at the cost of fuel penalty till the optimum temperatures are reached in coolant and lubrication circuits. The lower thermal capacity of the lubrication oil (with respect to the coolant) inverses the relation of viscosity with temperature, improves engine thermal efficiency benefit. Engine oil takes full NEDC test cycle duration to reach 90°C. This leads to higher friction loss throughout the test cycle, contributing a significant increase in fuel consumption. Increasing oil temperature reduces viscosity, thereby reducing the engine friction. This helps to identify the focus for thermal management in the direction of speeding up the temperature rise during a cold engine starting. This work aims at the study and experiment of an exhaust recovery mechanism to improve the NEDC fuel economy.

In current scenario, virtual validation is one of the important phase for any new product development process. The initial step for virtual validation for durability analysis of vehicle is to understand the loads which are transmitted to body from the roads. In current methodology standard 3g load cases are considered. These are worst load cases which show more number of high stress locations on vehicle. In actual vehicle running condition, dynamic loads are coming on vehicle structure. These dynamic loads can be obtained by measuring the loads coming on the vehicle through road load data acquisition system. The use of measured loads posed challenges due to the non-availability of representative mule in the initial phase of vehicle development. To overcome these challenges, Mahindra & Mahindra developed a new approach which enabled the direct substitution of analytically synthesized loads for measured data.

High speed diesel engines are difficult to start in cold conditions (at subzero temperature) because the cylinder head and cylinder block absorbs heat of compression and thus preventing ignition due to the high surface to volume ratio. Also the coolant and the engine oil become viscous at subzero temperature and make the condition unfavorable for starting. Combustion optimization along with the help of a heating aid can make these engines to start quickly without any engine misbehavior. Cold startability is the ability of an engine to start within a specified time and continue to run without any malfunctioning. Combustion instability will lead to the misfiring of the engine unless it is calibrated properly. The European countries are subjected to a minimum temperature of -20°C to -25°C. So the intention of this work is to optimize the cold startability of Mahindra's Multi-Purpose Vehicle (MPV) up to -25°C which is to be sold in European countries.

The Ride Comfort has always been an important attribute of a vehicle that gets trade-off with handling characteristics of a vehicle. However, to cater the growing customer requirements for better ride comfort in a vehicle without compromising on other attributes, evaluating and achieving optimal ride comfort has become a significant process in the vehicle development. In the current engineering capability and virtual engineering simulations, creating an accurate and real time model to predict ride comfort of a vehicle is a challenging task. The qualitative evaluation of ride attributes has always been the proven conventional method to finalize the requirements of a vehicle. However, quantitative evaluation of vehicle ride characteristics benefits in terms of target setting during vehicle development process and in robust validation of the final intended product against its specifications.

This paper details about the approach and challenges in converting a conventional vehicle platform designed for diesel/gasoline powertrain into an electrified one. It is not always feasible to accommodate electric powertrain in conventional platforms based on the target requirements. Electrification of conventional vehicles will cut back dependence on fossil fuels, emission of greenhouse gases and emission of pollutants. Fossil fuel are going to be depleted in few decades. Moreover, the emission from traditional vehicle has raised a huge threat to the atmosphere. Auto OEM’s have recognized that electric drive vehicles are critical to the future of the industry. However, some difficulties exist to more noteworthy selection: the view of cost, EV range, access to charging, potential impacts, and absence of open mindfulness about the accessibility and common sense of these vehicles.

This paper details the methodology used to show the importance of Low rolling resistance tires in Electric Vehicles. Fuel efficiency and range is paramount with most of the electric vehicle buyers. Although many people are now becoming aware of low rolling resistance tires but its development started way back in 1990’s. It is always challenging to achieve low rolling resistance in smaller tires of size 12 inch or 13 inch along meeting the other critical vehicle parameters such as ride and handling, NVH, durability and many more. The reduction in rolling resistance can also affect the traction properties of tires. In case of very low rolling resistance tires the traction will be very less but it can badly affect the other vehicle parameters. Selection of tires further depend upon the RWUP (Real World Usage Profile). It means the vehicle is targeted for which region and what is the condition of roads there.

Indian Automobile Industry has started using Six Sigma for Vehicle Design and process improvement to compete with Global competition. This Paper describes how the Tools of Six Sigma shall be used as an Effective Tool for both redefining the Design and the Process Improvement. This Paper talks on the evolution of DMADV approach in Indian Automobile Industry compared to the related Trends in Other Manufacturing Sectors. The Author describes how the warranty failures in Commercial Segment Vehicle Category which was the selling talk for the Competition was addressed in Leading Indian Automobile OEM. As this Failure was adversely impacting customer satisfaction and no solution seemed forthcoming, top Management indicated to use a radically different approach to solve the problem within a years’ time.

Digital human models (DHM) have greatly enhanced design for the automotive environment. The major advantage of the DHMs today is their ability to quickly test a broad range of the population within specific design parameters. The need to create expensive prototypes and run time consuming clinics can be significantly reduced. However, while the anthropometric databases within these models are comprehensive, the ability to position the manikin’s posture is limited and needs lot of optimization. This study enhances the occupant postures and their seating positions, in all instances the occupant was instructed to adjust to the vehicle parameters so they were in their most comfortable position. While all the Occupants are accommodated to their respective positions which finally can be stacked up for space assessments. This paper aims at simulating those scenarios for different percentiles / population which will further aid in decision making for critical parameters.

Plenum is the part located between the front windshield and the bonnet of an automobile . It is primarily used as an air inlet to the HVAC during fresh air mode operation. It’s secondary functions include water drainage, aesthetic cover to hide the gap between windshield to bonnet, concealing wiper motors and mechanisms etc. The plenum consists mainly two sub parts viz. upper plenum and lower plenum. Conventional plenum design which is found in majority of global OEMs employ a plastic upper plenum and a metal lower plenum which spans across the entire width of engine compartment. This conventional lower plenum is bulky, consumes more packaging space and has more weight. In this paper, we propose a novel design for the plenum lower to overcome above mentioned limitations of the conventional design. This novel design employs a dry and wet box concept for its working and is made up of complete plastic material.

Turbocharged common rail direct injection engines offer multiple benefits compared to their naturally aspirated counterparts by allowing for a significant increase in the power and torque output, while simultaneously improving the specific fuel consumption and smoke. They also make it possible for the engine to operate at a leaner air/fuel mixture ratio, thereby reducing particulate matter emission and permitting higher EGR flow rates. In the present work, a two cylinder, naturally aspirated common rail injected engine for use on a load carrier platform has been fitted with a turbocharger for improving the power and torque output, so that the engine can be used in a vehicle with a higher kerb weight. The basic architecture and hardware remain unchanged between the naturally aspirated and turbocharged versions. A fixed geometry, waste gated turbocharger with intercooling is used.

Technology is one of the key determinants of the outcome in today's wars. Many targeting systems today use infra-red imaging as a means of acquiring targets when ambient light is insufficient for optical systems. Reducing thermal signatures offers an obvious tactical advantage in such a scenario. One way to reduce thermal emission of combat vehicles is to adopt highly efficient electrical power trains instead of internal combustion engines that tend to reject a sizeable amount of the input energy as heat. The tractor is one of the most versatile vehicles that are used in the theatre of combat for various operations such as haulage, clearing terrain, deploying bridges, digging trenches etc due to its excellent abilities in handling difficult terrain. A tractor powered by an all-electric power train was developed for civilian applications. The traction characteristics are identical to that of a conventional diesel powered tractor of comparable size.

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 Micro-hybrid technology otherwise called as stop start system offers a significant improvement in fuel economy particularly in urban driving conditions, where more often the engine idles unnecessarily at traffic signals/jams. Micro-hybrid technology stops the engine at traffic signals/jams and starts the engine automatically on clearance of traffic signals/jams leading to reduced fuel consumption and emissions. This is achieved by monitoring several vehicle and engine parameters through appropriate sensing elements. In this study, the system architecture and functional definitions of start/stop system is defined. Equivalence class, boundary value and decision-table testing are used to generate test cases. On generation of test cases, their relevance on on-road robustness and scope for optimization towards time/efforts are analyzed. In the process, a matrix of different conditions and criteria are formulated. Under these conditions, the system behavior is evaluated.