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The need for eco-friendly vehicle powertrains has increased drastically in recent years. The most critical component of an electric vehicle is the battery pack/cell. The choice of the appropriate cell directly determines the size, performance, range, life, and cost of the vehicle. Lithium-ion batteries with high energy density and higher cycle life play a crucial role in the progress of the electric vehicle. However, the packaging of lithium-ion cells is expected to meet lots of assembly demands to increase their life and improve their functional safety. Due to their low mechanical stability, the lithium-ion cell modules must have external pressure on the cell surface for improved performance. The cells must be stacked in a compressed condition to exert the desired pressure on the cell surface using compression foam/pads. The compression pads can be either packaged between each cell or once in every set of cells based on the cell assembly requirements.

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.

The side door closing effort is one of the main evaluating parameters which demonstrates the build quality of the vehicle. The side door hinge axis inclination is one of the key attributes that affect the side door closing effort. Commonly, the hinge axis is inclined in two directions of a vehicle to have necessary door rise during the door opening event. Due to the process and assembly variations in the door assembly, the upper and lower hinge axis of the side door deviates from the design axis. In this paper, the deviations in the side door hinge axis and its effects on the side door closing velocity is discussed. The deviations of the side door hinge axis are studied with a coordinate measuring machine. The side door closing velocity of the vehicle is measured with the velocity meter. The study revealed that side door closing velocity is increasing with an increase in the deviation of the top and bottom door hinge axis from the design hinge axis.

In an off-road vehicle, Vehicle Structure plays a major role in passenger safety, Aesthetics, Durability, through a validated construction of canopy structure. This structure is to maintain the shape of the vehicle and to support various loads acting on the vehicle. In present market a safe, Durable, Robust, Waterproof, Noise less, Light weight and cost-effective off-road vehicle will always be a delight for any customer. However, the current conventional way of Soft top vehicle structure use metal brackets and formed sheet parts to create a structure to retain the canopy shape in place. These conventional structures are often heavier and would have many demerits such as heavy weight, Corrosion, Risk of canopy tear due to metallic structure edges and inappropriate draining, water management. Considering this we replaced the heavy metal brackets in to blow molded plastic parts.

Ground clearance plays a vital role in an off-road vehicle during off roading. Higher the ground clearance, higher is the difficulty during ingress & egress of the vehicle. This brings in the necessity to provide entry-assist grab-handles for vehicle with more ground clearance (>200mm). Entry-assist grab handles alleviates the pain of the occupants during ingress and egress. For entry-assist grab handles’ purpose to be served, it should provide comfortable ergonomic grip & have to take the load of passengers while ingress or egress through-out the complete life cycle of the vehicle. Entry Assist grab handles can be fitted on A-Pillar zone to assist first row passengers & on B-pillar zone to assist second row passenger. Providing entry-assist grab handles on pillar trims make the grab-handles exposed to head-impact zone and hence, in most of the cases, it should pass the head impact regulations framed for respective countries.

Accurate ride and handling prediction is an important requirement in today's automobile industry. To achieve the same, it is imperative to have a good estimation of damper model. Conventional methods used for modelling complex vehicle components (like bushings and dampers) are often inadequate to represent behaviour over wide frequency ranges and/or different amplitudes. This is difficult in the part of OEMs to model the physics-based model as the damper’s geometry, material and characteristics property is proprietary to part manufacturer. This is also usually difficult to obtain as a typical data acquisition exercise takes lots of time, cost, and effort. This paper aims to address this problem by predicting the damper force accurately at different velocity/ frequency and amplitude of measured data using Artificial Neural Networks (ANN).

Aerodynamics of on-road vehicles has come to the limelight in the recent years. Better aerodynamic design of vehicle would improve vehicle fuel efficiency with increased acceleration performance. To obtain best aerodynamic body, the series of design modifications and different testing methodologies must be involved in vehicle design and validation phase. Wind tunnel aerodynamic force measurement, road load determination and computational fluid dynamics were the common methods used to evaluate the aerodynamic behavior of the vehicle body. As a novel approach, the present work discusses about the on-road (Real time) testing methodology that is aimed to evaluate the aerodynamic performance of vehicle body using surface pressure mapping. A 64-Channel digital pressure scanner has been utilized in this work for mapping the pressure at different locations of the typical vehicle body.

Air conditioning systems are one of the significant auxiliary loads on the vehicle powertrain. In an Electric Vehicle (EV) where the available energy is limited, it becomes crucial to optimize the overall energy consumption of the auxiliary loads. The major power consuming components in an automotive HVAC system (Heating, Ventilation and Air Conditioning) are: Compressor, Cabin blower, Condenser cooling fan and the Control devices. Significant progress is already made in enhancing the energy efficiency of the above-mentioned power consuming components part of vehicle HVAC system. Alternate energy sources are being explored recently, to reduce the energy demand from vehicle. One such proposal is to harness the abundant solar energy available, through solar panels and consume this energy to supplement the power required for HVAC system components. Solar panels convert solar energy to electrical energy by the principle of the photovoltaic effect.

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.

In present study a comparative investigation and correlation attempted on small scale vehicle model for aerody-namic drag performance at small scale wind tunnel test facility in India vs full vehicle tested at globally know and accepted full scale test facility in Pininfarina, Italy. Current investigation aims to assess the small-scale wind tunnel suitable for testing 1:3 small scale car models A scale model of 1:3 scale size was tested in small scale wind tunnel (at IISC,Bengaluru, India) having test section area of 11.68 Sq. m. To understand the overall vehicle aerodynamic drag performance small scale model was test-ed for different configurations such as baseline, spoiler removal, underbody cover and different yaw condition. To understand the correlation between small scale vs full vehicle’s aerodynamic performance one actual vehicle was also tested at full scale wind tunnel Pinifarina Italy.

Air conditioning systems are one of the significant auxiliary loads on the vehicle powertrain. In an Electric Vehicle (EV) where the available energy is limited, it becomes crucial to optimize the overall energy consumption of the auxiliary loads. The major power consuming components in an automotive HVAC system (Heating, Ventilation and Air Conditioning) are: Compressor, Cabin blower, Condenser cooling fan and the Control devices. Significant progress is already made in enhancing the energy efficiency of the above-mentioned power consuming components part of vehicle HVAC system. Alternate energy sources are being explored recently, to reduce the energy demand from vehicle. One such proposal is to harness the abundant solar energy available, through solar panels and consume this energy to supplement the power required for HVAC system components. Solar panels convert solar energy to electrical energy by the principle of the photovoltaic effect.

Currently the Automotive industry demands highly competitive product to survive in the global tough competition. The engine cooling system plays a vital role in meeting the stringent emission norms and improving the vehicle fuel economy apart from maintaining the operating temperature of engine. The airflow through vehicle subsystems like the grille, bumper, the heat exchangers, the fan and shroud and engine bay are called as front-end flow. Front end flow is crucial factor in engine cooling system as well as in determining the aerodynamic drag of vehicle. The airflow through the engine compartment is determined by the front-end vehicle geometry, the CRFM and CAC package, the engine back restriction and the engine compartment geometry including the inlet and outlet sections. This paper discusses the 1D modelling method for front-end airflow rate prediction and thermal performance by 1D method. The underbody components are stacked using heat stack and simulated in pressure mode.

Design and development of high-pressure pipe involves number of design validation plans for robust design in diesel engine. The fundamental behavior of two-cylinder diesel engine with parallel stroke involves high vibration which generates stress on components mounted on crankcase resulting into earlier fatigue failure. In this paper, the innovative approach of using optimized design of vibration damper for resolving high vibration stress concerns in fuel system is discussed. The vibration dampers were designed meeting both performance and durability aspects in two-cylinder diesel engine applicable for both passenger and commercial vehicle. This paper highlights the design approach involving experimental stress measurements and design optimization based on part development feasibility.

The front air-dam diverts the airflow flowing through the underbody, thereby reducing aerodynamic drag. The height, shape and position of air-dam must be optimized to get improved drag. Extensive iterations are carried out to finalize the front air-dam size and position until the target is achieved. Researchers used to study the effect of air-dam height, then with fixed height will work to finalize position. Studies with interactive effect of front air-dam height and position are scanty. The existing process is time consuming as the front air-dam size and position is adjusted manually and simulation is being performed for each design and requires detailed analysis for all design iterations. The objective of this study is to couple CFD solver with design optimization software to reduce overall manual design iterations to choose the effective front air-dam geometry.

Tractor roll over is the most common farm-related cause of fatalities nowadays. ROPS (Roll-Overprotective Structures) are needed to prevent serious injury and death. It creates a protective zone around the operator when a rollover occurs. In India the ROPS is getting mandatory across all HP ranges except narrow track. In the present study states the customized ROPS application for configurable design such as Automated safety zone for all homologation standards, ROPS A0-D excel calculator for selection of material at concept stage and bolt calculator for selection of size. For the above applications below aspects need to consider such as Tractor weight, Rear housing mounting, Operator seat index position (SIP), Seat reference points (SRP) and all ROPS homologation standards. This ROPS application is to reduce the timeline, manual error and ensure the reliability of the modular optimal design for various platforms and variants.

In recent times, Battery electric vehicles (BEV) have gained a lot of popularity since they can contribute immensely to control the urban air pollution. However, to consider the BEVs as a sustainable mobility solution, a significant improvement is needed in several aspects including performance, range, cost, weight and recharging time. In the present work, the acceleration performance of an electric vehicle is improved to match with its diesel variant by optimizing the accelerator pedal map strategy. Due to weight and cost constraints, the battery and electric machine capacity of the electric variant of the vehicle was considerably lower (41 % lesser power and 44% lesser torque). However, the expectation from the customers is to have no noticeable difference in the low-end performance feel between the variants.

This paper presents a comprehensive model of a hydraulic power steering system for predicting the transient responses under various steering inputs. The hydraulic system model, which integrates together all fluid line elements and hydraulic components, is formulated using the MSC Easy5 software. A full vehicle model is developed in ADAMS/Car. Functional Mock up Interface (FMI), a tool independent standard is used for co-simulation of ADAMS and Easy5 Dynamic models. This paper describes a co-simulation methodology developed using FMI interface for full vehicle Simulations using hydraulic power steering. A virtual simulation scheme is developed to obtain the system transient responses and the results are compared with those measured from the tests. In general, the simulation results agree with those obtained from the tests under the same steering inputs and operating conditions.

Objective metrics for performance evaluation of ride, handling and steering are required to compare, validate and optimize dynamic behavior of vehicles. Some of these objective metrics are recommended and defined by International Organization for Standardization (ISO) and Society of Automotive Engineers (SAE), which involve data processing, statistical analysis and complex mathematical operations on acquired data through simulation or experimental testing. Due to the complexity of operations and volume of data, evaluation is often time consuming and tedious. Process automation using existing tools such as MS Excel, nCode, Siemens LMS, etc. includes several limitations and challenges, which make it cumbersome to implement. This work is about development of a centralized platform for quantification, visualization and comparison of ride, handling and steering performance metrics obtained from testing and simulation data as per relevant ISO standards.

The automotive industries around the world is undergoing massive transformation towards identifying technological capabilities to improve vehicle performance. In this regard, the engine dynamic torque plays a crucial role in defining the transient performance and drivability of a vehicle. Moreover, the dynamic torque is used as a visualization parameter in performance prediction of a vehicle to set the right engineering targets and to assess the engine potential. Hence, an accurate measurement and prediction of the engine dynamic torque is required. However, there are very few methodologies available to measure the engine dynamic torque with reasonable accuracy and minimum efforts. The measurement of engine brake torque using a torque transducer is one of the potential methods. However, it requires a lot of effort and time to instrument the vehicle. It is also possible to back-calculate the engine torque based on fuel injection quantity and other known engine parameters.

A four-wheeled automobile during braking event in which left and right wheels of the vehicle are on different mu surfaces, has high chances of experiencing spin, which may lead to stability issues on vehicle. This paper intends to provide a mathematical approach to predict the deceleration at which vehicle will spin during braking in a differential mu surface, and determine the effect of influencing parameters on the extent of the vehicle spin tendency. This paper also provides a correlation between theoretical vs actual decelerations for vehicles to exhibit vehicle spin tendency. This paper helps in providing sufficient aid/tool for system designer to predetermine the vehicle spin at early level of system designs and make necessary amendments at initial stage of prototype development rather than late changes, to create a product which gives safe driving experience.