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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.

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.

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.

Drive cycles have been an integral part of emission tests and virtual simulations for decades. A drive cycle is a representation of running behavior of a typical vehicle, involving the drive pattern, road characteristics and traffic characteristics. Drive cycles are typically used to assess vehicle performance parameters, perform system sizing and perform accelerated testing on a test bed or a virtual test environment, hence reducing the expenses on road tests. This study is an attempt to design a relatively robust process to generate a real world drive cycle. It is based on a Six Sigma design approach which utilizes data acquired from real world road trials. It explicitly describes the process of generating a drive cycle which closely represents the real world road drive scenario. The study also focuses on validation of the process by simulation and statistical analysis.

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.

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.

The tractor usage is growing in the world due to derivative of rural economy and farming process. It needed wide range of implements based on the applications of the customer. The tractor plays a major role in Agricultural and Construction applications. In a tractor, hydraulic system is act as a heart of the vehicle which controls the draft and position of the implement. Hydraulic system consists of Powertrain assembly, 3-point linkage and DC sensing assembly. The design of hydraulic powertrain assembly is challenging because the loads acting on the system varies based on the type of implement, type of crop, stage of farming and soil conditions etc., Hydraulic powertrain assembly is designed based on standards like IS 12207-2019 which regulates the test methods for the system based on the lift capacity of the tractor. In this paper, virtual simulation has been established to optimize the design and perform the test correlation.

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.

In farm tractors, front end loaders are becoming popular attachments for primarily material handling such as loading, moving and unloading of woodchips, sand, gravels etc. It is also used for some severe load application such as tree uprooting and ripping operation which requires validation of loader frame and tractor as well. To validate the design, a standard pull-push test is carried out on tractor with loader in a laboratory. In this test front loader bucket is pushed against a rigidly clamped fixture with full engine throttle and maximum hydraulic cylinder pressure of loader. To avoid surprise failures during the test, a virtual simulation method needs to be developed and validated. In this paper, a method has been proposed by authors for the above objective. A multi-body dynamics model of tractor with loader is created in MSC ADAMS and actual event is simulated using test loads & boundary conditions.

Connected vehicles technology is experiencing a boom across the globe. Vehicle manufacturers have started using telematics devices which leverage mobile connectivity to pool the data. Though the primary purpose of the telematics devices is location tracking, the additional vehicle information gathered through the devices can bring in much more insights about the vehicles and its working condition. Cloud computing is one of the major enabled for connected vehicles and its data-driven solutions. On the other hand, machine learning and data analytics enable a rich customer experience understanding different inferences from the available data. From a fleet owner perspective, the revenue and the maintenance costs are directly related to the usage conditions of the vehicle. Usage information like load condition could help in efficient vehicle planning, drive mode selection and proactive maintenance [1].

Across the automotive industries, objective measurements and subjective assessment of vehicle ride performance are routinely carried out during development as well as validation phase. Objective measurements are receiving increased attention as they are generally believed to offer a higher degree of objectivity and repeatability compared to the subjective assessment alone. Typical industry practices include the acquisition of vehicle-occupant vibrational response on specified road sections, test surfaces on proving grounds or in a controlled input environment such as four-poster test rig. In presented work, a study is performed on the repeatability of vehicle ride performance metrics such as weighted RMS acceleration and frequency responses using the data acquired in repeated trials conducted using three different sports utility vehicles (SUVs) on a sufficiently long designated road section.

Steering returnability while driving is one of the most important parameter which affects the drive pleasure and handling of a vehicle. Steering returnability refers to the automatic returning response of the steering wheel after taking a full turn while vehicle is being steered during driving. Evaluating steering response characteristics of any vehicle in a virtual environment at early stage of a product development saves significant development time and cost. Through this paper an attempt has been made to develop a methodology for selection of suspension hard points which influences steering returnability characteristics of a vehicle at an early product design stage. Conventionally, suspension kinematic parameters such as Caster angle, Steering axis inclination (SAI), etc. are iterated during vehicle design stage to achieve desired Steering returnability.

Vehicle lateral dynamic response parameters such as yaw velocity, lateral acceleration, roll angle, etc. depend on the nature of steering input. Response parameters vary with the amplitude and frequency of steering input. This paper deals with developing insights into the effect of steering input frequency on transient handling dynamics. For the purpose two SUV segment vehicles with similar curb weight are considered. Vehicles are given pulse inputs of the amplitudes corresponding to 4 m/s2 steady state lateral acceleration and target speeds of 80 kmph and 100 kmph, as recommended in ISO 7401:2011. Steering inputs are executed using a Steering Robot (ABD SR30). Lateral transient dynamic response gains as well as natural frequencies of yaw are studied for 0-2 Hz input frequencies. Several insights are developed, adding to the understanding of transient lateral dynamics and its relationship with steering input.

Body in White (BIW) is one of the critical aggregates of an automobile. Establishing the quality parameters during body manufacturing is essential to achieve robust BIW structure. Spot weld integrity and dimensional accuracy are the two major quality parameters of a BIW. Weld integrity plays an important role in achieving dimensional accuracy and structural stability. Various combinations of sheet metals are joined together to form a BIW structure. Spot weld parameter selection is one of the critical activity and needs to be programmed for the various combinations of sheet metals. Weld parameter for the various combinations are calculated with the resistance of the joining sheet metals thicknesses. The calculated parameters are validated with the coupon test (or) peel test and it requires several iterations to establish weld integrity of the different combinations and the selected parameters get registered in the weld controller.

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.

Tractor weight transfer is the most common farm-related cause of fatalities nowadays. As in India it is getting mandatory for all safety devices across all HP ranges. Considering any changes in the weight from an attachment such as Rops, PTO device, tow hook and draw bar etc. can shift the center of gravity towards the weight. center of gravity is higher on a tractor because the tractor needs to be higher in order to complete operations over crops and rough terrain. Terrains, attachments, weights, and speeds can change the tractor’s resistance to turning over. This center of gravity placement disperses the weight so that 30 percent of the tractor’s weight is on the front axle and 70 percent is on the rear axle for two-wheel drive propelled tractors and it must remain within the tractor’s stability baseline for the tractor to remain in an upright position.