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Air suspension systems had been introduced in automobiles since 1950s. These systems are being explored to improve the ride comfort, handling stability and also serve as a medium for better cargo protection. These system are well developed for buses and high end passenger sedans, also have feasibility for adapting for wide range of configurations of suspension system and axle. Passenger cars and Sports Utility Vehicle (SUV) pickup category of vehicle offers different challenges such as space availability, spring selection and characterization that need to be addressed for successful implementation of air suspension in these category vehicles. This work defines methodology to implement air suspension system in SUV Pickup category vehicle. Paper work includes concept study, mathematical co-relation, and prediction of air spring characteristics and integration of experimental and analytical tool for development of air suspension system.

Forging is a metal forming process involving shaping of metal by the application of compressive forces using hammer or press. Forging load of equipment is an important function of forging process and the prediction of the same is essential for selection of appropriate equipment. In this study a hot forging material i.e. 42CrMo4 steel is selected which is used in automotive components like axle, crank shaft. Hot forging experiments at 750°C are carried out on cylindrical specimens of aspect ratio 0.75 and 1.5 with true height strain (ln (ho/hf)) of 0.6. Forging load for the experiments is calculated using slab and upper bound deformation models as well as Metal forming simulation using commercially available FEA software. The upper bound models with 30% deviation from the simulation results are found to be more accurate compared to the slab models.

Now-a-days, Advanced driver-assistance systems (ADAS) is equipping cars and drivers with advance information and technology to make them become aware of the environment and handle potential situations in better way semi-autonomously. High-quality training and test data is essential in the development and validation of ADAS systems which lay the foundation for autonomous driving technology. ADAS uses the technology like radar, vision and combinations of various sensors including LIDAR to automatize dynamic driving tasks like steering, braking, and acceleration of vehicle for controlled and safe driving. And to integrate these advance technologies, the ADAS needs labeled data to train the algorithm to detect the various objects and moments of driver. Image annotation is one the well-known service to create such training data for computer vision. There are number of open source annotated datasets available viz. COCO, KITTI etc.

In year 2015, 17 people were killed every hour by road accidents in India [1]. The occurrence of road accidents is observed to be higher during night, when visibility is at its lowest. The two factors which affect visibility are insufficient illumination and glare caused by the oncoming traffic. The Adaptive Front Lighting System [AFS] is an active safety feature which addresses these problems by employing specific lighting modes for Town, Country, Expressway conditions and automatic switching between Driving Beam and Passing Beam whenever required. Matrix of LEDs or a Projector with an actuator or a combination of both is employed in achieving different Lighting modes. The projector based AFS module is preferred for implementing the AFS control logic for passing beam owing to its economic cost.

The Indian government has been promoting electric vehicles through various policy initiatives, such as offering incentives and subsidies to EV manufacturers and consumers, establishing charging infrastructure across the country, and setting ambitious targets for EV adoption. These measures aim to reduce the dependence on imported fossil fuels, mitigate air pollution, and promote sustainable mobility. As a result, the demand for electric vehicles across India is steadily increasing, and the country is emerging as a lucrative market for EVs globally. An electronically commuted brushless DC (BLDC) motor usually functions for traction in electric two-wheelers. Electric vehicles need to comply with electromagnetic compatibility (EMC) requirements. During the EMC compliance of electric two-wheelers, it is certain that the BLDC motor and its controller play an important role.

A bus is integral part of public transportation in both rural and urban areas. It is also used for scheduled transport, tourism, and school transport. Buses are the common mode of transport all over the world. The growth in economy, the electrification of public transport, demand in shared transport, etc., is leading to a surge in the demand for buses and accelerating the overall growth of the bus industry. With the increased number of buses, the issue of safety of passengers and the crew assumes special importance. The comfort of driver and passenger in the vehicle involves the vibration performance and therefore, the structural integrity of buses is critically important. Bus safety act depicts the safety and comfort of bus operations, management of safety risks, continuous improvement in bus safety management, public confidence in the safety of bus transport, appropriate stakeholder involvement and the existence of a safety culture among bus service providers.

The Indian automotive industry is striving towards more safe and durable vehicles. A need was felt to study the effect of changes in axle static loads on fatigue life of the axle components. Also, there was a need to develop generic test method, as there are no test standards or generic methods available in public domain for fatigue testing of commercial vehicle axles. The study was carried out to check direct effect of change in axle loads on various connections on axle, effect of suspension configuration and force distribution, Vehicle dynamics, etc. In this paper, an India specific generic load spectra was evaluated for accelerated laboratory validation. Paper discusses the methodology as; study of heavy commercial vehicle systems, road load data collection on identified test vehicles w.r.t. test matrix finalized, India specific test loads and load spectra development, normalization of axle load spectra w.r.t to static axle weights and arriving at test guidelines.

The Construction & Mining field is continuously upgrading, reshaping under the stimulus of technical enhancement. India is considered one of fastest growing country in the word. Requirement for Construction Equipment Vehicles in India is continuously growing due increased rate infrastructure development. To promote development of the Construction Equipment Vehicles (CEV’s) manufacturing sector it was also necessary to build a new governance architecture. Every vehicle plying on road has to comply with Central Motor Vehicle Regulatory requirements as per CMVR act 1989. Earlier 2021 CEV’s were required to go through performance trials like brake, steering effort, turning circle measurement, speedometer calibration as dynamic tests as per regulations.

Design of vehicle for targeted customer usage is one of the key steps during vehicle development process. Due to globalization, most of vehicles, aggregates, components are being designed for global market considering worldwide load spectrum. Generally for doing this the vehicle response is being measured for different markets but this process is very time consuming. Also for getting these vehicle dependent parameters, exercises need to be repeated on each type/class of vehicle. So there is a need to have a robust procedure, tools which will helps OEM’s to predict the loads, vehicle response for different market segments at an early stage of vehicle development program using the inputs which are vehicle independent. The solution for this could be to use vehicle independent input such as digitized road profiles (2D or 3D) of target customer markets in combination with proper MBD simulation tools.