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Ride is considered to be one of the crucial criterion for evaluating the performance of a vehicle. Automobile industry is striving for improvement in designs to provide superior passenger comfort in Commercial vehicles segment. In Industry, Quarter-car model has been used for years to study the vehicle’s ride dynamics. But due to lower DOF involved in quarter car, the output accuracy is somewhat compromised. This paper aims in development of a 7 DOF full-car Model to perform the ride- comfort analysis for Light Duty 4*2 Commercial Bus using MATLAB Simulink which can be used to tune the suspension design to meet the required ride-comfort criteria. Firstly, experimental data and Physical Parameters are collected by performing Practical Test on commercial Bus on different road profiles. Secondly, a Full Car Mathematical Model with 7 DOF has been developed for a bus using MATLAB Simulink R2018a.

Last decade has been era of environmental awareness. Various programs have launched for making devices and appliances eco-friendly. This initiative has lead automobile industry toward hybridization and now total electrification of vehicles. As electric motor is being added to automobile as a prime mover, due to high frequency vibrations along with higher torque electric motor needs to be isolated properly & carefully as this vibration can damage other automobile parts. Dynamic response of electric motor is different from response of IC engines, so use of engine mounting design method may not be suitable for designing mounting system for electric motor. First, both 4- point and 3- point mounting system are considered for analytical and experimental investigation of force and displacement transmissibility. Position and orientation of elastomeric mounts plays important role in design of mounting system for electric motor.

Design of real time active controls for structural dynamics problems requires a very precise mathematical model, to closely determine the system dynamic behavior, under virtual simulation. The finite element models can somehow be used as a mathematical model but due to complex shape/structure of the component, the size of discrete models resulting from finite element analysis is usually very large, causing the virtual simulation to be extremely computationally intensive and time consuming, also the boundary conditions applied are not very scalable, making the system deviate from its real dynamic behavior. Thus, this paper deals with the design of a Model Order Reduction technique, using orthogonal decomposition of system matrices, which can be used for creating accurate low-order dynamic model with scalable boundary conditions.

Passive safety regulations specify minimum safety performance requirements of vehicle in terms of protecting its occupants and other road users in accident scenarios. Currently for majority cases, the compliance of vehicle design to passive safety regulations is assessed through physical testing. With increased number of products and more comprehensive passive safety requirements, the complexity of certification is getting challenged due to high cost involved in prototype parts and the market pressures for early product introduction through reduced product development timelines. One of the ways for addressing this challenge is to promote CAE based certification of vehicle designs for regulatory compliance. Since accuracy of CAE predictions have improved over a period of time, such an approach is accepted for few regulations like ECE-R 66/01, AIS069 etc which involves only loadings of the structures.

This work aims at demonstrating nodes and antinodes at various frequencies of vibrations. Chladni plate is used for this purpose. When the plate is excited because of vibrations from a vibrator source, the sand of the plate creates specific patterns. These patterns are related to the excitation frequency. The sand on the plate moves away from antinodes where the amplitude of the standing wave is maximum and towards nodal lines where the amplitude is minimum or zero, forming patterns known as Chladni figures. The formation of patterns depends on material properties, geometry of plate, and thickness of plate and frequency/vibration pattern of the vibrator. The experimental setup consisted of a aluminum rectangular plate of 16 cm × 16 cm and aluminum circular plate of diameter 16 cm are having thickness of 0.61 mm placed over a mechanical vibrator (GelsonLab HSPW-003), which was driven by a sine wave signal generator (Ningbo Hema scientific).

The paper discusses the methodology for measuring the sound absorption of sound package materials in a different sizes of reverberation chambers. The large reverberation chamber is based on test methods and requirements as per ASTM C423 and ISO 354 standards. Both the test standards are similar and recommend a reverberation chamber volume of at least 125 m3 and 200 m3 respectively for sound absorption measurements from 100 Hz to 5000 Hz. The test sample size requirements are from 5.5 to 6.7 m2 as per ASTM C423 and 10 to 12 m2 as per ISO 354. In the automotive sector passenger car, heavy truck, and commercial vehicle, the parts that are used are much smaller in size than the size prescribed in both the standards. The requirement is to study the critical parameters such as the chamber volume, sample size, reverberation time and cut-off frequency etc. which are affecting the sound absorption property of acoustic material.

In order to reduce development time and costs, application of numerical prediction techniques has become common practice in the automotive industry. Among the wide range of simulation applications, prediction of the vehicle interior noise is still one of the most challenging ones. The Finite Element Method (FEM) is well known for acoustic predictions in the low-frequency range. As part of the development of a full sized bus model, noise levels at Driver Ear Levels (DEL) and Passenger Ear Levels (PEL) were targeted. The structural and acoustic analysis were performed for a bus to reduce interior noise in the low-frequency range. Various counter measures were identified and structural optimization/modifications were performed from virtual simulation to reduce the DEL and PEL. Structure-borne noise due to both road-induced vibration and engine vibration were considered by using FEM techniques.

In today’s scenario, the emission norms are getting stringent day by day due to an increased level of pollution. The world is shifting towards low carbon footprint which made it necessary to adopt efficient technologies with fewer emissions. The hybridization of vehicles has resulted in improved efficiency with lower emissions which can fulfil the near future emission norms. Retrofitting of hybrid components into a conventional IC engine vehicle is so far the best way to achieve better performance both economically and technologically. This research is primarily focused on the design and development of a novel retrofit solution of P3x architecture for the light commercial vehicle. This retrofit solution is different from other hybrid solutions in terms of powertrain. It contains an innovative add-on powertrain along with the existing powertrain. This additional powertrain consists of a pair of helical gears followed by a chain and sprocket as a coupler for traction motor.

The increasing in popularity of Light Commercial Vehicles (LCV) segment is an emerging trend in the commercial vehicle industry. LCVs are very efficient and cost-effective for transportation of materials and good on short distances or loads of lesser weights. Sensing the market potential, many auto companies have developed LCVs recently. Since LCV segment is price sensitive, low cost single cylinder water cooled diesel engine being used as prime mover. High noise & vibration is inherent feature of diesel engine & it is predominant in single cylinder diesel engine. In order to retain low cost of product, less attention is given on overall noise of vehicle. Also, it is challenging to meet the regulatory limits of Pass-by Noise (PBN) for this category of vehicle. This paper is a development work done for pass-by noise reduction of a diesel powered single cylinder LCV vehicle. A prototype vehicle needs to meet the legislative pass-by noise requirement when tested as per IS0 362 / IS 3028.

Designers and analysts need to compare and conduct synthesis for selection of materials based on their properties involving simulation, optimization and correlation with test data. An example is that of acoustic material properties such as random and normal incidence sound absorption coefficient and sound transmission loss. The international test standards necessitate having standard operating procedures for characterization of these materials. This procedure is quite involved and addresses steps including test data acquisition, post processing, calculations, classification, report generation and most importantly, storage of such innumerable material properties in a structured manner to facilitate ease of retrieval and updating of properties. It is also highly desirable to have a synergy of the databank directly with simulation tools. Further, all of these steps need to be accurate, non-speculative and quick.

Active control mainly comprises of three parts; sensor-detects the input disturbance, actuator -provide counter measures and control logic -processing of input disturbances and converting it into logical output. Lot of methods for active vibration control are available but this paper deals with active control of steering wheel vibrations of an LCV. A steering wheel is, one such component that directly transfers vibration to the driver. Active technique described here is implemented using accelerometer sensor, IMA (Inertial Mass Actuator) and feed forward Fx-LMS (Filtered reference Least Mean Square) control algorithm. IMA is a single-degree-of-freedom oscillator. To enable a control, IMA needs to be coupled to the structure at a single point, acting as an add-on to the passive system. Fx-LMS is a type of adaptive algorithm which is computationally simple and it also includes compensation for secondary path effects by using an estimate of the secondary path.

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.

On-board diagnostics (OBD) is a term referring to a vehicle's self-diagnostic and reporting capability. It is a system originally designed to reduce emissions by monitoring the performance of major emission related components. There are two kinds of on-board diagnostic systems: OBD-I and OBD-II. In India OBD I was implemented from April 2010 for BS IV vehicles. OBD II was implemented from April 2013 for BS IV vehicles. Apart from the comprehensive component monitors, OBD II system also has noncontinuous monitors like Catalyst monitoring, Lambda monitoring, and other after treatment system monitors. For OBD II verification and Validation, it is required to test all the sensors and actuators that are present in the engine, for all possible failures. From an emissions point of view there are lists of critical failures that are caused due to malfunction of sensors and actuators. Carrying out the full matrix failure testing on the running engine could be tedious, unsafe and time consuming.

This project was undertaken with an objective to develop methodology by formulating set of procedures that would help in achieving the end goal. Once methodology is established, it paves way to optimize the end results more effectively which results in reduced lead time during product development. Methodology can either be based on pure experimental investigations or by simulations. Combination of mathematical and empirical approach is inherently followed in simulations, which helps in reducing the testing time and overall cost. Commercial vehicles (CV) have seen paradigm shift in the fuel consumption (FC) certification approaches, with an intention to align with 2016 Paris climate agreement. Use of simulation tool like VECTO for commercial vehicle FC certification has gained momentum in Europe. Overall experience gained in commercial vehicle FC simulation has motivated us to leverage the learnings for off-road applications like agricultural tractors.

The Light commercial vehicle (LCV) is primarily used for the last mile delivery and it hold the volume share of around 61% in the commercial vehicle segment. The last mile delivery services have seen a massive surge after the CoVID 19 pandemic resulting is the increase sale of LCV in last few years and is expected to grow further by 8-11% in the coming years. However, city logistic is also responsible for most pollution and noise in the city. Hence, policymakers are aiming to reduce carbon footprint by promoting the use of Electric vehicle by providing incentive to automakers though schemes like FAME I and FAME II. In order to effectively reduce the carbon footprint within city it is important to increase the use of new electric vehicle and convert the old polluting vehicles to electric. Hence, a retro fitment solution for converting used LCV to electric can help in reducing emission as well as noise pollution. Later the same solution can be offered as OE fitment solution.

Advanced Driver Assistance Systems (ADAS) play a crucial role in enhancing road safety by providing intelligent assistance to drivers. To ensure the reliability and effectiveness of ADAS functions, rigorous verification and validation processes are necessary. One critical aspect of this process is scenario generation, which involves creating diverse and representative driving scenarios for testing and evaluating ADAS functions. This paper proposes a novel approach for synthetic scenario generation specifically tailored for Indian road conditions. The approach leverages real-time road data collected from various sources, including camera sensors, Lidar sensor, GPS devices, and traffic monitoring systems. The collected data is processed and analyzed to extract relevant information, such as road geometries, traffic patterns, and environmental conditions.

One of the primary reasons for road accidents is driving while distracted or drowsy. Often, long and monotonous road journeys lead to distracted or drowsy driving. Therefore, there is a need for a system which alerts a distracted or drowsy driver. Moreover, as the levels of autonomy move beyond SAE Level 2, the system assumes a larger share of the dynamic driving task. Under challenging circumstances, the system might ask the driver to take back vehicle control. To guarantee safety, it’s crucial to monitor the driver’s condition in order to assess their readiness to regain control of the vehicle. An advanced safety feature known as a driver monitoring system (DMS), sometimes referred to as a driver state sensing (DSS) system, is designed to monitor a driver’s attentiveness and alertness, providing warnings or alerts to refocus their attention on driving when drowsiness or distraction is detected.

Computer-aided engineering (CAE) is a routinely used technology for the design and testing of road vehicles, including the simulation of their response to an impact. To increase automotive industry competitiveness by reducing physical test-based type approval and to improve road safety, recent initiatives have been taken by both industry and public authorities to promote the use of virtual testing through numerical simulation as an alternative way to check regulatory compliance. [1] To ensure acceptance of this alternative method, the accuracy of the simulation models and procedures needs to be assured and rated independently of the modelling process, software tools, and computing platform. Similarly, it is also imperative to understand the uncertainties emerging out of different component design parameters and analyze their sensitivity towards producing deviations in the reported results as per the requirements of the regulatory standard.

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 term Industry 4.0 is well known in contemporary automotive landscape. It encompasses a smart integrated framework of IIoT (Internet of Things) and industrial automation with machine learning, artificial intelligence and big data analytics to arrive at optimal solutions to running the processes in a streamlined, efficient and effective manner. Industry 4.0 has assumed critical significance in the contemporary era of people working from remote locations to operate processes in order to build products, thereby ensuring business continuity. Consequently, it follows that if industry 4.0 is applied to automotive homologation activity, it will lead to a standardized evaluation, consistent fidelity of testing, accurate judgement of the product under test with regards to its certification, and most importantly, timed delivery to release in the market. The author hereby elucidates a unified Industry 4.0 Framework for Automotive homologation in India which is the need of the hour.