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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.

Currently, on-road transport contributes nearly 12% of India’s total energy related carbon dioxide (CO2) emissions that are expected to be doubled by 2040. Following the global trends of increasingly stringent greenhouse gas emissions (GHG) and criteria emissions, India will likely impose equivalent Bharat Stage (BS) regulations mandating simultaneous reduction in CO2 emissions and nearly 90% lower nitrogen oxides (NOx) from the current BS-VI levels. Consequently, Indian automakers would likely face tremendous challenges in meeting such emission reduction requirements while balancing performance and the total cost of ownership (TCO) trade-offs. Therefore, it is conceivable that cost-effective system improvements for the existing internal combustion engine (ICE) powertrains would be of high strategic importance for the automakers.

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.

Bharat Stage VI emission norms were implemented in India in two stages: Stage I from April 1, 2020, and Stage II from April 1, 2023. For M & N category vehicles, the RDE test along with other applicable certification tests is mandatory for obtaining a BSVI compliance certificate during stages I and II. The RDE test is conducted on roads under real driving conditions, unlike the Type-I test, which uses a predefined cycle on the chassis dynamometer, during which the ambient temperature and other environmental conditions are controlled in a narrow range. During BSVI Stage I for the RDE test, there was no limit for any pollutant. Therefore, it is considered as the RDE monitoring stage, and from BS-VI Stage II, limits are enforced on a few pollutants (NOX and PN) as notified in notification GSR 226(E) dated March 27, 2023. Therefore, it is considered the RDE compliance stage.

Due to the transformation of the automotive industry from conventional vehicles to electric vehicles, new challenges have emerged concerning Electromagnetic Compatibility. Though the Radiated Emission limits in global regulation are the same for both types of powertrains of vehicles, however, due to the phenomena of conversion of high voltage to low voltage, rapid charging/discharging, and different components involved in electric powertrain, the Radiated Emission from electric vehicles give a strikingly different trend which is challenging to combat. When compared with the conventional Spark Ignition vehicle, many other electronic components of the electric vehicle stay in the mode of Power ON while in the “Ignition ON” steady state. This resulted in us observing a significant shift in the amplitude and frequency throughout the frequency band of Radiated Emission measurement.

The paper talks about Quantification of Alertness for vision based Driver Drowsiness and Alertness Warning System (DDAWS). The quantification of alertness, as per Karolinska Sleepiness Scale (KSS), reads the basic input of facial features & behaviour recognition of driver in a standard manner. Although quantification of alertness is inconclusive with respect to the true value, the paper emphasised on systematic validation process of the system covering various scenarios in order to evaluate the system’s functionality very close to the reality. The methodology depends on definition of threshold values of blink and head pose. The facial features are defined by number of blinks with classification of heavy blink and light blink and head pose in (x, y, z) directions. The Human Machine Interface (HMI) warnings are selected in the form of visual and acoustic signals. Frequency, Amplitude and Illumination of HMI alerts are specified.

Following global trends of increasingly stringent greenhouse gas (GHG) and criteria pollutant regulations, India will likely introduce within the next decade equivalent Bharat Stage (BS) regulations for Diesel engines requiring simultaneous reduction in CO2 emissions and up to 90% reduction in NOx emission from current BS-VI levels. Consequently, automakers are likely to face tremendous challenges in meeting such emission reduction requirements while maintaining performance and vehicle total cost of ownership (TCO), especially in the Indian market, which has experienced significant tightening of emission regulation during the past decade. Therefore, it is conceivable that cost effective approaches for improving existing diesel engines platforms for future regulations would be of high strategic importance for automakers.

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.

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 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.

With the recent development in virtual modelling and vehicle simulation technology, many OEM’s worldwide are using digital road profiles in virtual environment for vehicle durability load prediction and virtual design evaluation. For precise simulation results, it is important to have the tire digital twin which is the realistic representation of tire in the virtual environment. The study comprises of discussion about different types of tire models such as empirical, solid model, rigid ring model and flexural ring models such as Pacejka, MF Swift, CD tire, F tire etc. and also the complexity involved in development of these tire models. Generation of virtual tire model requires highly sophisticated test rigs as well as vehicle level testing with Wheel Force transducers and other vehicle dynamics sensors. The large number of data points generated with testing are converted in standard TYDEX format to be further processed in various software tool for virtual model generation.

The Indian market for battery-powered electric vehicles (xEV) is growing exponentially in the coming years, fueled by tumbling lithium-ion battery prices and favorable government policies. Lithium-ion battery is leading in clean mobility ecosystem for electric vehicles. LiBs efficient and safe performance for tropical climatic conditions is one of the primary requirements for xEV to succeed in India. The performance of LiBs, however, is impacted due to ambient temperature as well as the heat generated within cell due to the load cycle electrochemical reaction. The acceptable operating temperature region for LiBs normally is between 20 °C to 45 °C and anything outside of this region will lead to degradation of performance and irreversible damages. Therefore, understanding the thermal behavior is very crucial for an efficient battery thermal management.

Energy dispersive X-ray fluorescence (EDXRF) analysis have made it possible to conduct elemental analysis on a variety of fields, including those with environmental, automotive, geological, chemical, pharmaceutical, archaeology, and biological origins. The ability of EDXRF to deliver quick, non-destructive, and multi-elemental analytical findings with increased sensitivity is of great importance. It is a vital tool for quality control and quality assurance applications. Thus, EDXRF plays an important role to compare batch-to-batch products for meeting quality standards. This paper presents application of EDXRF as an effective tool for quick qualitative and quantitative evaluation of given samples.

Automotive electronics is increasingly playing a vital role in all vehicle subsystems. Since an electronic control system needs to be interfaced with the outside world, an electronic smart switch forms a key output interface with various loads such as solenoids, lamps, motors, relays, fans etc. Although integrated circuit based smart-switch semiconductor solutions are provided by all global semiconductor vendors, they prove more often than not to be overdesigned for majority of situations relevant to low end vehicles. They are also generously loaded with standard high-end features like thermal and overload protection which may not always be required. In addition, external transient protection and on-chip diagnostic features lend further complexity to the entire solution.

Particulate matter is one of the major pollutant responsible for deteriorating air quality, particularly in urban centers. Information on contributing sources with the share from different sources is a first and one of the important steps in controlling pollution. Diverse sources, anthropogenic as well as natural, like industries, transport, domestic burning, construction, wind-blown dust, road dust contribute to particulate matter pollution. Receptor modeling is a scientific method which is utilized for assessment of the contribution of various sources based on chemical characteristics of particulate matter sources and ambient air particulate matter. Representative data of fractions of various chemical species in the particulate matter from the different sources i.e. source fingerprint is an essential input for the receptor modeling approach.

In present scenario, tyre industry is more focused on providing maximum extent of NVH comfort to passengers by improvising the tyre design. Noise contribution from the tyres is classified in to three regions, viz., structure-borne (tyre vibrations), air-borne (tread pattern) and cavity noise (air cavity). In general, a Finite Element (FE) model of tyre provides an inherent advantage of analyzing tyre dynamic behavior. In this paper, an attempt was made to develop a three-dimensional FE tyre model and validate the same through experimental approach. The CAD Model of the tyre was generated through 3D image scanning process. Material property extraction of tyre was carried out by Universal Testing Machine (UTM) to generate Finite Element (FE) model. For validation of tyre FE model, Experimental Modal Analysis (EMA) and Noise Transfer Function (NTF) were conducted.

To enhance the crashworthiness of electric vehicles, designing the optimized and safer battery pack is very essential. The deformed battery cell can result in catastrophic events like thermal runaway and thus it becomes crucial to study the mechanical response of battery cell. The goal of the research is to experimentally investigate the effect of mechanical deformation on Lithium-ion battery cell. The paper thoroughly studies the phenomenon of short circuiting at the time of failure. Various experiments are carried on 18650 cylindrical cells (NCA chemistry) under custom designed fume hood. The setup captures the failure modes of battery cell. The loading conditions have been designed considering the very possible physical conditions during crash event. The study has been done for radial compression, semicircular indentation, hemispherical indentation, flat circular indentation and case of three-point bending.

The Electric Vehicles (EV) or Hybrid Electric Vehicle (HEV) has a bunch of electrical/electronic components and its operation give rise to complicated EMI/EMC issues. The Power Electronics Module (PEM), comprising of DC-DC convertor/invertor and Battery Management Unit (BMU), is driving the motor to propel the vehicle. “Battery Pack Module” powers these units through cables. The fast switching of these circuit elements present in the system leads to noise propagation through the cables. These noise signals give rise to various Electromagnetic (EM) related issues in the cable harness of vehicle. It is essential that these cables should not interfere with other electronic components and also does not get effected by external EM disturbances.

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.

Electric Vehicles (EVs), with its inherent advantage of zero tailpipe emissions, are gaining importance because of aggressive push from government not only to reduce air pollution but also to reduce dependency of fossil fuel. EVs and necessary charging infrastructure along with ‘connected’ technology is redefining mobility. Considering the fast growing EV market, it becomes important for an EV Powertrain Architect to design and develop a powertrain solution having low engineering efforts and satisfying business, market and regulatory requirements at a competitive price. This paper presents a compact, flexible, convenient and smart featured simulation tool for an EV Powertrain Architect for estimating the specifications of key powertrain components such as traction battery and electric motor. The proposed tool takes into consideration the end-user as well as the regulatory requirements of range, maximum speed, acceleration and gradeability.