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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.

Autonomous Emergency Braking (AEB) systems play a critical role in ensuring vehicle safety by detecting potential rear-end collisions and automatically applying brakes to mitigate or prevent accidents. This paper focuses on establishing a framework for the Verification & Validation (V&V) of Advanced Driver Assistance Systems (ADAS) by testing & verifying the functionality of a RADAR-based AEB ECU. A comprehensive V&V approach was adopted, incorporating both virtual and physical testing. For virtual testing, closed-loop Hardware-in-Loop (HIL) simulation technique was employed. The AEB ECU was interfaced with the real-time hardware via CAN. Data for the relevant target such as the target position, velocity etc. was calculated using an ideal RADAR sensor model running on the real-time hardware. The methodology involved conducting a series of test scenarios, including various driving speeds, obstacle types, and braking distances.

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.

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.

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.

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.

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.

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.

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.

An excellent physical and mechanical property makes Aluminium (Al) alloy suitable alternative lightweight materials against steel and cast iron in automotive components. ICME is a computational tool, which integrates the materials information to engineering product performance analysis. MatCalc is ICME tool, which follows the chain rule of process, microstructure, property and performance relationship in materials development. This paper reports the development of Al 6061-T6 propeller shaft through forging process and the materials and process model of the Al yoke is simulated using MatCalc simulation software. Finite element analysis method is used for designing of Al 6061-T6 propeller shaft. The forged Al yoke is solutionized at temperature 550°C for 1 hr followed by artificial ageing at temperature 180°C for 16 hrs to improve the hardness and strength of the yoke.

The automotive and related industries are concentrating their efforts on improving comfort by lowering engine, wind, and road noise and vibrations. However, as background noise levels decrease, the squeaks and rattles (S&R) generated by the vehicle's many components become more noticeable and distracting. As a result of the absence of a dominant noise source from a traditional petrol/diesel car, (S&R) noise becomes more dominant than other types of noise in electric vehicles. In this paper, we propose a novel simulation technique for developing a systematic approach to identifying and solving (S&R) problems in vehicle components/sub-assemblies during the primary stage of product development cycle, thus reducing the overall product development time. This paper will present a novel approach to comprehending various methods and Design of Experiments (DOE) techniques used to determine the root cause of (S&R) problems and to solve those using numerical methods.

Bharat Stage VI (BS VI) emission norms are already introduced in India from 1st April 2020. The implementation of BS VI emission standards essentially brings Indian motor vehicle regulations on par with most stringent International standards. The BS VI regulation also mandated Real Driving Emission (RDE) measurement with objective to limit regulated pollutants esp. NOX & PN during real use of vehicle. For M1 passenger vehicles Carbon Dioxide (CO2) emissions measured in Lab is also regulated under CAFÉ (Corporate Average Fuel Economy) however, CO2 emission during Real on Road Driving is not regulated. So, this study was carried out to compare CO2 on real road traffic conditions with standard lab conditions. This study was done on a set of BS VI compliant vehicles with diverse characteristic such as engine capacity, fuel type.

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).

Major cause of air pollution in the world is due to burning of fossil fuels for transport application; around 23% GHG emissions are produced due to transport sector. Likewise, the major cause of air pollution in Indian cities is also due to transport sector. Marginal improvement in the fuel economy provide profound impact on surrounding air quality and lightweighting of vehicle mass is the key factor in improving fuel economy. The paper describes robust and integrated approach used for design and development of lightweight bus structures for Indian city bus applications. An attempt is made to demonstrate the use of environment friendly material like aluminium in development of lightweight superstrutured city buses for India. Exercise involved design, development and prototype manufacturing of 12m Low Entry and 12m Semi Low Floor (SLF) bus models.

Role of wheel and underbody aerodynamics of vehicle in the formation of drag forces is detrimental to the fuel (energy) consumption during the course of operation at high velocities. This paper deals with the CFD simulation of the flow around the wheels of a bus with different wheel housing arrangements. Based on benchmarking, a model of a bus is selected and analysis is performed. The aerodynamic drag coefficient is obtained and turbulence around wheels is observed using ANSYS Fluent CFD simulation for different combinations of wheel-housing- at the front wheels, at the rear wheels and both in the front and rear wheels. The drag force is recorded and corresponding influence on energy consumption of a bus is evaluated mathematically. A comparison is drawn between energy consumption of bus body without wheel housing and bus body with wheel housing. The result shows a significant reduction in drag coefficient and fuel consumption.

Active aerodynamics can be defined as the concept of reducing drag by making real-time changes to certain devices such that it modifies the airflow around a vehicle. Using such devices also have the added advantages of improving ergonomics and performance along with aesthetics. A significant reduction in fuel consumption can also be seen when using such devices. The objective of this work is to reduce drag acting on a passenger car using the concept of active aerodynamics with grill shutters and air dams. First, analysis has been carried out on a baseline passenger car and further simulated using active grill shutters and air dams for vehicle speed ranging from 60 kmph to 120 kmph, with each active device open from 0° to 90°. The optimized model is then validated for a scaled down prototype in a wind tunnel at 80kmph. Vehicle has been modelled using SolidWorks tool and the simulation has been carried out using ANSYS Fluent.