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Autonomous vehicles perform various functions with their own control strategies. Functions like Lane Departure Warning (LDW), Lane Keeping system (LKS) and Forward Collision Warning System (FCWS) requires special test tracks for their verification and validation. These test track requirements change with region to region according to available infrastructure. This paper deals with the design and development of test tracks for different ADAS functions verification and validation of Indian specific scenarios and its simulation in IPG CarMaker. The test track conceptualization has been done through the understanding and study of different international standards and geometry of test tracks for Indian conditions have been developed. IPG CarMaker software tool is used for creation of test track, and same track is used for simulation of above ADAS functions in IPG CarMaker.

Any change is vehicle exterior design, affects the aerodynamics characteristic. Generally different types of roof racks are attached on passenger vehicles to carry luggage which affects aerodynamic drag. The objective of this work is to perform aerodynamic analysis of ground vehicle with roof rack to investigate the change in drag coefficient. First, the aerodynamic analysis of a baseline passenger car model is performed with and without generic benchmarked roof rack at 100 kmph. Further analysis is carried out with different new designs of roof racks. Based on simulation result, a scaled down prototype model is fabricated and validated by using a wind tunnel test for optimum suitable case. The modelling of the vehicle is done in CATIA tool and simulation is carried out by using ANSYS Fluent.

Occupant motion in a vehicle rollover accident is a function of many factors. Some important ones are vehicle kinematics, position of the occupant in the vehicle, occupant size, ground topology and restraint usage. The far side belted occupants are more vulnerable than the near side occupants in a rollover accident as they have more energy as a result of their trailing and higher side of the vehicle. This outcome is attributable to the inadequate safety performance of the conventional single loop; B-pillar mounted D-ring restraints. Roof crush tends to displace the vehicle's B-pillar, resulting in D-Ring displacement which causes slack in the lap portion of the restraint. This slack enables centrifugal loads to move the far side occupant further away from the vehicle's instantaneous point of rotation. In this scenario, the presence of any ejection portal can result in an occupant becoming partially or fully ejected.

Frontal crash is the most common type of accidents in passenger vehicles which results in severe injuries or fatalities. During frontal crash, some frontal vehicle body has plastic deformation and absorbs impact energy. Hence vehicle crashworthiness is important consideration for safety aspect. The crash box is one of the most important parts in vehicle frontal structure assembly which absorb crash energy during impact. In case of frontal crash accident, crash box is expected to be collapsed by absorbing crash energy prior to the other parts so that the damage to the main cabin frame and occupant injury can be minimized. The main objective of this work is to design and optimize the crash box of passenger vehicle to enhance energy absorption. The modeling of the crash box is done in CATIA V5 and simulations are carried out by using ANSYS. The results show significant improvement in the energy absorption with new design of the crash box and it is validated experimentally on UTM.

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.

Electric passenger car with floor battery usually have its front boot space empty and the space is used as additional luggage storage. This space can be utilized to capture the wind energy and generate electricity. Based on this, the objective of this work is to perform an aerodynamic analysis of an electric passenger car using wind turbine placed at the front. Initially the aerodynamic analysis of a basic electric car model is performed and further simulated using wind turbines and aerodynamic add-on-devices. The simulation is carried-out using ANSYS Fluent tool. Based on the simulation result, scaled down optimized model is fabricated and tested in wind tunnel for validation. The result shows reduction of drag coefficient by 5.9%.

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.

This paper presents a methodology for predicting thermal comfort inside Midibus cabin with an objective to modify the Heating, Ventilation and Air Conditioning (HVAC) duct design and parametric optimization in order to have improved thermal comfort of occupant. For this purpose the bus cavity is extracted from baseline CAD model including fully seated manikins with various seating positions. Solar Load has been considered in the computational model and passenger heat load is considered as per BSR/ASHRAE 55-1992R standard. CFD simulation predicted the air temperature and velocity distribution inside passenger cabin of the baseline model. The experimental measurements have been carried out as per the guidelines set in APTA-BT-RP-003-07 standard. The results obtained from CFD and Experimental test were analysed as per EVS EN ISO7730 standard and calculated occupant comfort in terms of thermal comfort parameters like Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD).

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.

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 death toll due to traffic accidents in India is on a rise, according to the latest Road Transport ministry report, a total of 4.97 lakh road accident was reported in 2011. Though compared to 2010, the accidents have gone down by 1,945, the number of deaths at 1,42,485 has increased by over 7,000.[1] This paper proposes a design of an Emergency Intimation System (EIS) tailored to fit for Indian consumer needs and available infrastructure. EIS is an emergency alert technology devised to assist drivers and passenger in an event of vehicle crash. Majority of deaths are caused by slow accident response time. EIS is aimed to lower this response time and ensure that the required rescue and medical services are made available in time. This device employed to make this emergency alerts will be fitted into the vehicle Electrical and Electronics (E/E) architecture and will have interfaces with crash sensor network, CAN network and GSM 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.

India is one of the largest markets for the automobile sector and considering the trends of road fatalities and injuries related to road accidents, it is pertinent to continuously review the safety regulations and introduce standards which promise enhanced safety. With this objective, various Advanced Driver Assistance Systems (ADAS) regulations are proposed to be introduced in the Indian market. ADAS such as, Anti-lock Braking Systems, Advanced Emergency Braking systems, Lane Departure Warning Systems, Auto Lane Correction Systems, Driver Drowsiness Monitoring Systems, etc., assist the driver during driving. They tend to reduce road accidents and related fatalities by their advanced and artificial intelligent fed programs. This paper will share an insight on the past, recent trends and the upcoming developments in the regulation domain with respect to safety.

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.

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.

Government of India, in 2017, mandated a Side Impact Test (AIS 099 technically aligned to UN ECE Regulation No. 95.03 series of amendments) on M1 category Passenger Vehicles to ensure protection of occupants in lateral impact accident scenarios. Later, in 2022, a draft notification has been issued by the Government mandating installation of 6 airbags (2 Nos of thorax side airbags, 2 Nos of head protection or curtain airbags in addition to already mandated installation of Driver and Passenger Airbags) in all such passenger vehicles. However, the vehicles fitted with side thorax airbag and curtain airbags are proposed to be assessed as per AIS099 test only. Curtain Airbags are typically installed to protect occupant’s head from severe injuries in narrow object impacts simulated in Pole Side Impact Test Configurations. However, at present, India has not notified an equivalent standard to UN R135 demanding performance of the vehicle in pole side impact scenarios.

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 windscreen wiping system is mandatory requirement for automotive vehicle as per Central motor vehicle rules (CMVR). The main scope of the standard is to ensure vision zones to be wiped by wiping system to ensure maximum field of vision to the driver. The evaluation of vision zones as per IS 15802:2008 is generally determined by virtual simulation by OEMs. The limitation of virtual simulation is due to actual tolerances in vehicle, due to seat fitment, ergonomic dimensions, seat cushioning effect and wiper non-effective operation which are not taken into consideration very well off. The testing methodology described in the paper is an in-house developed test method based on SAE recommended practices. With the help of 3D H-point machine and a laser based ‘Theodolite’ equipped with horizontal and vertical angle projections from single pivot point is used to develop various vision zones on an actual vehicle windscreen as per technical data.

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.