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Autonomous driving is looked upon as solution for future of automotive vehicles. The technology has tremendous possibilities to improve safety, fuel economy, comfort, cost of ownership etc. The project to develop an autonomous controller from scratch was undertaken, with objective to drive under selected test scenarios. The car, modified to drive using this autonomous controller, is able to handle these scenarios. The key scenarios include ability to successfully drive on tracks with well-marked lanes, Follow the route as per selected trip plan file, recognize and follow all traffic road signs, traffic signals en-route, identify other vehicles on the road or pedestrians in the lane and take the appropriate action. The development was carried out using frugal engineering approach. As the Autonomous Vehicle technology is still under development, the standard proven published approaches are not available.

Vehicle localization and position determination is a major factor for the operation of Autonomous Vehicle. Errors or unavailability of resources to determine this, poses a serious threat not only to the vehicle but also the environment around it. Global Positioning System (GPS) is one of the most common resources to determine position about the reference geographic coordinate system. But this resource has several drawbacks of its own viz. clock errors, multi-path errors and also uncertainty of good signal strength due to weather conditions or physical barriers. Also an additional drawback of a low-update rate makes it unreliable for the Autonomous Localization algorithm to operate on this. Thus a system is required which has no external environment dependencies to determine the position of the vehicle. Inertial Measurement Unit is a coupled system comprising of a 3-axis accelerometer and 3-axis gyroscope which records body force accelerations and the yaw rate.

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.

BS-VI or equivalent development calls for tremendous efforts in concept investigation and calibration for engine out, after treatment, diagnostic checks, off-cycle emissions, field performance, component safety etc. Achieving calibration quality for all these tasks is very challenging considering development time and cost with conventional physical testing approach. Present article focuses on assessment of testing and calibration using virtual approach. To prove and validate this approach, a six-cylinder heavy duty diesel engine is selected and configured in HiL environment. The engine plant model is built offline and validated with base engine data at steady state and transient operations and RT model is integrated with ECU hardware. Data for plant model corrections is generated with short measurement campaign. Refined real time plant model is prepared for evaluating different calibration strategies on virtual test bed environment.

Automotive clutches form the most important component in the drive line which acts both as torque transmitter and as a fuse. Testing clutches, in the vehicle assembly, poses certain limitations. In this context the automotive clutch, as a component, needs to be evaluated to determine various performance parameters like wear, load loss, slipping torque, slipping time etc. to meet desired design, performance and durability requirements. It is very important to simulate engine and vehicle conditions in terms of operating environment, speed and load accurately while evaluating above parameters. This creates lot of challenges to design and develop a test rig capable of evaluating complete clutch performance. Very limited options are available for such test rigs worldwide. In India, no manufacturer provides such indigenous test rigs. Developing an indigenous, cost effective clutch test rig was the need of the hour.

This paper introduces xEV Simulator- A MATLAB based simulator platform capable of analyzing EV/HEV powertrain system in both backward and forward modelling. xEV Simulator employs Forward Simulation for drive-cycle performance evaluations and Backward simulation for powertrain component sizing and support xEV powertrain design. The powertrain subsystems are modelled in Simulink. This enables the model based system simulation and further controller prototyping and HiL testing. xEV Offline Simulator GUI enables user to simulate standard EV/HEV configurations with standard drive-cycles. The model parameters of different component subsystems can be configured. The Backward modelling and simulation support the estimation of subsystem values like Propulsion motor, Energy storage, etc., to perform as per the drive-cycle requirement.

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.

Towards the effort of reducing pollutant emissions, especially soot and nitrogen oxides, from direct injection Diesel engines, engineers have proposed various solutions, one of which is the use of a gaseous fuel as a partial supplement for liquid Diesel fuel. These engines are known as dual fuel combustion engines. A dual fuel (Diesel-CNG) engine is a base diesel engine fitted with a dual fuel conversion kit to enable use of clean burning alternative fuel like compressed natural gas. In this engine diesel and natural gas are burned simultaneously. Natural gas is fed into the cylinder along with intake air; the amount of diesel injection is reduced accordingly. Dual fuel engines have number of potential advantages like fuel flexibility, higher compression ratio, and better efficiency and less modifications on existing diesel engines. It is an ecological friendly technology due to lower PM and smoke emissions and retains the efficiency of diesel combustion.

Control algorithm development for typical Engine Management System is a challenging task. To develop a reliable control algorithm, proper closed loop testing environment is required. In such development activity, it is of prime importance to validate the algorithm on a standalone target engine. This can be achieved in engine test cell where the actual engine will be controlled by prototype ECU. But this process has drawbacks like higher testing cost, time consuming, non-reusability of test bed etc. Simulation based engine plant model development for closed loop ECU testing is an effective technique for such application. Various generic engine models are available for such application.to suit a particular target engine these model need to be parameterized with precise engine data. The vehicle parameters used for parameterization are typically obtained from actual test and engine design data.

Electric Power Assist Steering (EPAS) is a safety critical system because it affects vehicle stability and dynamics. In EPAS, electric motor takes the power from the battery and delivers this power to rack and pinion only on demand. Since EPAS contains electrical component such as Motor and electronic component such as Electronic Control Unit (ECU), reliability of these components is very important. To ensure safety and reliability, ISO 26262 standards are adapted which are derived from IEC 61508. This standard regulates the product development on system, hardware and software level and manages functional safety for electrical and electronic components. This paper discusses the applicability of the ISO 26262 standard to the development of EPAS ECU with respect to its hardware and software design. Hazard analysis and risk assessment of the basic EPAS architecture is performed and architecture is improved to achieve safety goal as per the standard.