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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.

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.