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Electronic throttle body (ETB) is commonly employed in an intake manifold of a spark ignition engine to vary the airflow quantity by adjusting the throttle valve in it. The actual position of the throttle valve is measured by means of a dual throttle position sensor (TPS) and the signal is feedback into the control unit for accomplishing the closed loop control in order handle the nonlinearities due to friction, limp-home position, aging, parameter variations. This work aims presents a neural networks based novel virtual sensor for the estimation of throttle valve position in the electronic throttle body. Proposed neural network model estimates the actual throttle position using three inputs such as reference throttle angle, angular error and the motor current. In the present work, the dynamic model of the electronic throttle body is used to calculate the current consumed by the motor for corresponding throttle valve movement.

Advanced driver-assistance systems (ADAS) are becoming an essential part of the modern commercial automobile industry. Vehicle handling and stability are determined by the yaw rate and body slip of the vehicle. This paper is a comparative study of a nonlinear vehicle stability control algorithms for steering control based on two different controllers i.e. fuzzy logic based controller and PID controller. A full vehicle 14DOF model was made in Simulink to simulate an actual vehicle. The control algorithms are based on a two-track 7-DOF model with a non-linear tire model based on Pacejka “Magic tire formula”, which was used to establish the desired response of a full vehicle 14DOF model. It was found that the fuzzy logic-based control algorithm demonstrated an overall superior performance characteristic than a PID based control algorithm; this includes a significant decrease in time lag and overshoot.

Electronic throttle control is extensively preferred to vary the air intake in the engine manifold for regulating the torque in order to obtain the better vehicle response, high performance in terms of improving the fuel economy and trim down the emissions of the spark ignition engines. For such type of the engine control systems the throttle angle is estimation is accomplished either by pedal follower or torque based method. This work aims to develop a throttle opening angle estimation strategy in a closed loop manner using fuzzy logic approach by considering real time internal system and driver torque demands for controlling the SI engine. In present work the torque demand from internal system such as catalyst heating, cold start assist and battery voltage compensation is estimated using fuzzy logic strategy. Such intelligent system aims to replace the lookup tables associated with those systems and reduces the calibration effort.

The main objective of the study is to design and analyze casing and supports of a transmission system for an electric vehicle. The system comprises of motors as the power source, constant mesh gear box coupled with limited slip differential as the power transmitting source. The space occupied by the transmission system is a foremost constraint in designing the system. The wear and tear in the system is caused by the gear meshing process and transmission error which lead to failure of the transmission system. This internal excitation also produces a dynamic mesh force, which is transmitted to the casing and mounts through shafts and bearings. In order to overcome such issues in a transmission system, a gear box casing, differential mounts and motor mounts have been designed by the use of CAD-modeling software “SOLIDWORKS”. The designs were imported to FEA software “ANSYS” for carrying out static structural analysis.

This paper describes the design methodology and algorithm development towards the design of an automatic external gear-shifting and clutch-actuation system for a sequential gearbox with the aim of providing the drivers with easier and an efficient means of shifting gears. Automatically actuated manual transmission system bridges the gap between automatic and manual transmissions which provides the advantages of both type of transmissions. This would ideally leads to faster shifting time and provide significant benefits in the form of electronic-aids like launch control and traction control. Removal of mechanical clutching would reduce fatigue and lead to ergonomic benefit. Based on the benchmarking performed on an easily available ready-to-install aftermarket alternative, options will be considered for the actuating mechanism and the most feasible will be used to develop a shifting system.