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Modelling and Validation of a Control Algorithm for Yaw Stability & Body Slip Control Using PID & Fuzzy Logic Based Controllers

SITAMS-Chellappan Kavitha
VIT University-Umashankar Lath, Sanyam Kakkar, Aman Agarwal, Bragadeshwaran Ashok, Vemuluri Ramesh Babu, Sathiaseelan Denis Ashok
Published 2019-10-11 by SAE International in United States
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. The proposed control algorithms were validated through the co-simulation of Carsim and Simulink in real time.
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Neural Network Based Virtual Sensor for Throttle Valve Position Estimation in a SI Engine

SITAMS-Chellappan Kavitha
VIT University-Bragadeshwaran Ashok, Sathiaseelan Denis Ashok, Chidambaram Ramesh Kumar
Published 2019-10-11 by SAE International in United States
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. Proposed virtual sensor is tested for the sinusoidal and random driving cycle throttle angle input using a Bosch DVE5 electronic throttle body. Estimated throttle valve angle using the…
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