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Experimental Investigations on CO2 Recovery from Engine Exhaust Using Adsorption Technology

ARC,SMEC,Vellore Institute of Technology-Saravanan S, Chidambaram Ramesh Kumar
  • Technical Paper
  • 2019-28-2577
Published 2019-11-21 by SAE International in United States
Energy policy reviews state that automobiles contribute 25% of the total Carbon dioxide (CO2) emission. The current trend in emission control techniques of automobile exhaust is to reduce CO2 emission. We know that CO2 is a greenhouse gas and it leads to global warming. Conversion of CO2 into carbon and oxygen is an energy-consuming process compared to the catalytic converters. The best way to reduce CO2 is to capture it from the source, store it and use it for industrial applications. To physically capture the CO2 from the engine exhaust, adsorbents like molecular sieves are utilized. In comparison to other CO2 separation methods, adsorption technique consumes less work and energy. Moreover, the sieves can be regenerated, reused and recycled once it is completely saturated. In this research work, zeolite X13 was chosen as a molecular sieve to adsorb CO2 from the exhaust. A chamber was designed to store the zeolite and it is attached to the exhaust manifold. The selected engine was a single-cylinder Briggs and Stratton petrol engine. The experiments were conducted in two…
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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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