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Adaptation for Air-Intake System Throttle Control in a Gasoline Engine With Low-Pressure Exhaust-Gas Recirculation

[+] Author Affiliations
Mario Santillo, Suzanne Wait, Julia Buckland

Ford Research and Advanced Engineering, Dearborn, MI

Paper No. DSCC2015-9657, pp. V001T12A001; 8 pages
  • ASME 2015 Dynamic Systems and Control Conference
  • Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems
  • Columbus, Ohio, USA, October 28–30, 2015
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5724-3
  • Copyright © 2015 by ASME


We investigate control strategies for traditional throttle-in-bore as well as low-cost cartridge-style throttle bodies for the air-intake system (AIS) throttle used in low-pressure exhaust-gas recirculation (LPEGR) on a turbocharged gasoline engine. Pressure sensors placed upstream and downstream of the AIS throttle are available as signals from the vehicle’s engine control unit, however, we do not use high-bandwidth feedback control of the AIS throttle in order to maintain frequency separation from the higher-rate EGR loop, which uses the downstream pressure sensor for feedback control. A design-of-experiments conducted using a feed-forward lookup table-based AIS throttle control strategy exposes controller sensitivity to part-to-part variations. For accurate tracking in the presence of these variations, we explore the use of adaptive feedback control. In particular, we use an algebraic model representing the throttle plate effective opening area to develop a recursive least-squares (RLS)-based estimation routine. A low-pass filtered version of the estimated model parameters is subsequently used in the forward-path AIS throttle controller. Results are presented comparing the RLS-based feedback algorithm with the feed-forward lookup table-based control strategy. RLS is able to adapt for part-to-part and change-over-time variabilities and exhibits an improved steady-state tracking response compared to the feed-forward control strategy.

Copyright © 2015 by ASME



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