Conference Proceedings

DIESEL ENGINE FUEL INJECTION CONTROL USING A MODEL-GUIDED EXTREMUM-SEEKING METHOD

Prasad Divekar, Qingyuan Tan, Xiang Chen, Ming Zheng, Ying Tan

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 | AMER SOC MECHANICAL ENGINEERS | Published : 2016

Abstract

Diesel engine fuel injection control is presented as a feedback based online optimization problem. Extremum seeking (ES) approach is used to address the online optimization formulation. The cost function is synthesized from extensive experimental investigations such that the indicated thermal efficiency of the engine is maximized while minimizing the NOx emissions under external boundary conditions. Knowledge of the physical combustion and emission formation process based on a precalibrated non-linear engine model output is used to determine the ES initial control input to minimize the seeking time. The control is demonstrated on a hardware-in-the-loop engine simulator bench.

University of Melbourne Researchers