AAC 2019 Paper Abstract

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Paper ThAT3.1

Xia, Lu (Eindhoven University of Technology), Willems, Robbert (Eindhoven University of Technology), de Jager, Bram (Technische Universiteit Eindhoven), Willems, Frank (Eindhoven University of Technology)

Constrained Optimization of Fuel Efficiency for RCCI Engines

Scheduled for presentation during the Invited Session "AI / Intelligent Vehicle Control and Calibration" (ThAT3), Thursday, June 27, 2019, 10:30−10:50, Chamerolles

9th IFAC International Symposium on Advances in Automotive Control, June 23-27, 2019, Orléans, France

This information is tentative and subject to change. Compiled on April 19, 2024

Keywords Combustion Modeling and Control: Spark Ignition, Compression Ignition, Homogeneous Charge Compression Ignition, Model-based Diagnostics, Model-based Calibration

Abstract

Fuel efficiency optimization and emission reduction have become essential parts of engine research, due to the growing demand for environmental protection. In this paper, a computationally efficient optimization method has been applied to maximize the fuel efficiency under constraints of maximum pressure rise rate and various pollutant emissions using the combination of multiple regression analysis and particle swarm optimization. This optimization method has been applied to a Reactivity Controlled Compression Ignition (RCCI) engine. First, a data-driven model has been identi ed, which shows good agreement with experimental data for gIMEP as well as emissions. Using this RCCI model in the proposed optimization method, the optimal operating conditions for highest gross indicated thermal efficiency are determined under various conflicting emission and safety constraints.

 

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