Model Predictive Controller Design For Internal Combustion Engines Based On The Second Law Of Thermodynamics
Date of Award
Doctor of Philosophy
Mechanical and Aerospace Engineering
Rick Meyer, Ph.D.
Claudia Fajardo, Ph.D.
Jennifer Hudson, Ph.D.
Damon A. Miller, Ph.D.
Energy resources depletion and worldwide strict emissions policies pose challenges that automotive manufacturers try to overcome through researching advanced powertrain technologies such as lean-burn gasoline, direct injection, homogeneous charge compression ignition engines, powertrain electrification, etc. Most of these developments have been focused on conventional internal combustion engines (ICE) emissions and performance enhancements. Most ICE control strategies are built based on the First Law of Thermodynamics (FLT) i.e., to deliver a specific load requirement, enhancing thermal efficiency, etc. The FLT doesn’t account for in-cylinder high temperature thermodynamics process irreversibilities that cause losses in the work potential; up to 25% of the fuel availability or exergy can be lost to irreversibilities during a single combustion cycle. The second law of thermodynamics (SLT) states that not all energy in an energy source is available to do work; the SLT evaluates the maximum available energy i.e., the exergy in that source after accounting for the losses caused by the irreversibilities. Therefore, including the exergy in an optimal engine control algorithm may lead to improved ICE thermal efficiencies. Specifically, SLT parameters are proposed to be included in an optimal control engine strategy. The control approach is tested using different engine modeling approaches: simplified spark ignition (SI) and compression ignition (CI) engines models, a detailed 1-D GT Power SI engine model with limited model calibration, and a detailed 1-D GT Power SI engine model with extensive model calibration. The outputs of the models provide differing levels of process resolution. Results show that using the SLT parameters with optimal control resulted in better fuel consumption and emissions reduction for each model type.
Abotabik, Muataz, "Model Predictive Controller Design For Internal Combustion Engines Based On The Second Law Of Thermodynamics" (2022). Dissertations. 3874.