PhD Dissertation Defense: Volkan Aran08-07-2019

Flexible and Robust Control of Heavy-Duty Diesel Engine Airpath Using Data Driven Disturbance Observers and GPR Models



Volkan Aran
Mechatronics, PhD Dissertation, 2019


Thesis Jury

Prof. Dr. Mustafa Unel (Thesis Advisor), Assoc. Prof. Dr. Kemalettin Erbatur,

Assist. Prof. Dr. Meltem Elitaş, Prof. Dr. Şeref Naci Engin, Prof. Dr. Metin Gökaşan



Date & Time: July 12th, 2019 – 10:00 AM

Place: FENS L048

Keywords: Diesel Engine, Airpath Control, Disturbance Observer, Gaussian Process Regression, Sliding Model Control, Model Based Control, WHTC




Diesel engine airpath control is crucial for modern engine development due to increasingly stringent emission regulations. This thesis aims to develop and validate a flexible and robust control approach to this problem for specifically heavy-duty engines. It focuses on estimation and control algorithms that are implementable to the current and next generation commercial electronic control units (ECU). To this end, targeting the control units in service, a data driven disturbance observer (DOB) is developed and applied for mass air flow (MAF) and manifold absolute pressure (MAP) tracking control via exhaust gas recirculation (EGR) valve and variable geometry turbine (VGT) vane. Its performance benefits are demonstrated on the physical engine model for concept evaluation. The proposed DOB integrated with a discrete-time sliding mode controller is applied to the serial level engine control unit. Real engine performance is validated with the legal emission test cycle (WHTC - World Harmonized Transient Cycle) for heavy-duty engines and comparison with a commercially available controller is performed, and far better tracking results are obtained. Further studies are conducted in order to utilize capabilities of the next generation control units. Gaussian process regression (GPR) models are popular in automotive industry especially for emissions modeling but have not found widespread applications in airpath control yet. This thesis presents a GPR modeling of diesel engine airpath components as well as controller designs and their applications based on the developed models. Proposed GPR based feedforward and feedback controllers are validated with available physical engine models and the results have been very promising.