Development of a Data-Driven Injection Rate Model Based on Measurements With an Instrumented Diesel Fuel Injector
Diesel fuel injectors play a central role in the performance and robustness of large diesel and dual fuel engines. Instrumentation of such injectors has the potential to reveal detailed insights into the fuel injection process and related combustion phenomena inside the engine. A valuable parameter for analyzing the injection and the combustion process is the fuel injection rate (i.e., the actual nozzle fuel mass flow rate during the injection process). This parameter can be measured when the injection system is set up on a hydraulic test rig but not when it is part of an engine.
The target of this thesis is to develop a data-driven model that predicts the fuel injection rate curve as a function of other signals obtained from an instrumented prototype injector. Injection rate measurements were carried out on a hydraulic test rig to generate a measurement database for modeling.
Masterarbeit
Tasks:
- Familiarization with injection and related measurement technology
- Preprocessing of hydraulic test rig and injection system measurement data
- Development of a data-driven model for fuel injection rate prediction
- Composition of the master’s thesis
Prerequisites: Programming skills in Python and/or R; experience in data analysis
Earliest possible start date: Immediately
Duration: Approximately 6 months
Contact details:
Ao. Univ.-Prof. Dr. Andreas Wimmer, +43 (316) 873-30101, andreas.wimmer@lec.tugraz.at
Dr. Constantin Kiesling, +43 (316) 873-30092, constantin.kiesling@lec.tugraz.at
If this job profile does not match your career expectations, then we cordially invite you to view our other advertised positions as well or to apply without reference to an open position, describing your career goals, your desired fields of work and your abilities.
In order to perform our research activities at the highest level, which are oriented towards the overall system, we are continuously expanding our team in the disciplines of mechanical engineering, physics, mathematics, process engineering, material science, electronics, data science, sensor technology and others. |
 |