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.
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
Ao. Univ.-Prof. Dr. Andreas Wimmer, +43 (316) 873-30101, firstname.lastname@example.org
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