STUDENT PROJECT: ML-based modeling of heat pumps using transfer learning
BITZER Electronics A/S
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BITZER Electronics develops controllers for different HVAC&R systems such as heat pumps, ventilation systems, reefer trucks/trailers, reefer containers, and supermarket refrigeration systems. In heat pumps, mathematical models of the systems are different from application to application based on the size of the heat pump, utilized components, application requirements, etc. Thus, obtaining an accurate and precise model of each system required a lot of effort.
The model of heat pumps can be used in many development scenarios in such as efficiency optimization or fault detection. Thus, we are looking for a student or a group of students who are interested in using Machine Learning methodologies for heat pump modelling.
Method
Transfer learning refers to a process where a model trained on one problem is used in some way on a second related problem. This methodology is supervised learning and is generally used when the input data of one ML algorithm (teacher model) is the same as or similar to the second model (student model), but the targets are different in those models. Using this advantage, a small amount of data from a new system can be used to tune the trained model and obtain an accurate model of the new system.
Application
Bitzer Electronics provides a simulation model of a heat pump that can be used for data collection and training of the teacher model. Different heat pump simulation models are available to use as the student model.
Prerequisites
// You have a basic knowledge of ML algorithms and are eager to apply it to the industry.
// You are familiar with MATLAB/Simulink or Python.
Communication
As a student, or group of students, who collaborate with us, you are welcome to visit us to get more insight into the company’s fingerprint. We provide student desks if you like to have close communication with us.
Supervisors
Zahra Soltani (PhD Control Engineer, Control Team)
[email protected]
Kresten Sørensen (Head of Control Team)
[email protected]
Department: Control Team
Location: Kærvej 77, 6400, Sønderborg, Denmark
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