Whirlpool is looking at advanced controls technologies including machine learning, neural networks, and model predictive controllers that will more efficiently cool complex refrigerator systems. Students on this team will evaluate current capabilities on the Python framework that will be fast prototyped and applied in a simulation environment with a conceptual plant model.
Abstract:
Whirlpool, the world’s leading major home appliance company, has been an innovator for over 100 years, beginning with a patent for an electric-driven wringer washer. Current refrigerator advancements are taking the appliance from a two compartment device (refrigerator and freezer) to one with multiple compartment systems that allow the user to quickly access snacks or even convert compartments from refrigerator to freezer and back again. These compartments increase the energy consumption of the system and require significant increases in expensive insulation to manage temperature control.
In order to drive disruptive innovation on performance algorithms, Whirlpool is looking at methods and ways to easily design, prototype, and test advanced controls technologies including machine learning, neural networks, and model predictive controllers that will more efficiently cool these complex systems. Students on this team will evaluate current advanced control capabilities on the Python framework that will be fast prototyped and applied in a simulation environment with a conceptual plant model.
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