The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 30, 2025

Filed:

Apr. 03, 2023
Applicants:

Vedang Deshpande, Cambridge, MA (US);

Raphael Chinchilla, Cambridge, MA (US);

Ankush Chakrabarty, Cambridge, MA (US);

Christopher Laughman, Cambridge, MA (US);

Inventors:

Vedang Deshpande, Cambridge, MA (US);

Raphael Chinchilla, Cambridge, MA (US);

Ankush Chakrabarty, Cambridge, MA (US);

Christopher Laughman, Cambridge, MA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
F25B 49/02 (2006.01); F24F 11/56 (2018.01); F24F 11/64 (2018.01);
U.S. Cl.
CPC ...
F25B 49/022 (2013.01); F24F 11/56 (2018.01); F24F 11/64 (2018.01); F25B 2500/18 (2013.01); F25B 2500/19 (2013.01); F25B 2600/11 (2013.01); F25B 2600/2513 (2013.01); F25B 2700/171 (2013.01); F25B 2700/19 (2013.01); F25B 2700/21 (2013.01);
Abstract

The present disclosure discloses a system and a method for controlling an operation of a vapor compression cycle based on a hybrid model of dynamics of the vapor compression cycle including a physics-based model and a data-driven model. The method comprises executing a constrained Kalman smoother over the observed variables collected over multiple instances of time to jointly estimate the parameters of the physics-based model and states of the vapor compression cycle, and updating the data-driven model to minimize a difference between the states estimated by executing the constrained Kalman smoother and the states predicted by the physics-based model. The method further comprises updating the hybrid model with the estimated parameters of the physics-based model and the updated data-driven model, and controlling the operation of the vapor compression cycle using the updated hybrid model.


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