IP Library › Granted Patent US 12,410,935
Granted Patent B2
US 12,410,935 · App. 17/914,497 · Granted Sep 9, 2025

Computerized device and computer-implemented method for controlling a HVAC system

Inventors: Olga Galchenko (St. Petersburg, RU); Mikhail Gritckevich (St. Petersburg, RU); Evgeny Ivanov (St. Petersburg, RU)
Assignee: SIEMENS AKTIENGESELLSCHAFT
F24F11/63F24F2110/20F24F2110/70
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Quick Facts
Patent No.
US 12,410,935
App. No.
17/914,497
Granted
Sep 9, 2025
Kind
B2
Abstract

Various embodiments of the teachings herein include a device for controlling a HVAC system of a room. The device may include: a memory storing a metamodel for a distribution of physical quantities of air in the room, the metamodel based on reduced order modeling of a plurality of executed simulations of the physical quantities for a first configuration of the room; and a processor programmed to determine a value of a first subset of the physical quantities at a certain location in the room using the metamodel and a set of measured values of each physical quantity being measured by a number of physical sensors.

Claims (27)

1. A device for controlling a HVAC system of a room, the device comprising:

a memory storing a metamodel for a distribution of physical quantities of air in the room, the metamodel based on reduced order modeling of a plurality of executed simulations of the physical quantities for a first configuration of the room;

a processor programmed to determine a value of a first subset of the physical quantities at a certain location in the room using the metamodel and a set of measured values of each physical quantity being measured by a number of physical sensors;

a receiving unit for receiving a request defining a desired temperature at a desired location in the room; and

a controller for generating a control signal for controlling the HVAC system based on the value of one or more of the first subset of the physical quantities determined and the received request;

wherein the metamodel is based on a plurality of parametrical simulations approximated using reduced order modeling into a set of algebraic equations for a set of desired physical quantities;

the set of algebraic equations include a system of linear equations; and

the system of linear equations provide a column vector of the desired physical quantities is equal to a sum of a product of a matrix describing the measured values of the physical quantities and a column vector of metamodel coefficients and a column vector of discrepancy.

2. The device of claim 1 , wherein the first subset of physical quantities include: air temperature, air velocity, relative humidity, absolute humidity, and/or CO 2 -content of air.

3. The device of claim 1 , wherein the metamodel models a 3D distribution of a plurality of physical quantities of the air in the room.

4. The device of any of claim 1 , wherein the plurality of executed simulations includes computer aided engineering (CAE) simulations applied to the certain room configuration.

5. The device of any of claim 1 , wherein the room configuration describes a geometry of the room including an area of the room, a height of the room, windows and doors of the room, a position of the room in the building, a number of persons in the room, locations of persons in the room, objects in the room, and/or locations of objects in the room.

6. The device of claim 1 , wherein the reduced order modeling includes machine learning.

7. The device of claim 1 , wherein the reduced order modeling includes a simulation and/or a number of empirical models.

8. The device of claim 1 , wherein:

the simulations are executed for a plurality of locations in the room; and

each of the simulations is executed based on a set of boundary conditions.

9. The device of claim 1 , wherein the processor is further programmed to determine the value of the certain physical quantity at any location in the room.

10. A HVAC system comprising:

a memory storing a metamodel for a distribution of physical quantities of air in the room, the metamodel based on reduced order modeling of a plurality of executed simulations of the physical quantities for a first configuration of the room; and

a processor programmed to determine a value of a first subset of the physical quantities at a certain location in the room using the metamodel and a set of measured values of each physical quantity being measured by a number of physical sensors;

a receiving unit for receiving a request defining a desired value for at least one property of the air at a desired location in the room;

wherein the processor generates a control signal for controlling the HVAC system based on the value of one or more of the first subset of the physical quantities determined and the received request; and

a fan coil unit controlled by the processor to adjust the at least one property of the air at the desired location in the room;

wherein the metamodel is based on a plurality of parametrical simulations approximated using reduced order modeling into a set of algebraic equations for a set of desired physical quantities;

the set of algebraic equations include a system of linear equations; and

the system of linear equations provide a column vector of the desired physical quantities is equal to a sum of a product of a matrix describing the measured values of the physical quantities and a column vector of metamodel coefficients and a column vector of discrepancy.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 26, 2022
From: GALCHENKO, OLGA; GRITCKEVICH, MIKHAIL; IVANOV, EVGENY
To: OOO SIEMENS
Reel/Frame 061213/0403 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 26, 2022
From: OOO SIEMENS
To: SIEMENS AKTIENGESELLSCHAFT
Reel/Frame 061213/0618 →
Continuity (1)
Related Publication 20230131098A1 · Apr 27, 2023
References Cited (21)
US 6173902B1 · Bauer · 2001 [cited by examiner]
US 12066798B2 · Wan · 2024 [cited by examiner]
US 20140039844A1 · Strelec · 2014 [cited by examiner]
US 20160209065A1 · Hagström et al. · 2016 [cited by applicant]
US 20160246269A1 · Ahmed et al. · 2016 [cited by applicant]
US 20170074535A1 · Booij · 2017 [cited by examiner]
US 20180082204A1 · Iwamasa · 2018 [cited by examiner]
US 20180252427A1 · Hieke · 2018 [cited by examiner]
US 20200004214A1 · Ahmed et al. · 2020 [cited by applicant]
US 20200082036A1 · Saito · 2020 [cited by examiner]
US 20210173365A1 · Ahmed et al. · 2021 [cited by applicant]
US 20220221149A1 · Carroll · 2022 [cited by examiner]
CN 105473354A · 2016 [cited by applicant]
CN 105805887A · 2016 [cited by applicant]
CN 107223195A · 2017 [cited by applicant]
WO 2019197324 · 2019 [cited by applicant]
Search Report for International Application No. PCT/RU2020/000162, 12 pages. [cited by applicant]
Ghosh, Rajat et al:; “Proper Orthogonal Decomposition-Based Modeling Framework for Imrpoved Spatial Resolution of Measured Temperature Data”; IEEE Transactions on Components, Packaging and Manufacturing Technology; IEEE… [cited by applicant]
Harish, V.S.K.V. et al:; “Reduced order modeling and parameter identification of a building energy system model through an optimization routine”; Applied Energy; Elsevier Science Publishers; vol. 162; pp. 1010-1023; XP0… [cited by applicant]
Phan, Long et al:; “Reduced order modeling of data center model with multi-Parameters”; Energy and Buildings; Lausanne; vol. 136; pp. 86-99; XP029860856; ISSN: 0378-7788; DOI: 10.1016/J.ENBUILD.2016.11.050. [cited by applicant]
Chinese Office Action, Application No. 202080099121.X, 9 pages, Jan. 27, 2024. [cited by applicant]