IP Library › Granted Patent US 12,372,934
Granted Patent B2
US 12,372,934 · App. 18/432,947 · Granted Jul 29, 2025

Building HVAC system with multi-objective optimization control

Inventors: Michael J. Risbeck (Madison, WI); Kirk H. Drees (Cedarburg, WI); Jonathan D. Douglas (Mequon, WI)
Assignee: TYCO FIRE & SECURITY GMBH
G05B19/042F24F8/10F24F11/47F24F11/52F24F11/64F24F11/70F24F8/22F24F2110/10F24F2110/20F24F2120/20F24F2140/60G05B15/02G05B19/04G05B2219/2614G06F30/20
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Quick Facts
Patent No.
US 12,372,934
App. No.
18/432,947
Granted
Jul 29, 2025
Kind
B2
Abstract

A controller for heating, ventilation, or air conditioning (HVAC) equipment operable to affect an environmental condition of a building is configured to obtain predictive models that predict values of an energy control objective and an air quality control objective as a function of control decision variables for the HVAC equipment. The controller executes a multi-objective optimization process using the predictive models to produce multiple sets of optimization results corresponding to different values of the control decision variables, the energy control objective, and the air quality control objective. The controller selects one or more of the sets of optimization results based on the values of the energy control objective and the air quality control objective. The controller operates the HVAC equipment to affect the environmental condition of the building in accordance with the values of the control decision variables corresponding to a selected set of the optimization results.

Claims (44)

1. A controller for heating, ventilation, or air conditioning (HVAC) equipment operable to affect an environmental condition of a building, the controller comprising:

one or more processors; and

memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

obtaining one or more predictive models configured to predict values of an energy control objective and an air quality control objective as a function of control decision variables for the HVAC equipment;

executing a multi-objective optimization process comprising performing multiple different optimizations using the one or more predictive models to produce multiple sets of optimization results, wherein each of the multiple different optimizations is performed using a different set of constraints and produces a different set of the optimization results comprising different values of the control decision variables, the energy control objective, and the air quality control objective;

selecting one or more of the sets of optimization results based on the values of the energy control objective and the air quality control objective; and

operating the HVAC equipment to affect the environmental condition of the building in accordance with the values of the control decision variables corresponding to a selected set of the optimization results.

2. The controller of claim 1 , wherein the energy control objective comprises an amount of energy consumption predicted to result from operating the HVAC equipment in accordance with the control decision variables.

3. The controller of claim 1 , wherein the energy control objective comprises an amount of carbon emissions predicted to result from operating the HVAC equipment in accordance with the control decision variables.

4. The controller of claim 1 , wherein the energy control objective comprises a cost of energy consumed by the HVAC equipment predicted to result from operating the HVAC equipment in accordance with the control decision variables.

5. The controller of claim 1 , wherein the air quality control objective comprises an infection risk predicted to result from operating the HVAC equipment in accordance with the control decision variables.

6. The controller of claim 1 , wherein the air quality control objective comprises an amount or concentration of particles in indoor air in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables.

7. The controller of claim 1 , wherein the air quality control objective comprises an indoor air quality score predicted to result from operating the HVAC equipment in accordance with the control decision variables.

8. The controller of claim 1 , wherein the air quality control objective comprises an amount or concentration of carbon dioxide in indoor air in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables.

9. The controller of claim 1 , wherein the air quality control objective comprises one or more comfort parameters affecting occupant comfort in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables.

10. The controller of claim 1 , wherein the different sets of constraints comprise different sets of constraints for the control decision variables or different search spaces for the control decision variables, the multiple different optimizations producing corresponding sets of the multiple sets of optimization results.

11. The controller of claim 1 , wherein executing the multi-objective optimization process comprises optimizing an objective function that quantifies the values of the energy control objective subject to a constraint based on the values of the air quality control objective.

12. The controller of claim 1 , wherein:

executing the multi-objective optimization process comprises performing an optimization of an objective function comprising either (i) the energy control objective without the air quality control objective or (ii) the air quality control objective without the energy control objective;

the optimization of the objective function is performed subject to a constraint on whichever of the energy control objective or the air quality control objective is not included in the objective function; and

the multiple sets of optimization results are produced by adjusting the constraint on whichever of the energy control objective or the air quality control objective is not included in the objective function and repeating the optimization of the objective function for multiple different values of the constraint.

13. The controller of claim 1 , wherein executing the multi-objective optimization process comprises optimizing an objective function subject to one or more constraints comprising the one or more predictive models.

14. The controller of claim 1 , wherein selecting one or more of the sets of optimization results comprises selecting one or more of the sets of optimization results for which the values of the energy control objective and the air quality control objective are not both improved by another of the sets of optimization results.

15. A method for operating heating, ventilation, or air conditioning (HVAC) equipment operable to affect an environmental condition of a building, the method comprising:

obtaining one or more predictive models configured to predict values of an energy control objective and an air quality control objective as a function of control decision variables for the HVAC equipment;

executing a multi-objective optimization process comprising performing multiple different optimizations using the one or more predictive models to produce multiple sets of optimization results, wherein each of the multiple different optimizations is performed using a different set of constraints and produces a different set of the optimization results comprising different values of the control decision variables, the energy control objective, and the air quality control objective;

selecting one or more of the sets of optimization results based on the values of the energy control objective and the air quality control objective; and

operating the HVAC equipment to affect the environmental condition of the building in accordance with the values of the control decision variables corresponding to a selected set of the optimization results.

16. The method of claim 15 , wherein the energy control objective comprises at least one of:

an amount of energy consumption predicted to result from operating the HVAC equipment in accordance with the control decision variables;

an amount of carbon emissions predicted to result from operating the HVAC equipment in accordance with the control decision variables; or

a cost of energy consumed by the HVAC equipment predicted to result from operating the HVAC equipment in accordance with the control decision variables.

17. The method of claim 15 , wherein the air quality control objective comprises at least one of:

an infection risk predicted to result from operating the HVAC equipment in accordance with the control decision variables;

an amount or concentration of particles in indoor air in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables;

an indoor air quality score predicted to result from operating the HVAC equipment in accordance with the control decision variables;

an amount or concentration of carbon dioxide in the indoor air in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables; or

one or more comfort parameters affecting occupant comfort in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables.

18. The method of claim 15 , wherein executing the multi-objective optimization process comprises optimizing an objective function that quantifies the values of the energy control objective subject to a constraint based on the values of the air quality control objective.

19. The method of claim 15 , wherein:

executing the multi-objective optimization process comprises performing an optimization of an objective function comprising either (i) the energy control objective without the air quality control objective or (ii) the air quality control objective without the energy control objective;

the optimization of the objective function is performed subject to a constraint on whichever of the energy control objective or the air quality control objective is not included in the objective function; and

the multiple sets of optimization results are produced by adjusting the constraint on whichever of the energy control objective or the air quality control objective is not included in the objective function and repeating the optimization of the objective function for multiple different values of the constraint.

20. The method of claim 15 , wherein executing the multi-objective optimization process comprises optimizing an objective function subject to one or more constraints comprising the one or more predictive models.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 18, 2024
From: JOHNSON CONTROLS TYCO IP HOLDINGS LLP
To: TYCO FIRE & SECURITY GMBH
Reel/Frame 066957/0796 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 5, 2024
From: RISBECK, MICHAEL J.; DREES, KIRK H.; DOUGLAS, JONATHAN D.
To: JOHNSON CONTROLS TYCO IP HOLDINGS LLP
Reel/Frame 066387/0252 →
Continuity (10)
Continuation 17483078 · Sep 23, 2021
Continuation In Part 17403669 · Aug 16, 2021
Continuation In Part 17393138 · Aug 3, 2021
Continuation 16927766 · Jul 13, 2020
Continuation In Part 16927759 · Jul 13, 2020
Provisional Application 63220878 · Jul 12, 2021
Provisional Application 63194771 · May 28, 2021
Provisional Application 63044906 · Jun 26, 2020
Provisional Application 62873631 · Jul 12, 2019
Related Publication 20240176319A1 · May 30, 2024
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