Building management system with clean air and infection reduction features

Patent metadata

Field	Value
Publication number	US-2023250988-A1
Application number	US-202318106932-A
Country	US
Kind code	A1
Filing date	Feb 7, 2023
Priority date	Feb 8, 2022
Publication date	Aug 10, 2023
Grant date	—

Abstract

Systems and methods for executing an IAQ analysis of a building. One system includes a controller including memory and one or more processors configured to obtain IAQ data from one or more sensors within the building, wherein the IAQ data is associated with at least one of a plurality of environment species, obtain BAS data, identify one or more unknown parameters from the IAQ data and BAS data of two or more of the plurality of environment species, estimate the one or more unknown parameters based on inputting the IAQ data and the BAS data into an optimization model, and wherein the optimization model analyzes predicted concentrations of the plurality of environment species subject to the two or more of the plurality of environment species evolving according to a single-species concentration model, and provide the estimated one or more unknown parameters to one or more predictive models.

First claim

What is claimed is:

1 . A building management system (BMS) for executing an indoor air quality (IAQ) analysis of a building, the BMS comprising:
a controller comprising memory and one or more processors configured to:
obtain IAQ data from one or more sensors within the building, wherein the IAQ data is associated with at least one of a plurality of environment species;
obtain building automation system (BAS) data;
identify one or more unknown parameters from the IAQ data and BAS data of two or more of the plurality of environment species;
estimate the one or more unknown parameters based on inputting the IAQ data and the BAS data into an optimization model, and wherein the optimization model analyzes predicted concentrations of the plurality of environment species subject to the two or more of the plurality of environment species evolving according to a single-species concentration model; and
provide the estimated one or more unknown parameters to one or more predictive models configured to predict values of a control objective for one or more building zones as a function of control decision variables for HVAC equipment.

2 . The BMS of claim 1 , wherein the single-species concentration model is an ordinary differential equation model, and wherein the plurality of environment species are subject to the two or more of the plurality of environment species evolving according to the single-species concentration model using one or more basis function expansions of the one or more unknown parameters.

3 . The BMS of claim 2 , wherein a predicted error of the optimization model of the two or more environment species of the plurality of environment species is scaled according to one or more scaling coefficients of the optimization model, wherein the two or more of the plurality of environment species is collected from a sensor of the one or more sensors.

4 . The BMS of claim 3 , wherein the one or more scaling coefficients are determined based comparing a first accuracy of a first sensor configured to collect the IAQ data for a first environment species with a second accuracy of a second sensor configured to collect the IAQ data for a second environment species and in response to comparing the first accuracy and the second accuracy, biasing either the first environment species or the second environment species in the optimization model.

5 . The BMS of claim 1 , wherein the plurality of environment species comprises at least two of a carbon dioxide species, a particulate matter species, a volatile organic compounds species, and a humidity species.

6 . The BMS of claim 1 , wherein the optimization model comprises an objective function, and wherein the objective function is minimized by adjusting the one or more unknown parameters according to the predicted concentrations approximately matching one or more measured time series concentrations.

7 . The BMS of claim 1 , wherein the one or more unknown parameters comprises at least one of a time series occupancy, a time series ventilation rate, or a time series recirculation rate, and wherein the two or more of the environment species is associated with one or more of the predicted concentrations.

8 . The BMS of claim 7 , wherein a time series occupancy trajectory and a ventilation trajectory are the same for each of a plurality of single-species concentration models, and wherein the predicted concentrations are different for each of the plurality of single-species concentration models.

9 . The BMS of claim 1 , the one or more processors further configured to:
operate HVAC equipment to affect an environmental condition of the building in accordance with a selected set of optimization results from the one or more predictive models.

10 . The BMS of claim 1 , the one or more processors further configured to:
in response to estimating the one or more unknown parameters, modify a control strategy for the one or more building zones based on improving a value of the predicted values.

11 . The BMS of claim 1 , the one or more processors further configured to execute the one or more predictive models to:
scale at least one of a first control objective or a second control objective based on the estimated one or more unknown parameters and at least one hospitalization metric; execute an optimization process using the one or more predictive models to produce multiple sets of optimization results of the control decision variables and corresponding sets of optimal values of the first control objective and the second control objective for a time period; select one or more of the sets of optimization results; and operate the HVAC equipment to affect an environmental condition of the building in accordance with the values of the control decision variables corresponding to a selected set of the optimization results.

12 . A building management system (BMS) for executing an indoor air quality (IAQ) analysis of a building, the BMS comprising:
a controller comprising memory and one or more processors configured to:
obtain IAQ data from one or more sensors within the building, wherein the IAQ data is associated with an environment species;
obtain building automation system (BAS) data;
identify occupancy and ventilation rate as a plurality of unknown parameters from the IAQ data and BAS data the environment species;
estimate the occupancy and the ventilation rate based on inputting the IAQ data and the BAS data into an optimization model, and wherein the optimization model analyzes predicted concentrations of the environment species subject to the environment species evolving according to a single-species concentration model; and
provide the estimated occupancy and estimated ventilation rate to one or more predictive models configured to predict values of a control objective for one or more building zones as a function of control decision variables for HVAC equipment.

13 . The BMS of claim 12 , wherein the single-species concentration model is an ordinary differential equation model, and wherein the environment species is subject to the environment species evolving according to the single-species concentration model using one or more basis function expansions of the plurality of unknown parameters.

14 . The BMS of claim 12 , wherein the optimization model comprises an objective function, and wherein the objective function is minimized by adjusting the plurality of unknown parameters according to the predicted concentrations approximately matching one or more measured time series concentrations.

15 . The BMS of claim 12 , the one or more processors further configured to:
operate HVAC equipment to affect an environmental condition of the building in accordance with a selected set of the optimization results from the one or more predictive models.

16 . The BMS of claim 12 , the one or more processors further configured to:
in response to estimating the occupancy and the ventilation rate, modify a control strategy for the one or more building zones based on improving a value of the predicted values.

17 . A computer-implemented method for executing an indoor air quality (IAQ) analysis of a building, the computer-implemented method comprising:
obtaining, by a processing circuit, IAQ data from one or more sensors within the building, wherein the IAQ data is associated with at least one of a plurality of environment species; obtaining, by the processing circuit, building automation system (BAS) data; identifying, by the processing circuit, one or more unknown parameters from the IAQ data and BAS data of two or more of

Assignees

• Johnson Controls Tyco IP Holdings LLP

Inventors

• Risbeck Michael J
• Lee Young M
• Douglas Jonathan D
• Bazant Martin Z

Classifications

• F24F11/63 Primary

  Electronic processing · CPC title

• G05B19/042

  using digital processors (G05B19/05 takes precedence) · CPC title

• G05B2219/2614

  HVAC, heating, ventillation, climate control · CPC title

• Y02B30/70

  Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating · CPC title

• F24F2110/70

  Carbon dioxide · CPC title