Hvac system with building infection control

Patent metadata

Field	Value
Publication number	US-2021011444-A1
Application number	US-202016927759-A
Country	US
Kind code	A1
Filing date	Jul 13, 2020
Priority date	Jul 12, 2019
Publication date	Jan 14, 2021
Grant date	—

Abstract

A heating, ventilation, or air conditioning (HVAC) system for one or more building zones includes airside HVAC equipment operable to provide clean air to the one or more building zones and a controller. The controller is configured to obtain a dynamic temperature model and a dynamic infectious quanta model for the one or more building zones, determine an infection probability, and generate control decisions for the airside HVAC equipment using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability.

First claim

What is claimed is:

1 . A heating, ventilation, or air conditioning (HVAC) system for one or more building zones, the HVAC system comprising:
airside HVAC equipment operable to provide clean air to the one or more building zones; and a controller configured to:
obtain a dynamic temperature model and a dynamic infectious quanta model for the one or more building zones;
determine an infection probability; and
generate control decisions for the airside HVAC equipment using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability.

2 . The HVAC system of claim 1 , wherein the airside HVAC equipment comprises:
disinfection lighting operable to disinfect the clean air before it is provided to the one or more building zones; and one or more filters configured to filter the clean air before it is provided to the one or more building zones.

3 . The HVAC system of claim 1 , wherein the controller is configured to receive a desired level of disinfection via a user interface and generate a threshold value for the infection probability using the desired level of disinfection.

4 . The HVAC system of claim 1 , wherein the controller is configured to obtain a dynamic humidity model for the one or more building zones and use the dynamic humidity model, in addition to the dynamic temperature model and the dynamic infectious quanta model, to generate the control decisions.

5 . The HVAC system of claim 1 , wherein the one or more building zones comprise a plurality of building zones and the dynamic temperature model and the dynamic infectious quanta model are either:
individual dynamic models for each of the plurality of building zones; or. aggregate dynamic models for the plurality of building zones based on a weighted volume average of the plurality of zones.

6 . The HVAC system of claim 1 , wherein using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability to generate the control decisions comprises:
generating optimization constraints based on the dynamic temperature model, the dynamic infectious quanta model, and the infection probability; and performing an optimization of an objective function subject to the optimization constraints to generate the control decisions as results of the optimization.

7 . A controller for a heating, ventilation, or air conditioning (HVAC) system 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 a dynamic temperature model and a dynamic infectious quanta model for one or more building zones of the building;
determining an infection probability;
generating control decisions using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability; and
using the control decisions to operate at least one of disinfection lighting, a variable air volume (VAV) unit, or an air handling unit (AHU) of the HVAC system.

8 . The controller of claim 7 , wherein the controller is configured to receive a desired level of disinfection via a user interface and generate a threshold value for the infection probability using the desired level of disinfection.

9 . The controller of claim 7 , wherein the control signals are generated using a constraint on infectious quanta concentration based on a Wells-Riley Equation.

10 . The controller of claim 7 , wherein the operations further comprise:
obtaining a dynamic humidity model for the one or more building zones; and using the dynamic humidity model, in addition to the dynamic temperature model and the dynamic infectious quanta model, to generate the control decisions.

11 . The controller of claim 7 , wherein the one or more building zones comprise a plurality of building zones and the dynamic temperature model and the dynamic infectious quanta model are either:
individual dynamic models for each of the plurality of building zones; or. aggregate dynamic models based on a weighted volume average of the plurality of building zones.

12 . The controller of claim 7 , wherein using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability to generate the control decisions comprises:
generating optimization constraints based on the dynamic temperature model, the dynamic infectious quanta model, and the infection probability; and performing an optimization of an objective function subject to the optimization constraints to generate the control decisions as results of the optimization.

13 . The controller of claim 7 , wherein the control decisions indicate an amount of clean air to be provided to the one or more building zones and using the control decisions to operate the VAV unit comprises:
generating both a temperature setpoint and a minimum airflow constraint for the VAV unit, the minimum airflow constraint based the amount of clean air to be provided to the one or more building zones; and operating the VAV unit to control a temperature of the one or more building zones based on the temperature setpoint, subject to the minimum airflow constraint.

14 . A method for controlling building equipment to provide a desired level of disinfection, the method comprising:
obtaining a dynamic temperature model and dynamic infectious quanta model for one or more building zones; determining an infection probability; generating control decisions using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability; and using the control decisions to operate the building equipment to provide the amount of clean air to the one or more building zones.

15 . The method of claim 14 , wherein using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability to generate the control decisions comprises:
generating optimization constraints based on the dynamic temperature model, the dynamic infectious quanta model, and the infection probability; and performing an optimization of an objective function subject to the optimization constraints to generate the control decisions as results of the optimization

16 . The method of claim 14 , wherein the controller is configured to receive the desired level of disinfection via a user interface and generate a threshold value for the infection probability using the desired level of disinfection.

17 . The method of claim 14 , further comprising:
obtaining a dynamic humidity model for the one or more building zones; and using the dynamic humidity model, in addition to the dynamic temperature model and the dynamic infectious quanta model, to generate the control decisions.

18 . The method of claim 14 , wherein the one or more building zones comprise a plurality of building zones and the dynamic temperature model and the dynamic infectious quanta model are either:
individual dynamic models for each of the plurality of building zones; or aggregate dynamic models based on a weighted volume average of the plurality of building zones.

19 . The method of claim 14 , wherein the building equipment comprise at least one of disinfection lighting, a filter, an air handling unit (AHU), or a variable air volume (VAV) unit.

20 . The method of claim 19 , wherein the control decisions comprise at least one of commands to actuate the disinfection lighting between an on state and an off state, a fre

Assignees

• Johnson Controls Tech Co

Inventors

• Risbeck Michael J
• Drees Kirk H
• Douglas Jonathan D

Classifications

• F24F11/64 Primary

  using pre-stored data · CPC title

• F24F8/10

  by separation, e.g. by filtering · CPC title

• G05B19/042 Primary

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

• F24F11/47

  Responding to energy costs · CPC title

• F24F8/22

  using UV light · CPC title