Method and apparatus for determining a thermal setpoint in a HVAC system

• US 6,145,751 A
• Filed: 01/12/1999
• Issued: 11/14/2000
• Est. Priority Date: 01/12/1999
• Status: Expired due to Term

• Current Assignee: Thermo Dynamic Solutions LLC (IPValuation Partners, LLC)
• Original Assignee: Siemens Building Technologies Incorporated (Siemens AG)
• Inventors: Ahmed, Osman
• Primary Examiner(s): WAYNER, WILLIAM E
• Application Number:
  US09/228,428
• Time in Patent Office: 672 Days
• Field of Search: 236/51, 236/78 B, 165/208, 165/209, 165/254, 374/115
• US Class Current: 236/51
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 2110/10 Temperature
• CPC Class Codes: F24F 2120/20 Feedback from users
• CPC Class Codes: G05D 23/1919 characterised by the type of controller

Abstract

The present invention discloses methods for determining setpoint information in a HVAC system. Setpoint values are determined using occupant feedback provided by individual occupants over at least one of an Internet or Intranet communications network. According to a first aspect of the invention a setpoint is determined using fuzzy logic. According to a second aspect, historical setpoint data determined using occupant feedback is used to develop a neural network for predicting setpoint values.

Claims

1. A method for adjusting a thermostat setpoint for controlling the temperature of a space controlled by an HVAC system using feedback information provided by individual occupants located in the space, comprising the steps of:

(a) transmitting feedback information from plural occupants to a CPU over at least one of an Internet and Intranet communications network;

(b) calculating an average feedback temperature value; and

(c) adjusting the thermostat setpoint based on said calculated average value.

2. A method for calculating a new thermal setpoint for controlling the temperature of a space controlled by an HVAC system using the existing thermal setpoint and subjective thermal comfort (fuzzy) feedback information provided by one or more individual occupants, comprising:

(a) transmitting thermal comfort (fuzzy) feedback from plural occupants to a CPU over at least one of an Internet and Intranet communications network, wherein said thermal comfort feedback is selected from a predetermined number of thermal comfort perception sets (fuzzy sets), each said thermal comfort perception set being assigned a predetermined value;

(b) converting the thermal comfort (fuzzy) feedback received from occupants of a given heating/cooling zone into a numerical (crisp) room air temperature value T* using a defuzzification process wherein said crisp room air temperature value T* is determined as a weighted average of the thermal comfort feedback; and

(c) calculating the new thermal setpoint using a temperature difference (T_d) between the crisp room air temperature T* and the existing thermal setpoint.

3. The method according to claim 2, wherein in step (b) the crisp room air temperature value T* is calculated using a center of area approach

4. The method according to claim 2, wherein in step (b) the crisp room air temperature value T* is calculated by determining a centroid approach wherein T*=(∫

Tda)/A,

where each occupant'"'"'s thermal comfort feedback is expressed as one of a predefined number of fuzzy sets, each set having a predetermined temperature range which overlaps with an adjacent set,

where A represents a sum of areas of the pre defined number of sets, the area of each set being truncated in relation to a percentage of feedback, and ∫

Tda represents the integral of the product of the temperature T and differential area da of the truncated sets.

5. The method according to claim 2, wherein in step (c) the new thermal setpoint is determined from the temperature difference (T_d) using a linear rule.

6. The method according to claim 2, wherein in step (c) the new thermal setpoint (TS) is determined from the temperature difference (T_d) using fuzzy logic approach, comprising the steps of:

(c-1) reading at least one weighing factor (w_n) from a look-up table using the temperature difference (T_d);

(c-2) calculating a thermal setpoint (TS) using one of a center of area approach and a centroid approach, wherein;

the center of area approach is determined;

TS=Σ

(w_n Td_n)/Σ

w_n, and

the centroid approach is determined;

TS=(∫

T_d da)/A,

where each occupant'"'"'s thermal comfort feedback is expressed as one of a predefined number of sets, each set having a predetermined temperature range which overlaps with an adjacent set,

where A represents a sum of areas of the predefined number of sets, the area of each set being truncated in relation weighing factor w_n corresponding to a percentage of occupant feedback set n, ∫

Tda representing the integral of the product of the temperature T and differential area da of the truncated sets, Td_n is a predetermined center temperature of set n, and n is the number of fuzzy sets.

7. A method for calculating a new thermal setpoint for a PMV sensor controlling the thermal comfort of a space in an HVAC system using the existing thermal setpoint and subjective (fuzzy) feedback information, comprising:

(a) receiving feedback information including fuzzy feedback information over at least one of an Internet and Intranet communications network, wherein said fuzzy feedback includes thermal comfort perception selected from a predetermined number of thermal comfort perception sets (fuzzy sets), each said thermal comfort perception set being assigned a predetermined value;

(b) converting the fuzzy feedback received from occupants of a given heating/cooling zone into crisp numerical values, including room air temperature value T*, using a defuzzification process wherein said crisp values are determined as a weighted average of the fuzzy feedback; and

(c) calculating a PMV setpoint value for the PMV sensor using the crisp values.

8. The method according to claim 7, further wherein the feedback information includes items of information selected from the group consisting of (thermal comfort sensation, draft sensation, humidity sensation, description of occupant activity, and description of clothing), and in step (c) the defuzzification process uses at least one of a lookup table, center of area approach and centroid approach.

9. A control system for adjusting a thermostat setpoint for controlling the temperature of a space controlled by an HVAC system using occupant feedback comprising:

a software interface for entering occupant feedback;

means for transmitting the occupant feedback;

a CPU for receiving feedback information from said transmitting means, wherein said CPU calculates an adjusted thermostat setpoint using a previous thermostat setpoint and the occupant feedback information.

10. The control system of claim 9, wherein said transmitting means includes at least one of an Internet and Intranet communications network.

11. The control system of claim 10, wherein said software interface is a web page on the Internet, and the occupant feedback includes thermal comfort information.

12. A control system for adjusting a PMV sensor setpoint for controlling the temperature of a space controlled by an HVAC system using occupant feedback comprising:

a software interface for entering occupant feedback;

means for transmitting the occupant feedback;

a CPU for receiving feedback information from said transmitting means, wherein said CPU calculates an adjusted PMV setpoint using a previous PMV setpoint and the occupant feedback information.

13. The control system of claim 12, wherein said transmitting means includes at least one of an Internet and Intranet communications network.

14. The control system of claim 13, wherein said software interface is a web based interface on the Internet, and the occupant feedback includes thermal comfort information.

15. An adaptive method for predicting a setpoint for controlling the temperature of a space controlled by an HVAC system using historical data, comprising the steps:

(a) compiling historical data including setpoint data and identification data identifying prevailing characteristics when said setpoint data was determined, wherein said setpoint data includes at least one of thermal setpoint and PMV setpoint data, and said identification data includes time of day, day of week, outside air temperature, and outside humidity;

(b) determining a regression relationship between each said item of setpoint data and its associated identification information using regression analysis; and

(c) predicting a thermal setpoint in real-time using said regression relationship based on input information including time of day, day of week, outside air temperature, and outside humidity.

16. The adaptive method according to claim 15, wherein said regression relationship in step (b) is determined using a general regression neural network.

17. The adaptive method according to claim 15, wherein the historical setpoint data was determined using fuzzy feedback received from occupants of a given heating/cooling zone.