(12) United States Patent
`Steinberg et al.
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 8,751,186 B2
`*Jun. 10, 2014
`
`USOO8751 186B2
`
`(54)
`
`(71)
`(72)
`
`(73)
`(*)
`
`(21)
`(22)
`(65)
`
`(63)
`
`(60)
`
`(51)
`
`(52)
`
`(58)
`
`Applicant: EcoFactor, Inc., Millbrae, CA (US)
`Inventors: John Douglas Steinberg, Millbrae, CA
`(US); Scott Douglas Hublou, Redwood
`City, CA (US)
`Assignee: EcoFactor, Inc., Millbrae, CA (US)
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 0 days.
`This patent is Subject to a terminal dis
`claimer.
`
`Notice:
`
`Appl. No.: 13/858,710
`Filed:
`Apr. 8, 2013
`
`Prior Publication Data
`US 2013/023.1785 A1
`Sep. 5, 2013
`
`Related U.S. Application Data
`Continuation of application No. 13/409,729, filed on
`Mar. 1, 2012, which is a continuation of application
`No. 12/959,225, filed on Dec. 2, 2010, now Pat. No.
`8, 131,497, which is a continuation of application No.
`12/21 1,733, filed on Sep. 16, 2008, now Pat. No.
`7,848,900.
`Provisional application No. 60/994.011, filed on Sep.
`17, 2007.
`
`(2006.01)
`
`Int. C.
`GOID L/00
`U.S. C.
`USPC ........................................... 702/130; 702/182
`Field of Classification Search
`USPC .................. 702/130, 182; 700/276, 277,278;
`236/91 D; 165/58, 200, 287
`See application file for complete search history.
`
`SYSTEMAND METHOD FOR CALCULATING
`THE THERMAL MASS OF A BUILDING
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`4,136,732 A
`4,341,345 A
`
`1/1979 Demaray et al.
`7, 1982 Hammer et al.
`(Continued)
`
`FOREIGN PATENT DOCUMENTS
`
`EP
`JP
`
`3, 1991
`O415747
`7, 1993
`05-189659
`(Continued)
`
`OTHER PUBLICATIONS
`
`U.S. Appl. No. 13/523,697, Jun. 14, 2012, Hublou, Scott Douglas et
`al.
`
`(Continued)
`
`Primary Examiner — Elias Desta
`(74) Attorney, Agent, or Firm — Knobbe, Martens, Olson &
`Bear, LLP
`
`(57)
`ABSTRACT
`The invention comprises a system for calculating a value for
`the effective thermal mass of a building. The climate control
`system obtains temperature measurements from at least a first
`location conditioned by the climate system. One or more
`processors receive measurements of outside temperatures
`from at least one source other than the control system and
`compare the temperature measurements from the first loca
`tion with expected temperature measurements. The expected
`temperature measurements are based at least in part upon past
`temperature measurements obtained by said HVAC control
`system and said outside temperature measurements. The pro
`cessors then calculate one or more rates of change in tem
`perature at said first location.
`
`13 Claims, 13 Drawing Sheets
`
`PUT OTSE
`CAE AA
`
`wa
`
`its
`OY CYCLE ASA
`
`NR PRR Nse-A
`kiPERARE DAA
`
`iPT
`BUILDING/USER
`PROFE
`
`Yas
`
`INPUT cuRRET
`INSE
`EPERATURE
`
`Yi
`
`ACIATE
`ERA ASS
`NEX
`
`f
`
`Er'
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`US 8,751,186 B2
`Page 2
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`9, 1983 Hebert
`4,403,644 A
`4,475,685. A 10/1984 Grimado et al.
`4655.279 A
`4, 1987 Harmon
`4.674.027 A
`6/1987 Beckey
`5,244,146 A
`9, 1993 Jefferson et al.
`5,270,952 A 12/1993 Adams et al.
`53 14,004 A
`5, 1994 Strand et al.
`5,462,225. A 10/1995 Massara et al.
`5,544,036 A
`8, 1996 Brown et al.
`5,555,927 A
`9, 1996 Shah
`5,572.438 A 11/1996 Ehlers et al.
`5,682,949 A 1 1/1997 Ratcliffe et al.
`5,717.606 A
`2f1998 Packa et al.
`5,729.474. A * 3/1998 Hildebrand et al. .......... 7OO/276
`5,818,347 A 10, 1998 Dolan et al.
`5,977.964. A 1 1/1999 Williams et al.
`6,115,713 A
`9, 2000 Pascucci et al.
`6,145,751 A 11/2000 Ahmed
`6,178,362 B1
`1/2001 Woollard et al.
`6,241,156 B1* 6/2001 Kline et al. .................. 236/49.3
`6,260.765 B1
`7, 2001 Natale et al.
`6.351,693 B1
`2/2002 Monie
`6,400,996 B1
`6/2002 Hoffberg et al.
`6,437,692 B1
`8, 2002 Petite et al.
`6,478,233 B1
`1 1/2002 Shah
`6,480,803 B1
`1 1/2002 Pierret et al.
`6,483,906 B1
`1 1/2002 Lggulden et al.
`6,536,675 B1
`3/2003 Pesko et al.
`6,542,076 B1
`4/2003 Joao
`6.549,130 B1
`4/2003 Joao
`6574537 B2
`6/2003 KiperSztok et al.
`6,580,950 B1
`6, 2003 Johnson
`6,594,825 B1
`7/2003 Goldschmidtiki et al.
`6,595,430 B1
`7, 2003 Shah
`6,598,056 B1
`7/2003 Hull et al.
`6.619,555 B2
`9, 2003 Rosen
`6,622,097 B2
`9/2003 Hunter
`66221 15 B1
`9, 2003 Brown et al.
`6622,925 B2
`9, 2003 Carner et al.
`6,622.926 B1
`9, 2003 Sartain et al.
`6628.997 B1
`9/2003 Foxetal.
`6.633.823 B2 10/2003 Bartone et al.
`6643,567 B2
`1/2003 Kolketal
`6671586 B2 12/2003 Davis et al.
`6.695.218 B2
`2/2004 Fleckenstein
`6,726.113 B2
`4/2004 Guo
`6.731992 B1
`5/2004 Ziegler
`6,734,806 B1
`5/2004 Cratsley
`6,772,052 B1
`8/2004 Amundsen
`6,785.50 B1
`8/2004 Smith
`6,785,630 B2
`& 2004 Kolk
`6,786.42 B2
`9/2004 Rosen
`6,789.739 B2
`92004 Rosen
`6.853,959 B2
`2/2005 Ikeda et al.
`6868,293 B1
`3/2005 Schur
`68683 19 B2
`3/2005 KiperSztok et al.
`6,882,712 B1
`4/2005 Iggulden et al.
`6,889,908 B2
`5/2005 Crippen et al.
`6,891,838 B1
`5, 2005 Petite et al.
`6,912,429 B1
`6/2005 Bilger
`6.991,029 B2
`1/2006 Orfield et al.
`7,009.493 B2
`3/2006 Howard
`7031880 B1
`4/2006 seem et al.
`7039532 B2
`5/2006 Hunter
`7061393 B2
`6/2006 Buckingham et al.
`7,089,088 B2
`8/2006 Terry et al.
`7,130,719 B2 10/2006 Ehlers et al.
`7,130,832 B2 10/2006 Bannai et al.
`H2176 H
`12/2006 Meyer et al.
`7,167,079 B2
`1/2007 Smyth et al.
`7,187,986 B2
`3/2007 Johnson et al.
`7,205,892 B2
`4/2007 Luebke et al.
`7,215,746 B2
`5/2007 Iggulden et al.
`7,216,015 B2
`5/2007 Poth
`7,231,424 B2
`6, 2007 Bodin et al.
`
`6/2007 Rosen
`7,232,075 B1
`7/2007 Hoffberg et al.
`7,242.988 B1
`8, 2007 Schlack et al.
`7,260,823 B2
`4/2008 Gull et al.
`7,356,384 B2
`1/2009 Jackson et al.
`7,483,964 B1
`1/2010 Hoglund et al.
`7,644,869 B2
`8/2010 Harter
`7,784,704 B2
`7,848,900 B2 12/2010 Steinberg et al.
`7,894,943 B2
`2/2011 Sloup et al.
`7,908,116 B2
`3/2011 Steinberg et al.
`7,908,117 B2
`3/2011 Steinberg et al.
`8,010,237 B2
`8/2011 Cheung et al.
`8,019,567 B2
`9/2011 Steinberg et al.
`8,090.477 B1
`1/2012 Steinberg
`8, 131497 B2
`3/2012 Steinberg et al.
`8,131.506 B2
`3/2012 Steinberg et al.
`8, 180,492 B2
`5/2012 Steinberg
`8,340,826 B2 12/2012 Steinberg
`8,412,488 B2
`4/2013 Steinberg et al.
`8,423.322 B2
`4/2013 Steinberg et al.
`8.457,797 B2
`6/2013 Imes et al.
`2003/004.0934 A1
`2/2003 Skidmore et al.
`2004/0176880 A1
`9, 2004 Obradovich et al.
`2005/0222889 A1 10, 2005 Lai et al.
`2005/0288822 A1 12/2005 Rayburn
`2006/0045105 A1
`3/2006 DobOSZ et al.
`2006/0214014 A1
`9, 2006 Bash et al.
`2007/0043477 A1
`2/2007 Ehlers et al.
`2007/0045431 A1
`3/2007 Chapman et al.
`2007/0146126 A1
`6/2007 Wang
`2008, 0083234 A1
`4/2008 Krebs et al.
`2008. O198549 A1
`8/2008 Rasmussen et al.
`2008/0281472 A1 1 1/2008 Podgorny et al.
`2009/0052859 A1
`2/2009 Greenberger et al.
`2009.00996.99 A1
`4/2009 Steinberg et al.
`2009.0125151 A1
`5/2009 Steinberg et al.
`2009/024038 Al
`9, 2009 Lane
`2009,028.1667 A1 11/2009 Masui et al.
`2010/0019052 A1
`1/2010 Yip
`2010, 0070.086 A1
`3/2010 Harrod et al.
`2010, 0070089 A1
`3, 2010 Harrod et al.
`2010.007OO93 A1
`3/2010 Harrod et al.
`2010.0156608 A1
`6, 2010 Bae et al.
`2010, 0162285 A1
`6, 2010 Cohen et al.
`2010/0211224 A1
`8/2010 Keeling et al.
`2010. 0235004 A1
`9, 2010 Thind
`2010/0282857 A1 1 1/2010 Steinberg
`2010/0289643 A1 11/2010 Trundle et al.
`2010/0308119 A1 12/2010 Steinberg et al.
`2010/0318227 A1 12/2010 Steinberg et al.
`2011 OO31323 A1
`2/2011 Nold et al.
`2011, 0046792 A1
`2/2011 Imes et al.
`2011, 0046798 A1
`2/2011 Imes et al.
`2011/0046799 A1
`2/2011 Imes et al.
`2011/0046800 A1
`2/2011 Imes et al.
`2011/0046801 A1
`2/2011 Imes et al.
`2011/0051823 A1
`3/2011 Imes et al.
`2011/0054699 A1
`3/2011 Imes et al.
`2011/005471.0 A1
`3/2011 Imes et al.
`2011/0224838 A1
`9, 2011 Imes et al.
`2011/0246898 A1 10, 2011 Imes et al.
`2011/0290893 Al 12/2011 Steinberg
`2011/0307101 All
`12/2011 Imes et al.
`2011/0307103 Al 12/2011 Cheung et al.
`2012fOO23225 A1
`1/2012 Imes et al.
`2012/0046859 A1
`2/2012 Imes et al.
`2012/0064923 A1
`3/2012 Imes et al.
`2012/0065935 A1
`3/2012 Steinberg et al.
`2012fOO72O33 A1
`3/2012 Imes et al.
`2012fOO86562 A1
`4/2012 Steinberg
`2012/0093141 A1
`4/2012 Imes et al.
`2012/0101637 A1
`4/2012 Imes et al.
`2012/0135759 A1
`5, 2012 Imes et al.
`2012/01583.50 A1
`6/2012 Steinberg et al.
`2012fO215725 A1
`8, 2012 Imes et al.
`2012fO221151 A1
`8/2012 Steinberg
`2012fO221718 A1
`8, 2012 Imes et al.
`2012fO252430 A1 10, 2012 Imes et al.
`2012/0324119 A1 12/2012 Imes et al.
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`US 8,751,186 B2
`Page 3
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`2013,0053054 A1
`2013,0054758 A1
`2013,0054863 A1
`2013, OO60387 A1
`2013, O144445 A1
`2013, O144453 A1
`2013,0167035 A1
`2013,0238143 A1
`2013,0310989 A1
`
`2/2013 Lovitt et al.
`2/2013 Imes et al.
`2/2013 Imes et al.
`3/2013 Imes et al.
`6/2013 Steinberg
`6, 2013 Subbloie
`6, 2013 Imes et al.
`9/2013 Steinberg et al.
`11/2013 Steinberg et al.
`
`FOREIGN PATENT DOCUMENTS
`
`2010-038377
`JP
`2010-286218
`JP
`10-1994-001 1902
`KR
`10-1999-0070368
`KR
`10-2000-0059.532
`KR
`WO WO 2011, 149600
`WO WO 2012/O24534
`
`2, 2010
`12/2010
`6, 1994
`9, 1999
`10, 2000
`12/2011
`2, 2012
`
`OTHER PUBLICATIONS
`
`U.S. Appl. No. 13/725,447. Dec. 21, 2012, Steinberg, John Douglas.
`Arens, et al., “How Ambient Intelligence Will Improve Habitability
`and Energy Efficiency in Buildings”, 2005, researchpaper, Centerfor
`the Built Environment, Controls and Information Technology.
`Bourhan, et al., “Cynamic model of an HVAC system for control
`analysis”. Elsevier 2004.
`Comverge SuperStat Flyer, prior to Jun. 28, 2007.
`Control4 Wireless Thermostat Brochure, 2006.
`Cooper Power Systems Web Page, 2000-2009.
`Emerson Climate Technologies, “Network Thermostat for E2 Build
`ing Controller Installation and Operation Manual”. 2007.
`Enernoc Web Page, 2004-2009.
`Enerwise Website, 1999-2009.
`Honeywell Programmable Thermostat Owner's Guide, www.
`honeywell.com/yourhome, 2004.
`Honeywell, W7600/W7620 Controller
`HW 0021207, Oct. 1992.
`
`Reference Manual,
`
`Johnson Controls, “T600HCX-3 Single-Stage Thermostats', 2006.
`Johnson Controls, Touch4 building automation system brochure,
`2007.
`Kilicotte, et al., “Dynamic Controls for Energy Efficiency and
`Demand Response: Framework Concepts and a New Construction
`Study Case in New York”. Proceedings of the 2006 ACEEE Summer
`Study of Energy Efficiency in Buildings, Pacific Grove. CA, Aug.
`13-18, 2006.
`Lin, et al., “Multi-Sensor Single-Actuator Control of HVAC Sys
`tems', 2002.
`Pier, Southern California Edison, Demand Responsive Control of Air
`Conditioning via Programmable Communicating Thermostats Draft
`Report, 2006.
`Proliphix. Thermostat Brochure, prior to Jun. 2007.
`Raji, "SmartNetworks for Control', IEEE Spectrum, Jun. 1994.
`Wang, et al., “Opportunities to Save Energy and Improve Comfort by
`Using Wireless Sensor Networks in Buildings.” (2003), Center for
`Environmental Design Research.
`Wetter, et al. A comparison of deterministic and probabilistic opti
`mization algorithms for nonsmooth simulation-based optimization.
`Building and Environment 39, 2004, pp. 989-999.
`Written Opinion and Search Report for PCT/US2011/032537, dated
`Dec. 12, 2011.
`U.S. Appl. No. 13/470,074, Aug. 30, 2012, Steinberg.
`U.S. Appl. No. 13/852,577, Mar. 28, 2013, Steinberg et al.
`U.S. Appl. No. 13/858,710, Sep. 5, 2013, Steinberg et al.
`U.S. Appl. No. 13/861,189, Apr. 11, 2013, Steinberg et al.
`Brush, et al., Preheat—Controlling Home Heating with Occupancy
`Prediction, 2013.
`Gupta, Adding GPS-Control to Traditional Thermostats: An Explo
`ration of Potential Energy Savings and Design Challenges, MIT,
`2009.
`Gupta, et al., A Persuasive GPS-Controlled Thermostat System, MIT,
`2008.
`Krumm, et al., Learning Time-Based Presence Probabilities, Jun.
`2011.
`Scott, et al., Home Heating Using GPS-Based Arrival Prediction,
`2010.
`International Search Report and Written Opinion for PCT/US2013/
`035726, dated Aug. 6, 2013.
`* cited by examiner
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`U.S. Patent
`
`Jun. 10, 2014
`Jun. 10, 2014
`
`Sheet1 of 13
`Sheet 1 of 13
`
`US 8,751,186 B2
`US 8,751,186 B2
`
`
`
`HIG.Lf
`
`PETITIONER GOOGLE EX. 1017
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 2 of 13
`
`US 8,751,186 B2
`
`
`
`DATABASE
`
`UT TY
`
`DEMAND REDUCTION
`SERVICE SERVERS
`
`A/2 2
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 3 of 13
`
`US 8,751,186 B2
`
`(2/2,
`
`
`
`
`
`HOd po?uuoo dog dn ufils
`
`[…]] 00:
`
`
`
`[II Gg] mayor);
`
`kubnupp
`
`37222°
`
`Effffffffffffffffffffffffff?
`##############
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 4 of 13
`
`US 8,751,186 B2
`US 8,751,186 B2
`
`YNNGINY
`
`
`
`A¥IdSIG
`
`SSTTAIM
`
`W3d0N
`
`O9E7ISS7
`Ht|Aiddfis||WUMOdAYOWAWN
`
`Ž 29/2/
`
`S3HOLIMS
`
`YOLSINGAHL
`
`YOSSIIONOAIIN
`
`CSE
`
`PETITIONER GOOGLE EX. 1017
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 5 of 13
`
`US 8,751,186 B2
`
`%22
`
`400
`
`62
`(7
`
`622
`
`TEMPERATURE
`
`THERMOSTAT SETTINGS
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`C in house C is 327
`
`HVAC HARDWARE
`
`722
`
`9/2
`
`/(22
`
`f7(72
`
`TRANSACTION
`
`PRODUCT & SERVICE
`
`A 2
`
`
`
`
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 6 of 13
`
`US 8,751,186 B2
`
`
`
`12
`
`6 AM
`
`12 Noon 6 PM
`
`2
`
`A76, 64
`
`
`
`12
`
`6 AM
`
`12 Noon 6 PM
`
`12
`
`AZ2 (1A
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 7 of 13
`
`US 8,751,186 B2
`
`12
`
`6 AM
`
`2 Noon
`
`6 PM
`
`12
`
`
`
`12
`
`6 AM
`
`12 Noon
`
`6 PM
`
`2
`
`A2. 27
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 8 of 13
`
`US 8,751,186 B2
`
`12.
`
`6 AM
`
`2 Noon
`
`6 PM
`
`12
`
`
`
`A76, 5A
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 9 of 13
`
`US 8,751,186 B2
`
`
`
`522
`
`12
`
`6 AM
`
`12 Noon 6 PM
`
`12
`
`AV6 24
`
`
`
`12
`
`6 AM
`
`12 Noon 6 PM
`
`12
`
`AV2 2A
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 10 of 13
`
`US 8,751,186 B2
`
`95
`
`90
`
`85
`
`75
`
`70
`
`65
`
`12?
`
`2
`
`6 AM
`
`2 Noon
`
`6 PM
`
`12
`
`AV6
`
`(24
`
`95
`
`90
`
`85
`
`80
`
`122
`
`2227
`
`75 Nu-1-?-N-
`
`70
`
`65
`
`2
`
`6 AM
`
`12 Noon
`
`6. PM
`
`12
`
`AV6 (02A
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 11 of 13
`
`US 8,751,186 B2
`
`NPUT OUTSDE
`CLIMAE DATA
`
`f/22
`
`INPUT HVAC
`DUTY CYCLE DAA
`
`NPUT PROR NSIDE
`EMPERATURE DATA
`
`NPUT
`BUILDING/USER
`PROFELE
`
`NPUT CURRENT
`NSIDE
`TEMPERATURE
`
`f/7/2
`
`CALCUATE
`HERMAL MASS
`NDEX
`
`7/72
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`A76, MA
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 12 of 13
`
`US 8,751,186 B2
`
`INPUT OUTSDE - /22
`CLIMATE DATA
`
`INPUT HVAC
`DUTY CYCLE DATA
`
`7224
`
`NPUT INSIDE
`EMPERATURE DATA
`
`A2.2%
`
`NPUT PROFE DATA
`
`22
`
`
`
`
`
`
`
`
`
`MATCH COGGE)
`FLTER PATTERN
`
`
`
`REPORT
`CLOGGED
`FTER
`
`
`
`M222
`DOES PATTERN
`MATCH REFRIGERANT
`LEAK
`
`YES
`
`224
`
`REPORT
`COOAN LEAK
`
`NO
`
`DOES PATTERN
`MATCH OPEN
`WINDOW/DOOR
`
`YES REPORT OPEN
`WINDOW/DOOR
`
`NPUT
`COMPARATIVE DATA
`
`72/7
`
`NO
`
`
`
`
`
`W227
`
`725?
`
`CALCULATE
`RELATIVE
`EFFICIENCY
`
`fay2
`
`DOES
`PATTERNMATCH)YES PSE
`
`PROBLEM n
`
`n
`
`NO
`
`f2/?
`
`NO
`
`f276
`END
`
`REPORT UNKNOWN - 725?
`PROBEM
`
`
`
`
`
`AS RELATIV
`EFFICIENCY
`CHANGED
`
`YES
`
`A76, M2
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`U.S. Patent
`
`Jun. 10, 2014
`
`Sheet 13 of 13
`
`US 8,751,186 B2
`
`INPUT OUTSIDE 1752?
`CLIMATE DATA
`
`INPUT HVAC
`DUTY CYCLE DATA
`
`f24
`
`NPUT INSIDE
`TEMPERATURE DATA
`
`f326
`
`INPUT PROFILE DATA
`
`f32?
`
`NPUT HISTORICAL DAA f
`
`77
`
`NPUT SOLAR
`PROGRESSION DATA
`
`f(7
`
`
`
`
`
`
`
`DOES PATTERN
`CORRELATE WITH HISTORICANNO
`AND SOLAR PROGRESSION
`DATA
`p
`
`75,24
`
`INPUT
`COMPARAVE DATA
`
`57(2
`
`
`
`CALCULATE EXPECTED - ?ize
`INSIDE TEMPERATURE
`READING
`
`
`
`f74
`
`
`
`
`
`DOES INSIDE
`TEMPERATURE READING
`DVERGE FROM
`REDICrp WALUE
`
`YES
`
`//A
`END
`
`NO
`
`CALCULATE EXPECTED
`DURATION OF
`DISTORTION EVEN
`
`SET TARGET TEMPERATURE BASED
`ON CALCULATED DATA FOR
`DURATION OF DISTORTION EVENT
`
`SEND MESSAGE TO
`HOMEOWNER RE: PROBLEM
`
`
`
`M32
`
`A76, M7
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`US 8,751,186 B2
`
`1.
`SYSTEMAND METHOD FOR CALCULATING
`THE THERMAL MASS OF A BUILDING
`
`CROSS-REFERENCE TO RELATED
`APPLICATIONS
`
`This application is a continuation of U.S. patent applica
`tion Ser. No. 13/409,729, filed Mar. 1, 2012, which is a
`continuation of U.S. patent application Ser. No. 12/959,225,
`filed Dec. 2, 2010, now U.S. Pat. No. 8,131,497, issued on
`Mar. 6, 2012, which is a continuation of U.S. patent applica
`tion Ser. No. 12/21 1,733, filed Sep. 16, 2008, now U.S. Pat.
`No. 7,848,900, issued on Dec. 7.2010, which claims priority
`under 35 U.S.C. S 119(e) to U.S. Provisional Application No.
`60/994,011, filed Sep. 17, 2007, the entirety of each of which
`is hereby incorporated herein by reference and is to be con
`sidered part of this specification.
`
`10
`
`15
`
`BACKGROUND OF THE INVENTION
`
`2
`thermostats, they only have two input signals—ambient tem
`perature and the preset desired temperature. The entire
`advance with programmable thermostats is that they can shift
`between multiple present temperatures at different times.
`
`SUMMARY OF THE INVENTION
`
`There are many other sources of information that could be
`used to increase comfort, decrease energy use, or both. For
`example, outside temperature and humidity strongly affect
`subjective comfort. On a 95 degree, 90 percent humidity day
`in August, when people tend to dress in lightweight clothing,
`a house cooled to 70 degrees will feel cool or even uncom
`fortably cold. On a below-freezing day in January, when
`people tend to wear Sweaters and heavier clothes, that same
`70 degree home will feel too warm. It would therefore be
`advantageous for a thermostat system to automatically incor
`porate information about external weather conditions when
`setting the desired temperature.
`Thermostats are used to regulate temperature for the ben
`efit of the occupants in a given space. (Usually this means
`people, but it can of course also mean critical equipment, Such
`as in a room filled with computer equipment.) In general,
`thermostats read temperature from the sensor located within
`the “four corners' of the thermostat. With a properly designed
`system, the thermostat may well be located such that the
`temperature read at the precise location of the thermostat
`accurately reflects the conditions where the human (or other)
`occupants tend to be. But there are many reasons and circum
`stances in which that will not be the case. A single thermostat
`may produce accurate readings in Some circumstances but not
`others; it may be located in a place far from the occupants, or
`too far from the ductwork controlled by the thermostat, etc. In
`one house, for example, the thermostat may be located in a
`spot that receives direct Sunlightonhot afternoons. This could
`cause the thermostatto sense that the local ambient tempera
`ture is extremely high, and as a result signal the A/C to run too
`long, making the rest of the home too cold, and wasting
`considerable energy. In anotherhouse, the thermostat may be
`located in a hallway without ductwork or where the nearby
`ducts have been closed. In Such a scenario, the thermostat is
`likely to (correctly) report cold temperatures in the winter,
`leading the heating system to overheat the rest of the house
`and waste considerable energy.
`These problems can be reduced or eliminated through use
`of additional remote temperature sensors connected to the
`thermostat's control circuitry. However, Such systems require
`additional hardware, additional thermostat complexity, and
`skilled installation and configuration.
`It would therefore be desirable for a thermostat system
`using only a single temperature sensor to take Such Sub
`optimal installations into account and to correct for the erro
`neous readings generated by Such thermostats.
`Different structures will respond to changes in conditions
`Such as external temperature in different ways. For example,
`houses built 50 or more years ago will generally have little or
`no insulation, be poorly sealed, and have simple single-glazed
`windows. Such houses will do a very poor job of retaining
`internal heat in the winter and rejecting external heat in the
`Summer. In the absence of applications of thermal measures
`Such as heating and air conditioning, the inside temperature in
`such houses will trend to track outside temperatures very
`closely. Such houses may be said to have low thermal mass. A
`house built in recent years, using contemporary techniques
`for energy efficiency Such as high levels of insulation, double
`glazed windows and other techniques, will, in the absence of
`intervention, tend to absorb external heat and release internal
`
`PETITIONER GOOGLE EX. 1017
`
`25
`
`1. Field of the Invention
`This invention relates to the use of thermostatic HVAC
`controls that are connected to a computer network. More
`specifically, communicating thermostats are combined with a
`computer network to calculate the thermal mass of a struc
`ture.
`2. Background
`Climate control systems such as heating and cooling sys
`tems for buildings (heating, ventilation and cooling, or HVAC
`systems) have been controlled for decades by thermostats. At
`30
`the most basic level, a thermostat includes a means to allow a
`user to set a desired temperature, a means to sense actual
`temperature, and a means to signal the heating and/or cooling
`devices to turn on or offin order to try to change the actual
`temperature to equal the desired temperature. The most basic
`versions of thermostats use components such as a coiled
`bi-metallic spring to measure actual temperature and a mer
`cury Switch that opens or completes a circuit when the spring
`coils or uncoils with temperature changes. More recently,
`electronic digital thermostats have become prevalent. These
`thermostats use solid-state devices such as thermistors or
`thermal diodes to measure temperature, and microprocessor
`based circuitry to control the switch and to store and operate
`based upon user-determined protocols for temperature Vs.
`time.
`These programmable thermostats generally offer a very
`restrictive user interface, limited by the cost of the devices,
`the limited real estate of the small wall-mounted boxes, and
`the inability to take into account more than two variables: the
`desired temperature set by the user, and the ambient tempera
`ture sensed by the thermostat. Users can generally only set
`one series of commands per day, and in order to change one
`parameter (e.g., to change the late-night temperature) the user
`often has to cycle through several other parameters by repeat
`edly pressing one or two buttons.
`Because the interface of programmable thermostats is so
`poor, the significant theoretical savings that are possible with
`them (sometimes cited as 25% of heating and cooling costs)
`are rarely realized. In practice, studies have fund that more
`than 50% of users never program their thermostats at all.
`Significant percentages of the thermostats that are pro
`grammed are programmed Sub-optimally, in part because,
`once programmed, people tend to not to re-invest the time
`needed to change the settings very often.
`A second problem with standard programmable thermo
`stats is that they represent only a small evolutionary step
`beyond the first, purely mechanical thermostats. Like the first
`
`35
`
`40
`
`45
`
`50
`
`55
`
`60
`
`65
`
`

`

`3
`heat very slowly. The newerhouse can be thought of as having
`higher thermal mass than the older house.
`A conventional thermostat has no mechanism by which it
`might take the thermal mass of the structure into account, but
`thermal mass significantly affects many parameters relating
`to energy efficiency.
`The cost to an electric utility to produce power varies over
`time. Indeed, the cost of production between low demand and
`peak demand periods can vary by as much as an order of
`magnitude. Traditionally, residential customers paid the same
`price regardless of time or the cost to produce. Thus consum
`ers have had little financial incentive to reduce consumption
`during periods of high demand and high production cost.
`Many electric utilities are now seeking to bring various forms
`of variable rates to the retail energy markets. Under such
`schemes, consumers can reduce costs by taking into account
`not just how much energy they use, but when they use it.
`Thus many consumers now can see real benefits from opti
`mizing not just the total number of kilowatt-hours of electric
`ity consumed, but also optimizing when it is used. The opti
`mum strategy for energy use over time will vary based upon
`many variables, one of which is the thermal mass of the
`structure being heated or cooled. In a structure with high
`thermal mass, heating and cooling can effectively be shifted
`away from high cost periods to lower cost “shoulder' periods
`with little or no effect on comfort. If, for example, a utility
`charges much higher rates on hot Summer afternoons, it is
`likely that pre-cooling a high-thermal mass structure just
`before the high-cost period and then shutting down the air
`conditioning during the peak will allow the house to remain
`comfortable. But in a house with low thermal mass, the ben
`efits of pre-cooling will quickly dissipate, and the house will
`rapidly become uncomfortable if the air conditioning is shut
`off. Thus it would be advantageous for a temperature control
`system to take thermal mass into account when setting desired
`temperatures.
`Many factors affect the efficiency of HVAC systems. Some
`may be thought of as essentially fixed. Such as the theoretical
`efficiency of a central air conditioner (often expressed as its
`SEER rating), the matching of a given system to the charac
`teristics of a given home, the location and size of forced-air
`ductwork, etc. Other contributors to efficiency are more
`dynamic, such as clogged filters, refrigerant leaks, duct leak
`age and “pop-offs.” and the like.
`Most of these problems are likely to manifest themselves in
`the form of higher energy bills. But the “signature' of each
`different problem can be discerned from the way in which
`each such problem affects the cycle times of a given HVAC
`system over time and relative to weather conditions and the
`performance of other HVAC systems in other houses. If two
`otherwise identical houses are located next door to each other
`and have gas furnaces, but one is rated at 50,000 BTUs and the
`other is rated at 100,000 BTUs, the cycle times for the higher
`capacity furnace should be shorter than for the lower-capacity
`unit. If both of those same houses have identical furnaces, but
`one has a clogged filter, the cycle times should belonger in the
`house with the clogged filter. Because cycling of the HVAC
`system is controlled by the thermostat, those differences in
`cycle time would be reflected in the data sensed by and
`control signals generated by the thermostat. It would be
`advantageous for a thermostat system to be able to use that
`information to diagnose problems and make recommenda
`tions based upon that data.
`These needs are satisfied by at least one embodiment of the
`invention that includes a system for calculating a value for the
`effective thermal mass of a building comprising: at least one
`HVAC control system that measures temperature at at least a
`
`25
`
`30
`
`35
`
`40
`
`45
`
`50
`
`55
`
`60
`
`65
`
`US 8,751,186 B2
`
`10
`
`15
`
`4
`first location conditioned by said HVAC system, and report
`ing said temperature measurements as well as the status of
`said HVAC control system; one or more processors that
`receive measurements of outside temperatures from at least
`one source other than said HVAC control systems and com
`pare said temperature measurements from said first location
`with expected temperature measurements wherein the
`expected temperature measurements are based at least in part
`upon past temperature measurements obtained by said HVAC
`control system and said outside temperature measurements;
`and one or more databases that store at least said temperatures
`measured at said first location over time; calculating one or
`more rates of change in temperature at said first location; and
`relating said calculated rates of change to said outside tem
`perature measurements.
`Another embodiment includes a system for calculating a
`value for the operational efficiency of an HVAC system com
`prising at least one HVAC control system that measures tem
`perature at at least a first location conditioned by said HVAC
`system, and reporting said temperature measurements as well
`as the status of said HVAC control system; one or more
`processors that receive measurements of outside tempera
`tures from at least one source other than said HVAC control
`systems and compare said temperature measurements from
`said first location with expected temperature measurements
`wherein the expected temperature measurements are based at
`least in part upon past temperature measurements obtained by
`said HVAC control system and said outside temperature mea
`Surements; and one or more databases that store at least said
`temperatures measured at said first location over time; calcu
`lating one or more rates of change in temperature at said first
`location for periods during which the status of the HVAC
`system is "on': calculating one or more rates of change in
`temperature at said first location for periods during which the
`status of the HVAC system is “off”; and relating said calcu
`lated rates of change to said outside temperature measure
`mentS.
`A further embodiment includes a system for evaluating
`changes in the operational efficiency of an HVAC system over
`time comprising at least one HVAC control system that mea
`Sures temperature at at least a first location conditioned by
`said HVAC system, and reporting said temperature measure
`ments as well as the status of said HVAC control system; one
`or more processors that receive measurements of outside
`temperatures from at least one source other than said HVAC
`control systems and compare said temperature measurements
`from said first location with expected temperature measure
`ments wherein the expected temperature measurements are
`based at least in part upon past temperature measurements
`obtained by said HVAC control system and said outside tem
`perature measurements; and one or more databases that store
`at least said temperatures measured at said first location over
`time.
`A further embodiment includes a system for detecting and
`correcting for anomalous behavior in HVAC control systems
`comprising a first HVAC control system that measures tem
`perature at at least a first location conditioned by said first
`HVAC system, and reporting said temperature measurements
`as well as the status of said first HVAC control system; at least
`a second HVAC control system that measures temperature at
`at least a second location conditioned by said second HVAC
`system, and reporting said temperature measurements as well
`as the status of said second HVAC control system; one or
`more processors that receive measurements of outside tem
`peratures from at least one source other than said first and
`second HVAC control systems and compare said temperature
`measurements from said first HVAC controls system and said
`
`PETITIONER GOOGLE EX. 1017
`
`

`

`5
`second HVAC control system and said outside temperature
`measurements; and one or more databases that store said
`temperatures measurements.
`In at least one embodiment, the invention comprises a
`thermostat attached to an HVAC system, a local network
`connecting the thermostat to a larger network Such as the
`Internet, and one or more additional thermostats attached to
`the network, and a server in bi-directional communication
`with a plurality of such thermostats. The server logs the
`ambient temperature sensed by each thermostat vs. time and
`the signals sent by the thermostats to their HVAC systems.
`The server preferably also logs outside temperature and
`humidity data for the geographic locations for the buildings
`served by the connected HVAC systems. Such information is
`widely available from various sources that publish detailed
`weather information based on geographic areas such as by
`ZIP code. The server also stores other data affecting the load
`upon the system, Such as specific model of HVAC system,
`occupancy, building characteristics, etc. Some of this data
`may be supplied by the individual users of the system, while
`other data may come from third-party sources such as the
`electric and other utilities who supply energy to those users.
`Combining these data sources will also allow the server to
`calculate the effective thermal mass of the structures condi
`