Schneider Electric Usa, Inc.

Square D Company

Schneider Automation Gmbh

Turner, Larry A.

Buda, Paul Robert

Verga, Frank J.

Pazis, Jason

Brown, Scott Robert

Glasgow, David R.

Pollard, Gary Brent

Paul Robert Buda

Scott Robert Brown

Larry A Turner

Gary Brent Pollard

David R Glasgow

Jonathan H Bailey

Jason Pazis

Larry A Dew

Kelvin Peele

Frank J Verga

Roy Stephen Colby

Alexander Filippenko

Gary L Dowdy

Mark A Hinton

Colin N Gunn

Alan F Krauss

Robert M Slazinski

Jackie Laverne Winn

Ian J Lyttle

Gene Steifelmeyer

Marc Bruel

Scott Robert Littler

Raymond W Harris

Todd Charles Wheaton

Gary B Pollard

Scott Brown

Gary Pollard

Colin Gunn

Systems and methods for monitoring an HVAC&R system employ a monitoring agent that uses observations of evaporator and condenser intake temperatures, evaporator discharge temperature, and a compressor input power parameter to learn operating characteristics of the HVAC&R system in newly maintained condition. Thereafter, the agent continuously or regularly computes a relative coefficient of performance (COP) for the system under subsequent observed ambient conditions, and relates the present instantaneous efficiency of the HVAC&R system under the observed ambient conditions to the instantaneous efficiency when the system was in newly maintained condition. The relative COP can be used to detect system degradation and quantify the energy usage and cost attributable to the degradation. The agent can take appropriate actions to prevent/minimize damage based on the degree of degradation detected, including shutting off power to the HVAC&R system. The monitoring agent can also be extended to other types of systems besides HVAC&R system.

HVAC and R performance degradation monitor and relation builder

System and method for monitoring and detecting potential problems early in a VCC based HVAC&R system employs a monitoring application or agent that uses continuous machine learning and a temperature map to derive or 'learn' a relation between a measured input power parameter of one or more system compressors, and condenser and evaporator intake fluid temperatures, based on observations of the temperatures and the input power parameter when the HVAC&R system is new or in a “newly maintained” condition. The monitoring agent can then use the learned relation to determine, based on subsequent observations of the condenser and evaporator intake fluid temperatures, the input power parameter values that should be expected if the HVAC&R system were operating in the “newly maintained” condition. The agent can thereafter compare the expected compressor input power parameter values with observed input power parameter values to determine early whether the system is experiencing performance degradation.

Continuous learning compressor input power predictor

System and method for monitoring and detecting potential problems early in a VCC based HVAC&R system employs a monitoring application or agent that uses continuous machine learning and a temperature map to derive or 'learn' a relation between a measured input power parameter of one or more system compressors, and condenser and evaporator intake fluid temperatures, based on observations of the temperatures and the input power parameter when the HVAC&R system is new or in a 'newly maintained' condition. The monitoring agent can then use the learned relation to determine, based on subsequent observations of the condenser and evaporator intake fluid temperatures, the input power parameter values that should be expected if the HVAC&R system were operating in the &#x201c;newly maintained&#x201d; condition. The agent can thereafter compare the expected compressor input power parameter values with observed input power parameter values to determine early whether the system is experiencing performance degradation.

Embodiments of the disclosure provide a thermal model based on an adaptive filter bank for characterizing heat transfer of a volume of a thermal system. In one embodiment, the adaptive filter bank is used for diagnostics that provides information related to the condition of a thermal system. The diagnostics are based on an analysis of heat transfer characteristics of a dynamic representation of the thermal system. In accordance with the embodiments, thermal coefficients are generated based on an adaptive filter bank. One or more filters are applied to the thermal coefficients based on a sampling rate and one or more estimate thermal coefficient thresholds are generated based on the sampling rate. It is determined whether at least one of the thermal coefficients that is filtered satisfies at least one of the estimated thermal coefficient thresholds. Thereupon, alert information indicative of a diagnostic event is provided based on the determination.

Detecting diagnostic events in a thermal system

A processor-implemented method of controlling an HVAC system transforms a comfort map into a plurality of sequential constant-temperature segments that are used in generating a control temperature sequence that preserves occupant comfort while improving energy efficiency. The method balances user comfort, temperature trajectory execution complexity, operational HVAC trajectory realization, and energy efficiency. The system achieves this balance through utilization of comfort map metric data, analysis and control system execution. The system, comfort map metric data processing and analysis facilitates this balance by executing a control temperature sequence/temperature trajectories developed based on direct user comfort feedback data within the context of a comfort map and thermal equilibrium boundaries derived from the comfort map.

Apparatuses, methods and systems for comfort and energy efficiency conformance in an HVAC system

The INTERIOR COMFORT HVAC USER-FEEDBACK CONTROL SYSTEM AND APPARATUS transforms qualitative feedback received from a user/occupant into a 'comfort map,' or modifications thereto, a comfort map being defined at least in part by one or more comfort event windows. The comfort map data is used to determine a temperature setpoint sequence that avoids regions of the map corresponding to known and/or predicted regions of user discomfort.

Interior comfort HVAC user-feedback control system and apparatus

An HVAC&R monitor detects short-term and long-term system efficiency degradations by modeling either compressor input power or current. The model is continuously updated with new or recent temperature and power parameter measurements reflecting the most up-to-date operating condition of the system. Short-term system degradations are detected instantaneously by comparing compressor power or current as predicted by the model against measured power or current usage. Long-term system degradations are detected over time by monitoring the sensitivity of the compressor power or current usage to evaporator and/or condenser fluid temperatures. An appropriate warning and/or signal may be issued if system efficiency degradation is detected.

Detection of efficiency degradation in HVAC and R systems

The INTERIOR USER-COMFORT ENERGY EFFICIENCY MODELING AND CONTROL SYSTEMS AND APPARATUSES ('IUCEEMC') transforms comfort maps and occupant comfort inputs via a profile library manager component, exploration manager component, comfort map manager component, regulation monitor component, control temperature sequence generator component, and comfort map modification component, into comfort map and control temperature sequence outputs. In some implementations, the IUCEEMC can divide a timespace of a temperature model into a plurality of sections, select a section from the plurality of sections, perform a first persistent change of the section from the plurality of sections, and, via a control temperature sequence generator, calculate a control temperature sequence using the temperature model. The IUCEEMC can develop and execute a temperature trajectory on an HVAC system, such as a home or industrial HVAC system.

Interior user-comfort energy efficiency modeling and control systems and apparatuses using comfort maps

A frost monitor for HVAC&R systems detects efficiency degradations indicative of coil icing or frosting conditions by modeling compressor input power. The model uses temperature and compressor input power parameter measurements to predict expected compressor input power parameter values. Efficiency degradations are detected by comparing compressor power or current as predicted by the model against measured power or current. Deviations of the measured power parameter values from the predicted power parameter values by a predefined threshold reflect efficiency degradations that may be due to ice or frost accumulation on system coils. Such efficiency degradations may then be used to initiate a defrost cycle in the system.

Frost detection in HVACandR systems

A system for comfort based management of thermal systems, including residential and commercial buildings with active cooling and/or heating, is described. The system can operate without commissioning information, and with minimal occupant interactions, and can learn heat transfer and thermal comfort characteristics of the thermal systems so as to control the temperature thereof while minimizing energy consumption and maintaining comfort.

Operational constraint optimization apparatuses, methods and systems

According to one aspect, embodiments of the invention provide a power meter comprising a voltage sensor, at least one current and phase sensor circuit, and a central metering unit, wherein the voltage sensor is further configured to measure a voltage on an input line and transmit a signal related to the voltage to the central metering unit, wherein the at least one current and phase sensor circuit is further configured to measure a current and a voltage phase shift of a feeder line, and to transmit a signal related to at least one of the current of the feeder line and the voltage phase shift of the feeder line to the central metering unit, and wherein the central metering unit is configured to calculate power provided to a load via the feeder line based on the signal transmitted from the at least one current and phase sensor circuit.

Power meter with current and phase sensor

Power measurement by tracking of a voltage cycle when voltage and current measurements are taken at different locations on an AC power line, with the devices taking the measurements interconnected by an asynchronous data network. In general, a synchronization/timing message is sent from the voltage sensing side to the current sensing side, with the synchronization/timing message being transmitted at a predetermined point in the periodic voltage cycle. The receipt of the synchronization/timing message by the current sensing side may be used to re-synchronize an internal model of the voltage cycle maintained by the current sensing side to the measured voltage cycle. The predetermined point in the voltage cycle may be the zero-crossing point, or other point, of the voltage cycle.

Power determination from separated voltage and current sensors

A method of automatically detecting an anomalous condition relative to a nominal operating condition in a vapor compression system. An expected input power function in the form of a hyperplane is calculated based on three temperature readings: an intake temperature from an intake area of the condenser unit, a return temperature from an intake area of an evaporator unit, and a supply temperature from a supply output area of the evaporator unit. The function produces an estimate of the expected input power consumed by the compressor unit, and this expected input power is compared with an actual input power measured from the compressor unit. If the expected input power deviates from the measured input power by more than a predetermined tolerance, an indication is stored and communicated that an anomalous condition, such as a refrigerant loss, condenser unit fouling, or a malfunctioning fan, exists in the vapor compression system.

Growing community of inventors

Raleigh, NC, United States of America

Paul Robert Buda