Schneider Electric Usa, Inc.

Other

Square D Company

Turner, Larry A.

Buda, Paul Robert

Verga, Frank J.

Pazis, Jason

Brown, Scott Robert

Glasgow, David R.

Pollard, Gary Brent

Larry A Turner

Zhi Gao

Paul Robert Buda

Roy Stephen Colby

Scott Robert Brown

Gary Brent Pollard

David R Glasgow

Jason Pazis

Frank J Verga

Benoit Leprettre

Gary B Pollard

Scott Brown

Gary Pollard

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

Embodiments of the disclosure implement an application of an adaptive filter bank that is used to characterize the heat transfer of a volume in a thermal system, to estimate temperature and power consumption, and to improve performance characteristics in applications including optimal temperature control and diagnostics. In some embodiments, the adaptive filter bank is an iterative solution, comprised of a collection of adaptive filters defined to consume incident signals, produce an aggregate reference signal, estimate an error relative to an observed primary signal, and modify thermal coefficients to converge on a solution. For example, the incident signals are comprised of properties related to active, passive, solar irradiance, and unobserved heat transfer. A reference signal is an estimate of a primary signal, related to the rate of heat transfer or temperature change. Thereupon, the thermal coefficients are modified in an adaptive process to include gradient descent, which minimizes estimation error.

Adaptive filter bank for modeling 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

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 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. A thermal model represents thermal behavior of a volume in a thermal system, characterizing heat transfer and estimating energy consumption and temperature. A comfort model represents thermal comfort in a volume of a thermal system, estimating an effective temperature at which an occupant is unlikely to object. A comfort agent interacts with thermal models to estimate physically-realizable discrete temperature states with associated transition values, constrained by comfort model estimates, to identify an optimal path and define control temperatures for volumes in a thermal system, facilitating optimal start and temperature control.

Interior volume thermal modeling and control apparatuses, methods and 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

A method and apparatus to dynamically and adaptively demodulate induction motor instantaneous rotor slot harmonic frequency for line-connected squirrel-cage polyphase induction motors. The instantaneous rotor slot harmonic frequency carries essential information on the instantaneous rotor speed. Based on a correlation between the motor's input power and its rotor slot harmonic frequency, a dynamically varying carrier frequency is computed and used in a rotor slot harmonic frequency detector. The rotor slot harmonic frequency detector is based on a superheterodyne principle. It contains a generalized linear-phase low-pass filter, whose bandwidth is estimated dynamically by a filter bandwidth estimator. The rotor slot harmonic frequency detector also includes a latency compensator, which receives the dynamically varying carrier frequency signal and synchronizes it with the output of a frequency demodulator.

Systems, methods, and devices for demodulating induction motor instantaneous rotor slot harmonic frequency

A Complex Adaptive Phase Discriminator (PD), as presented in some concepts of the present disclosure, is an adaptive filter that accurately estimates the instantaneous frequency of a dynamic complex signal. The PD can demonstrate accurate instantaneous frequency estimation and rapid convergence in dynamic complex signal environments, even when the frequency of its input may change rapidly. A direct PD architecture can estimate the instantaneous frequency of a complex primary signal, iteratively adapting a phase of a complex exponential by minimizing the mean squared error of a complex error signal. Instantaneous frequency can be directly estimated from the phase of the complex exponential. In contrast, an indirect PD architecture can estimate the instantaneous frequency of a complex primary signal, iteratively adapting a complex coefficient by minimizing the mean squared error of a complex error signal. Instantaneous frequency can be indirectly estimated by extracting the phase of the complex coefficient.

Complex adaptive phase discriminator

Methods and devices are presented herein for estimating induction motor inductance parameters based on instantaneous reactive power. The induction motor inductance parameters, e.g., the stator inductance and the total leakage factor, can be estimated from motor nameplate data and instantaneous reactive power without involving speed sensors or electronic injection circuits. In one embodiment, the method includes: measuring voltages and currents; converting the measured voltages and currents into discrete-time voltage and current samples by analog-to-digital converters; synthesizing a complex voltage from the discrete-time voltage samples; synthesizing a complex current from the discrete-time current samples; acquiring and storing motor nameplate data; detecting instantaneous rotor speed by calculating an instantaneous rotor slot harmonic frequency with respect to an instantaneous fundamental frequency; calculating, via an induction motor inductance estimator, the motor's instantaneous reactive power and other intermediate quantities; and outputting the stator inductance and the total leakage factor.

Methods and devices for estimation of induction motor inductance parameters

Methods of determining a quantity of rotor slots in an induction motor are disclosed. An approximate slip is calculated according to an approximate slip function. A fundamental frequency is calculated from a representation of the voltage signal. A saliency frequency is calculated from a representation of the current signal. For each rotor slots index in a set of rotor slots indices, a slip estimate is calculated according to a slip estimation function. A slip estimation error signal is calculated. A rotor slots performance surface representative of an aggregate of the slip estimation error signals is calculated. A rotor slots quantity equal to the rotor slots index corresponding to a minimum of the rotor slots performance surface over at least a portion of the set of the rotor slots indices is defined.

Methods and apparatus for estimating rotor slots

A method of determining a quantity of rotor slots in an induction motor through analysis of voltage and current signals. An approximate slip is calculated according to an approximate slip function that is independent of a rotor slots quantity. A fundamental frequency is calculated from a representation of the voltage signal. A saliency frequency is calculated from a representation of the current signal. For each rotor slots index in a set of rotor slots indices, a slip estimate is calculated according to a slip estimation function that includes the saliency frequency, a saliency order, the fundamental frequency, a rotor slots index in the set of rotor slots indices, and a quantity of poles of the motor, such that the slip estimate is evaluated at respective ones of the set rotor slots indices. A slip estimation error signal is calculated according to a slip estimation error function that includes a difference between the approximate slip and respective ones of the slip estimates. A rotor slots performance surface representative of an aggregate of the slip estimation error signals evaluated over the set of the rotor slots indices is calculated. A rotor slots quantity equal to the rotor slots index corresponding to a minimum of the rotor slots performance surface over at least a portion of the set of the rotor slots indices is defined.

A method and apparatus to provide estimates of electrical parameters for line-connected induction motors during either steady-state or dynamic motor operations. The electrical parameters are calculated from the motor nameplate data and voltage and current measurements. No speed sensors or electronic injection circuits are needed. The method can be divided into 4 major steps. First, complex space vectors are synthesized from voltage and current measurements. Second, the instantaneous rotor speed is detected by calculating the rotational speed of a single rotor slot harmonic component with respect to the rotational speed of the fundamental frequency component. Third, the positive sequence fundamental frequency components are extracted from complex space vectors. Finally, least-squares estimates of the electrical parameters are determined from a dynamic induction motor equivalent circuit model.

Growing community of inventors

Chapel Hill, NC, United States of America

Larry A Turner