Mitsubishi Electric Research Laboratories, Inc.

Mitsubishi Electric Corporation

Christopher Laughman

Scott Bortoff

Daniel J Burns

Dan J Burns

Hongtao Qiao

Ankush Chakrabarty

Stefano Di Cairano

Daniel Nikolaev Nikovski

Vedang Mohanrao Deshpande

Yuichi Taguchi

Srikumar Ramalingam

Arvind Raghunathan

Claus Danielson

Richard C Waters

Jaishanker K Pillai

Neera Jain

Dan Burns

Raphael Chinchilla

Joel Paulson

Vedang Deshpande

Scott A Bortoff

The present disclosure provides a system and a method for controlling a vapor compression system (VCS). The method comprises collecting data points indicative of control of the operation of the VCS with different combinations of setpoints for different actuators of the VCS and corresponding costs of operation of the VCS for each of the different combinations of setpoints, and computing, using a Local Search Region Bayesian optimization (LSR-BO) of the combinations of setpoints and their corresponding costs of operation, a probabilistic surrogate model. The probabilistic surrogate model defines at least first two order moments of the cost of operation. The method further comprises selecting from the probabilistic surrogate model a current combination of setpoints improving the cost of operation with respect to a previous combination of setpoints, according to an acquisition function of the first two order moments of the cost of operation subject to a LRS constraint.

System and method for controlling a vapor compression system with safe actuator changes

The present disclosure discloses a system and a method for controlling an operation of a vapor compression cycle based on a hybrid model of dynamics of the vapor compression cycle including a physics-based model and a data-driven model. The method comprises executing a constrained Kalman smoother over the observed variables collected over multiple instances of time to jointly estimate the parameters of the physics-based model and states of the vapor compression cycle, and updating the data-driven model to minimize a difference between the states estimated by executing the constrained Kalman smoother and the states predicted by the physics-based model. The method further comprises updating the hybrid model with the estimated parameters of the physics-based model and the updated data-driven model, and controlling the operation of the vapor compression cycle using the updated hybrid model.

System and method for controlling an operation of a vapor compression cycle based on a hybrid model of dynamics of the vapor compression cycle

A method and system that describe collecting digital representation of observed variables of the operation of the vapor compression cycle over multiple instances of time and executing a constrained ensemble Kalman smoother for each instance of time to estimate the state variables of the vapor compression cycle for each instance of time. The constrained ensemble Kalman smoother updates the state variables over a sequence of time instances within a smoothing window by solving a series of constrained optimization problems in a range of a covariance, for which constraints are enforced for every variable in the smoothing window for every instance of the constrained optimization problems. The method and system further involve outputting, based on the estimates of the state variables, estimates of variables of the vapor compression cycle at each instance of time.

System and method for monitoring an operation of a vapor compression cycle

A system for controlling or optimizing the performance of a vapor compression system by modifying the actuator commands via an output interface, that realizes thermofluid property functions and their derivatives as spline functions which are represented in a coordinate system that is aligned with a fluid saturation curve. The system includes an interface configured to receive measurement data from sensors, a memory configured to store thermofluid property data and computer-executable programs including a B-spline method, and a processor for performing the computer-implemented method. The processor is configured to take as input two thermofluid property variables, and compute a coordinate transformation in which one axis of the coordinates is aligned with the liquid and vapor saturation curves. In the saturation-curve aligned coordinates, a spline function represents the thermofluid property function, with coefficients and knots stored in memory. The spline function is constructed in a manner such that derivatives of the thermofluid property function may be discontinuous across the saturation curve.

System and method for calculation of thermofluid properties using saturation curve-aligned coordinates

A system for designing a circuitry configuration of heat-exchanger units includes an interface to acquire design parameters the heat-exchanger units, a memory to store computer-executable programs including a relaxed decision diagram formation module, and a processor, in connection with the memory, configured to perform the computer-executable programs. The computer-executable programs include steps of providing a configuration of the heat-exchanger units, providing the design parameters of the heat-exchanger units acquired via the interface, generating a relaxed decision diagram based on the design parameters, creating constraints with respect to connections of the heat-exchanger units according to the relaxed decision diagram, and generating feasible configurations of the heat-exchanger units by a mixed-integer-programing method using the constraints.

Method and system for circuiting in heat exchangers

A controller for controlling a vapor compression system is provided. The controller is configured to control an operation of the VCS with different combinations of setpoints for different actuators of the VCS to estimate a cost of operation of the VCS for each of the different combinations of setpoints, and compute, using a Bayesian optimization of the combinations of setpoints and their corresponding estimated costs of operation, a probabilistic surrogate model, wherein the probabilistic surrogate model defines at least first two order moments of the cost of operation in the probabilistic mapping. The controller is further configured to select an optimal combination of setpoints having the largest likelihood of being a global minimum at the surrogate model according to an acquisition function of the first two order moments of the cost of operation.

Controlling vapor compression system using probabilistic surrogate model

A control system for controlling a set of actuators of a system. The control system comprising a switcher configured to select a subset of setpoints from a set of setpoints that control the corresponding set of actuators. An extremum-seeking controller (ESC) configured to perturb a subset of setpoints at each iteration based on a probabilistic distribution of partial gradients of a cost function relating values of the subset of setpoints to a cost of operation of the system. A stochastic gradient estimator is configured to estimate a full gradient of the cost function and update the estimation of the full gradient based on the probabilistic distribution of the partial gradients generated at each ESC iteration. A feedback controller is configured to drive a state of the subset of actuators of the system towards the corresponding perturbed subset of setpoints.

Extremum seeking control with stochastic gradient estimation

Systems and methods for a vapor compression system including primary actuators, secondary actuators, primary sensors that provide a primary set of system outputs, and secondary sensors that provide a secondary set of system outputs. A primary controller receives the primary set of system outputs, and produces a primary set of control inputs for the primary actuators, to regulate one or more zone temperatures to set-points and to regulate one or more critical process variables to set-points. A secondary controller receives the secondary set of system outputs, and produces a secondary set of control inputs, to minimize an overall system power consumption. The secondary inputs may include set-points to the primary controller. The primary outputs may include estimates of critical process variables that are used as inputs to the secondary controller.

System and method for power optimizing control of multi-zone heat pumps

A vapor compression system includes a heat transfer system including an arrangement of components moving a refrigerant through a vapor compression cycle to condition a controlled environment and a refrigerant management system including at least one expansion device regulating an amount of the refrigerant in the vapor compression cycle. The vapor compression system also includes a controller including a processor jointly controlling the expansion device and at least one component of the heat transfer system according to a metric of performance of the vapor compression system.

System and method for controlling refrigerant in vapor compression system

A thermal conditioning system for controlling a thermal comfort of an occupant of a building includes a vapor compression system to control an air temperature in the building space and a radiant system to control a radiant temperature in the building space. The system also includes a feedback controller to generate a first control signal for controlling a state of the vapor compression system to reduce an error between a set-point air temperature and a current air temperature in the building space and includes a feedforward controller to generate a second control signal control for controlling a state of the radiant system based on the state of the vapor compression system.

System and method for thermal comfort control

A method controls a vapor compression system including a variable speed compressor. A desired discharge temperature of the compressor is determined using a mapping between values of the discharge temperature of the compressor and values of speed of the compressor and outdoor air temperature. A transition function for transitioning a current discharge temperature to the desired discharge temperature is determined, such that the transition function is continuous and a rate of change of the transition function is limited. Next, a valve of the vapor compression system is controlled such that the discharge temperature is transitioned to the desired discharge temperature based on the transition function.

System and method for controlling vapor compression systems

A controller controls a first air-conditioning system and a second air-conditioning system having separate refrigerant circuits, but arranged for conditioning a common space. The controller includes a multi-variable regulator to determine control signals for controlling operations of first components of the first and the second refrigerant circuits to reduce jointly and concurrently an environmental error between setpoint and measured values of environment in the common space. The controller also includes at least two single-variable regulators to receive operational errors between setpoint and measured values of an operation of a second component of the first and the second refrigerant circuits. The controller separately determines control signals for controlling the operation of different refrigerant circuits that reduce the operational errors. The controller also includes a lookup table that stores values for other inputs of the systems that improve its performance, and which selects specific input values for both systems according to the outputs of the multi-variable and/or single variable regulators. The controller includes an electrical circuit for controlling the first and the second air-conditioning systems according to the determined control signals.

Coordinated operation of multiple space-conditioning systems

A multi-zone vapor compression system (MZ-VCS) includes a compressor connected to a set of heat exchangers controlling environments in a set of zones. A supervisory controller includes a processor configured for optimizing a cost function subject to constraints on an operation of the MZ-VCS to produce a set of values of the thermal capacity requested for the set of heat exchangers to achieve setpoint temperatures in the corresponding zones. The supervisory controller is a model predictive controller for determining the set of control inputs using a model of the MZ-VCS including a linear relationship between the thermal capacity of each heat exchanger and the temperature in a corresponding zone controlled by the heat exchanger. A set of capacity controllers, wherein there is one capacity controller for each heat exchanger, such that each capacity controller is configured for controlling the corresponding heat exchanger to achieve the requested thermal capacity.

System and method for controlling multi-zone vapor compression systems

A method for controlling an operation of a vapor compression system (VCS) determines values of measured outputs of the operation of the VCS that include performance and constrained outputs. The method determines states of the VCS using an estimator model of the VCS defining a relationship between the states of the VCS, control inputs and controlled outputs, such that a difference between outputs predicted using the estimator model and the measured outputs asymptotically approaches zero. The states of the VCS include a main state representing the operation of the VCS and an auxiliary state representing the effect of unknown disturbances on each measured output of the VCS. The control inputs for controlling the operation of the VCS are determined using a prediction model, such that the constrained output satisfies the constraints, and a difference between the performance output and the value of the setpoint asymptotically approaches zero.

System and method for controlling of vapor compression system

A method reconstructs at three-dimensional (3D) real-world scene from a single two-dimensional (2D) image by identifying junctions satisfying geometric constraint of the scene based on intersecting lines, vanishing points, and vanishing lines that are orthogonal to each other. Possible layouts of the scene are generated by sampling the 2D image according to the junctions. Then, an energy function is maximized to select an optimal layout from the possible layouts. The energy function use's a conditional random field (CRF) model to evaluate the possible layouts.

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Waltham, MA, United States of America

Christopher Laughman