1568 results about "HVAC" patented technology

The invention belongs to the technical field of intelligent control of heating, ventilation and air conditioning systems, and particularly relates to an intelligent optimizing and energy-saving control method for a central air conditioner based on deep learning, which comprises the following steps of: acquiring operation data of a central air conditioning system in real time through an internet of things technology; the operation data comprises operation parameters of cold and heat source equipment, flow and lift parameters of a water pump, fan frequency parameters of a cooling tower, temperature and humidity data of an air conditioner terminal, environment temperature and humidity data, weather forecast data and the like. Through deep integration of Internet of Things perception, deep learning prediction and a multi-objective optimization technology, the limitation of a traditional control framework is broken through, meanwhile, accurate prediction of building cooling and heating loads is realized through construction of a hybrid deep learning model, an optimization objective of a full life cycle perspective is established in combination with an equipment performance degradation model, and the system performance is improved. A federal learning framework is innovatively introduced into region-level energy efficiency management, and the model generalization ability is improved on the premise of ensuring data privacy.

The invention discloses a green building intelligent lighting and energy collaborative optimization system based on multi-source data fusion. According to the system, firstly, multi-source information such as indoor and outdoor illumination, weather, personnel occupation and electricity price is subjected to weighted fusion through dynamic confidence, and an accurate real-time environment state is constructed; then, model predictive control is combined with a multi-objective optimization strategy, and a sunshade device, intelligent lighting and a heating ventilation air conditioner are cooperatively adjusted, so that the comprehensive energy consumption or operation cost is minimized on the premise that the indoor illumination and temperature comfort requirements are met; besides, the self-adaptive module continuously learns and adjusts the thermal characteristics and the use mode of the building through online model parameter correction and occupancy probability prediction, and it is ensured that the energy-saving effect is stable for a long time; the system drives each execution device through a standard building self-control interface, is easy to integrate in a newly built or reformed project, and can significantly improve the energy utilization efficiency and the indoor environment quality.

A heat pump system for a vehicle may efficiently adjust the temperature of heating elements by using a chiller where a refrigerant and a coolant exchange heat. At the same time, the heat pump system may efficiently perform cooling and heating of a rear seat by using a rear heating, ventilation, and air conditioning (HVAC) module provided with a heat-exchanger.

A method for automatic directional control of an air conditioning vent including detecting a vehicle location and a vehicle orientation, determining a sun position with respect to the vehicle location and the vehicle orientation, determining a solar heat gain location within a vehicle cabin in response to the sun position, generating a control signal indicative of the solar heat gain location, and positioning the air condition vent to direct an airflow towards the solar heat gain location and to adjust the flow rate of the airflow in response to the control signal.

A method and system for controlling a heating, ventilation, and air conditioning system (HVAC) in a building based on adaptive model predictive control (MPC) is disclosed, and belongs to the technical field of intelligent building adaptive control. The method may include: acquiring operation data of the HVAC under different working conditions, and performing preprocessing on the acquired data; calculating a marginal fitness measure (MAD) of each data point for each class based on the preprocessed data, and calculating a fitness measure of each data point for each class by combining MADs of all descriptors to obtain a global fitness measure (GAD); setting a GAD threshold, and classifying current operation states of the system according to classification rules; and adopting adaptive control strategies for different operation states since model parameters of each class are fixed after classification.

The invention relates to the field of heating ventilation air conditioner automatic control, and discloses an efficient central air conditioner cold station optimization control system and method based on physical AI. The system comprises a data acquisition module, an energy efficiency modeling module, a load prediction module, a rolling optimization module, an execution control module and a feedback correction module. The data acquisition module forms a time sequence data set; the energy efficiency modeling module adopts transfer learning to obtain a system energy efficiency model of a target domain cold station; the load prediction module outputs a predicted cold load sequence; the rolling optimization module is used for solving an optimal control sequence under the constraints of cooling capacity balance, an equipment operation boundary and a temperature difference threshold by taking a predicted cooling load sequence, a system energy efficiency model and a current equipment operation state as input under a model prediction control framework; the execution control module issues a first control action to control the water supply temperature, the water pump and fan frequency and unit start and stop; and the feedback correction module calculates a residual error and is used for closed-loop correction of the next period.

The invention provides a multifunctional heating ventilation air conditioner waste heat utilization method and system, and the method comprises the following steps: 1, obtaining multi-source data of an air conditioner system and an external heat source, carrying out the preprocessing, carrying out the grading collection and preliminary integration of the multi-source waste heat, and dividing the multi-source waste heat into high-temperature waste heat, medium-temperature waste heat and low-temperature waste heat; multi-source data of an air conditioning system and an external heat source are collected, condensation heat of a compressor, industrial waste heat and other multiple types of waste heat are integrated and subjected to staged treatment, and a high-temperature power generation-medium-temperature heat supply-low-temperature heat storage gradient utilization system is constructed; an LSTM neural network thermal load prediction model and an intelligent algorithm are combined to dynamically adjust a waste heat distribution path so as to realize self-adaptive switching of a refrigeration mode, a heating mode and a hot water mode, and meanwhile, a cascade system, photovoltaic energy, geothermal energy and the like are coupled through a direct-current micro-grid to construct a hybrid energy supply system. The problems that in the prior art, waste heat sources are single, energy efficiency is low due to the fact that gradient utilization is lacked, dynamic regulation and control are insufficient, and cooperation with renewable energy sources is not achieved are sequentially solved.

The invention relates to the technical field of building intelligent control and energy saving, and discloses a building equipment intelligent control optimization management system based on a green low-carbon building. The system comprises five subsystems, wherein an environmental parameter sensing subsystem is used for acquiring temperature and humidity gradients, illumination intensity distribution and personnel activity thermodynamic diagram data inside and outside a building through a distributed sensing network to form a multi-dimensional environmental state vector; the equipment operation state acquisition subsystem acquires an operation power curve, an energy efficiency conversion rate curve and an equipment health degree index of heating ventilation air conditioning, illumination and renewable energy equipment in real time; the dynamic load prediction subsystem establishes an energy consumption load space-time distribution prediction model according to historical data time sequence relevance; the control strategy generation subsystem is used for generating an optimized instruction set containing an equipment start-stop time sequence, a power regulation gradient and an energy distribution weight in combination with the current environment vector and a predicted load; the execution terminal adapts the subsystem to convert the instruction into a device compatible signal and calibrate a response delay.

The invention discloses a control method and device of an HVAC system, a clean room HVAC system, a medium and equipment. The method comprises the steps that indoor and outdoor environment parameter values of a clean room and HVAC equipment operation state data are collected in real time; inputting the collected environmental parameter values into an operation parameter prediction model to obtain control information of the HVAC system; and adjusting operation parameters of the HVAC system based on the control information of the HVAC system and the operation state data of the HVAC equipment. By adopting the scheme, the response speed of the HVAC system can be improved, and the energy consumption of the HVAC system can be reduced.

An infection control tool for a building HVAC system includes processing circuitry configured to receive one or more inputs defining a HVAC system configuration for each of a baseline scenario and one or more other scenarios. The processing circuitry is also configured to estimate infection risk and at least one of energy consumption or operating cost for each of the one or more other scenarios relative to the baseline scenario. The processing circuitry is also configured to operate a display to provide the infection risk and at least one of the energy consumption or operating cost to a user.

The invention discloses an intelligent heating ventilation air conditioner optimization control system and method, and relates to the technical field of intelligent control, and the method comprises the following steps: first analysis obtains a first corresponding relation, sends a first regulation and control signal, completes the regulation and control of equipment parameters in different time durations, second analysis obtains an optimal regulation and control time duration, and sends a second regulation and control signal; and sending the second regulation and control signal, and performing first compensation. Through historical data analysis and dynamic regulation and control, excessive operation or low-efficiency operation of equipment is avoided, the equipment operation strategy can be adjusted according to the optimal regulation and control time duration, energy consumption is further reduced, PID control is adopted for temperature compensation, indoor temperature changes can be quickly responded, the equipment operation strategy is adjusted according to the optimal regulation and control time duration, and the energy consumption is further reduced. The service life of equipment is prolonged, different environments and operation conditions are adapted through historical data analysis and dynamic regulation and control, and energy consumption and operation cost of the system can be remarkably reduced by optimizing operation parameters and operation time of the equipment.

A building-integrated artificial intelligence system forming a continuous ambient neural field is disclosed. The system includes a distributed multimodal sensor lattice, an on-premise symbolic cognition engine, and an adaptive environmental control kernel operating entirely at the building edge without reliance on external cloud services. Sensor data from optical, thermal, acoustic, airflow, pressure, structural, electrical, and chemical modalities are transformed into non-identifying occupancy vectors, behavioral glyphs, risk indicators, and environmental state descriptors. A privacy-governed policy graph determines sensor permissions, redaction thresholds, consent conditions, emergency overrides, and jurisdiction-specific compliance parameters. The neural field predicts occupancy loads, optimizes HVAC, ventilation, and lighting, detects accidents and structural anomalies, classifies emergent risks, and generates redacted event capsules for audit and emergency dispatch. A federated topology enables multiple buildings to exchange compressed symbolic templates to improve predictive accuracy without transmitting raw data. The system provides a universal, regulation-aligned AI nervous system for autonomous building operations.

The invention provides a transformer substation civil engineering digital design system based on a domestic BIM platform, and the system comprises a building design module which is used for constructing a building professional model through employing a building component library; the general drawing design module is used for generating a general drawing professional model based on a parametric modeling technology; the water supply and drainage system digital design module is used for generating a water supply and drainage pipeline design scheme according to the water supply and drainage professional component library and determining a water supply and drainage professional model; the heating and ventilation system digital design module is used for determining the fan equipment model and the air pipe diameter according to the professional building model and determining a professional heating and ventilation model; and the multi-specialty cooperation module is used for carrying out online synchronous modification and real-time updating processing on the building specialty model, the general drawing specialty model, the water supply and drainage specialty model and the heating and ventilation specialty model. According to the method, building, general drawing, water supply and drainage and heating and ventilation multi-specialty collaborative design is achieved based on domestic BIM platform construction and through the parameterized modeling technology, and the design efficiency and the achievement standardization are improved.

Mobile, expandable cleanroom systems, methods, and devices are provided in accordance with various embodiments. Various embodiments include an expandable cleanroom that may include one or more tent enclosures and one or more door assemblies. Some embodiments include one or more HVAC systems. Some embodiments include a raisable truss structure that may lift and support the one or more tent enclosures. The expandable cleanroom may be coupled with an antechamber and / or a mechanical room. The combination of expandable cleanroom, antechamber, and / or mechanical room may be based on the form of a shipping container that may be transported by flatbed truck, railcar, boat, or other vehicles. This May allow for rapid deployment along with avoiding the need for wide-load permits; the various embodiments may also provide for inconspicuous deployment.

A heating, ventilation, and air condition (HVAC) unit includes a casing, a mount, and one or more flexible fingers. The casing is configured to condition air and direct the conditioned air to a vehicle occupant cabin. The mount extends from the casing and is configured to be mounted to an attachment surface. The mount includes an opening that has an inner surface. The flexible fingers each have a proximal end that extends from the inner surface and a distal end. One or more of the distal ends of the flexible fingers are configured to engage an attachment feature extending from the attachment surface and through the opening in the mount to secure the mount to the attachment feature.

The present invention belongs to the technical field of intelligent building energy management and control, and discloses a model-data dual-driven building energy management and control intelligent agent training environment creation method. The method is implemented by the following steps: First, a thermodynamic mechanism model of the building envelope structure and a simulation model of the HVAC system are constructed, and the two types of models are coupled through a joint simulation interface. Then, the existing building operation data is cleaned and repaired by time series alignment, missing value filling, outlier filtering, etc. to ensure data quality. Subsequently, the joint simulation model is run to generate output data such as hourly load and equipment status. Finally, through spatiotemporal label association and feature extraction, the cleaned and repaired measured data and the model output data are multi-source fused to construct a training database containing multi-dimensional features such as building thermal dynamic response and equipment operation characteristics, providing high-precision, full-scene training data support for the building environmental control intelligent agent.

The invention discloses a building energy consumption management and control method, belongs to the technical field of building energy-saving control, and solves the problems of response lag and energy waste caused by independent operation of a lighting system and an HVAC system. According to the technical scheme, a building parameter database is pre-stored; environment data and equipment power consumption are collected in real time; calculating a solar radiation thermal gain coefficient and a thermal load influence quantity of illumination on the HVAC; when the dynamic coupling factor exceeds a first threshold value or the variation of the illumination intensity exceeds a second threshold value within a preset time, triggering collaborative optimization; a lighting target power consumption value (the compensated lighting power consumption is not lower than a preset proportion of the basic lighting demand value) is synchronously generated after response, and the HVAC set temperature is corrected based on the thermal gain coefficient; and finally a control instruction is issued. The method is mainly used for real-time energy consumption collaborative optimization of large-scale public buildings.

The invention relates to a variable dew point control method of an all-air air conditioning system, belongs to the technical field of heating ventilation air conditioners, and solves the technical problems of temperature and humidity coupling in the prior art and difficulty in landing of a chilled water temperature resetting technology. The control method comprises the steps of S1, parameter initialization, S2, system starting and stabilizing, S3, air supply dew point dynamic adjustment and cold water valve control, S4, temperature and air supply amount control and S5, fresh air optimization and air valve control. The water supply temperature is adjusted by dynamically adjusting the air supply dew point and dynamically increasing the temperature of the outlet of the surface air cooler, the energy efficiency of the unit is remarkably improved, and the system is suitable for the chilled water temperature resetting technology and compatible with the application of the medium-temperature water supply technology.

A control system of a heating, ventilation, and / or air conditioning (HVAC) system includes a data communication controller configured to receive, via a first wireless communication protocol, data from a sensor indicative of an operational parameter of the HVAC system. The data communication controller is also configured to receive, via an electronic device communicatively coupled to the data communication controller, a control instruction, and to transmit, via a second wireless communication protocol different from the first wireless communication protocol, a control signal to adjust operation of an HVAC component configured to enable supply of conditioned air to a structure serviced by the HVAC system based on the data and the control instruction.

A system and method for controlling motorized vents of an HVAC system of a vehicle including at least one motor to move air louvers of an HVAC vent of the HVAC system, at least one thermal sensor to sense hot / cold areas inside the vehicle, and a position and motion control to control movement of the at least one motor, wherein position and motion control determines a targeted positioning of airflow based on hot / cold areas sensed by the thermal sensor.

A heating, ventilation, air conditioning, and refrigeration (HVAC&R) system configured to operate in a plurality of cooling modes includes a mechanical cooling system configured to place a working fluid in a heat exchange relationship with a cooling fluid, a free cooling system configured to place the cooling fluid in a second heat exchange relationship with an ambient air flow, and a controller comprising processing circuitry and a memory, wherein the memory comprises instructions that, when executed by the processing circuitry, are configured to cause the processing circuitry to transition operation of the HVAC&R system between the plurality of cooling modes based on a cooling demand of the HVAC&R system and based on an estimated power consumption of the HVAC&R system.

A controller is configured to operate a heating, ventilation, and air conditioning (HVAC) system based on a plurality of concentration measurements received from a refrigerant detection sensor. The controller is configured to receive the plurality of concentration measurements from the refrigerant detection sensor disposed upstream of an evaporator coil. The controller is further configured to determine if a concentration of a refrigerant in a volume exceeds a stored threshold value based at least in part on the received plurality of concentration measurements. In response to determining that the concentration of refrigerant in the volume does exceed the stored threshold value, the controller is configured to operate the HVAC system in a second mode of operation, wherein the second mode of operation includes turning off a compressor and actuating a blower disposed downstream of the evaporator coil to discharge an airflow.

The invention discloses a heating, ventilation and chilled water cooperative control method and system based on a double-branch deep and shallow feature fusion neural network, and the method comprises the steps: obtaining and preprocessing the historical operation data of a heating, ventilation and chilled water system, and forming standardized training data; a double-branch deep and shallow feature fusion neural network model is trained based on the standardized training data, and the model realizes equipment collaborative prediction through a cold water host load prediction branch and a freezing pump frequency prediction branch in combination with a deep and shallow feature fusion mechanism; acquiring environmental parameters in real time, inputting the environmental parameters into the trained model, and outputting a cold water host load predicted value and a freezing pump frequency predicted value; and correcting the predicted value based on a physical constraint correction algorithm, and outputting an optimization control instruction. The technical problem of poor control reliability caused by insufficient equipment collaboration, insufficient feature extraction and lack of physical constraints in the prior art is solved.

The invention relates to the technical field of energy-saving control, and discloses a self-adaptive energy-saving control method and system for building heating and ventilation equipment based on digital twinning. The method comprises the steps of collecting temperature and humidity in a building, heating and ventilation equipment operation, external environment and personnel flow data, extracting energy consumption fluctuation characteristics and performing coupling analysis on the energy consumption fluctuation characteristics and equipment operation data. A distributed lag regression model is constructed in combination with external environment data, the environment influence weight and trend are calculated, and a high-dynamic region is identified through fuzzy reasoning. Energy consumption is predicted based on high-dynamic area data, a waste value is calculated, equipment operation parameters are optimized, and a target power sequence is generated through population iteration. An adjusting instruction is generated through analysis and deployed to a control system, thermal sensation feedback and instantaneous power data are collected, comfort evaluation is conducted, and the adjusting instruction is updated for optimization control. According to the method, dynamic balance of energy conservation and comfort can be realized.

A wall building system includes panels for walls, floors, ceilings, roofs, eaves, and lofts that positively couple together via one or more couplers. The panels may include an insulating core. The one or more couplers incorporate features for receiving plumbing, vents, drains, electrical, coax, CAT5, HVAC, and any other utilities or technology. The panels are designed such that the utilities are concealed until an electrical outlet, drain or water is required, at which time the panel is cut to expose the one or more couplers, which are subsequently cut to reveal a hollow cavity within. The system is aesthetically pleasing and reduces construction time considerably. The system is also extremely energy efficient, fireproof, soundproof, insect proof, virus proof, resists hurricane force winds, is EMP proof, fallout proof, can support a heavy snow load, and is faster to build with and structurally stronger than other construction methods.

The utility model provides a shunting assembly and heating and ventilation equipment, the shunting assembly comprises a shell, a plate body and an inlet pipe, an expansion cavity is defined in the shell, the expansion cavity is provided with an opening, the shell is further provided with an inflow hole communicated with the expansion cavity, and the inflow hole is located at one end, deviating from the opening, of the expansion cavity; the plate body is installed on the shell and seals the opening, the plate body is provided with a plurality of flow dividing holes, and the flow dividing holes are communicated with the expansion cavity; one end of the inlet pipe is connected with the shell and communicated with the inflow hole, and the other end of the inlet pipe is used for introducing fluid; the shell and the inlet pipe are of an integrated metal plate structure. The shell and the inlet pipe are integrally formed by a sheet metal part through a sheet metal machining process, and particularly, the shell and the inlet pipe can be manufactured in a mode of extrusion forming of a cylindrical sheet metal part or coiling forming of a sheet metal part in a prefabricated shape, so that the whole structure is few in connecting points, higher in structural strength, higher in production efficiency and free of leakage points, and parts are reduced. And the hidden danger of liquid leakage during use is reduced.

A HVAC&R system includes a heat pump configured to selectively circulate a working fluid. The heat pump includes an outdoor heat exchanger, an indoor heat exchanger, a compressor, a reversing valve configured to direct the working fluid from the compressor to the outdoor heat exchanger or to the indoor heat exchanger, and a controller. The controller is configured to determine whether a pressure of the working fluid exiting the compressor exceeds a pressure threshold, and, in response to determining that the pressure of the working fluid exiting the compressor exceeds the pressure threshold, control the reversing valve to block the working fluid from flowing from the compressor through the reversing valve to the outdoor heat exchanger.

A central HVAC thermostat controls a central HVAC system of a home. The thermostat further includes a control unit and remote-control device for controlling at least one room HVAC system in a room of the home. The control unit generates control data for the at least one room HVAC system. The remote-control device receives the control data from the control unit. The remote-control device converts the control data to wireless control signals. Finally, the remote-control device sends the wireless control signals to the at least one room HVAC system using a first wireless communication technology. The at least one room HVAC system can include at least one air conditioner or at least one heat pump. The first wireless communication technology can be infrared technology. The control unit further transmits the control data to the remote-control device using a second wireless communication technology.

A computer-implemented method of determining a configuration for an energy installation for use in a property connected to an electricity distribution grid. The energy installation comprises a plurali

A vehicle thermal management system includes a heat pump system, a coolant loop that transfers heat energy between a battery and a cabin heating, ventilation, and air-conditioning (HVAC) module. The heat pump system can be an air-source heat pump or coolant-based heat pump with a water condenser. The coolant loop includes a low-temperature cooling system that rejects coolant heat to the ambient environment through a radiator. The cabin HVAC module includes a blower, a vent door, a cabin heater, and an evaporator. The coolant loop of the thermal management system includes an electric water pump, a chiller, a cabin heat exchanger, a three-way valve, and a one-way valve. The vehicle thermal management system can take advantage of a temperature difference between cabin exhaust air and battery coolant for heating and cooling, which reduces system power consumption.