10707 results about "Air conditioning" patented technology

Air conditioning device (1) for motorhomes, comprising: - at least one first heat exchanger for exchanging heat with the air circulating through it; - a cooling circuit (8) for a cooling fluid, with a path passing through the first heat exchanger; - a compressor (7) which includes an electric motor, for circulating the cooling fluid in the cooling circuit (8); - a power supply unit that can be connected to an external power supply to receive an electrical input current or electrical input power and to generate a variable supply voltage to drive the electric motor with an electrical supply current, - a controller (11) connected to the power supply unit that is suitable for receiving input data representative of a reference value of the electrical input current or electrical input power and that is programmed to adjust the power supply unit to generate the supply voltage with a reference amplitude and / or frequency such that the electrical input current or electrical input power is below the reference value; - a positioning device designed to determine the position of the air conditioning device (1); and - a memory containing a plurality of reference values ​​corresponding to a plurality of locations, wherein the controller (11) is capable of receiving a location signal from the positioning device and of setting as input data one of the reference values ​​present in the memory depending on the location signal.

The shutdown of a compressor (10) installed in a refrigerant circuit (2) in air conditioning or refrigeration system is controlled so as to prevent unpowered reverse rotation of the compressor. Prior to terminating electric power to the compressor drive motor (24), the pressure within the system is relieved and substantially equalized across the compressor, thereby eliminating the possibility of unpowered reverse rotation of the compressor at shutdown. Pressure relief and equalization may be achieved by reducing the operating speed of the compressor to a low forward speed for a period of time prior to deenergizing the compressor drive motor. Pressure equalization may also be achieved by driving the compressor in reverse rotation prior to deenergizing the drive motor.

The invention discloses an air conditioning system and a control method thereof. The air conditioning system comprises an air conditioning outdoor unit; the air conditioning outdoor unit comprises a compressor, an outdoor heat exchanger and an outdoor fan; the outdoor fan is at least provided with a first working mode and a second working mode; and when the outdoor fan runs in the first working mode, a wind gear is higher than that when the outdoor fan runs in the second working mode. The control method comprises the following steps that S1, the air conditioning system is controlled to enter arefrigeration mode; S2, according to the outdoor environment temperature and / or preset hours, the outdoor fan is controlled to enter the first working mode or the second working mode. According to the control method of the air conditioning system, the air conditioning system can control the outdoor fan to enter the first working mode or the second working mode according to the outdoor environmenttemperature and / or the preset hours, and when the outdoor fan runs in the second working mode, the wind gear of the outdoor fan is lowered, so that the use reliability the air conditioning system cannot be affected, and the requirement of a user on comfortableness can be met.

The invention relates to the technical field of air conditioning, in particular to a laboratory heating and ventilation load prediction and self-adaptive regulation and control method. According to the method, the infrared frame and the power sampling time mark are synchronized, the sensing flow is aligned and packaged, and the thermal diffusion evolution rate is generated. Lagging characteristics are determined in combination with power jump and temperature rise moments, and a heterogeneous dynamic coupling model is established. Extracting a physical evolution parameter as a mechanism operator, injecting the mechanism operator into a hidden layer of the prediction model, reconstructing a phase space, and calculating an air load increment in a lag window. And reverse mapping is executed based on the heat exchange characteristics to generate a feedforward instruction, and when the rate exceeds a threshold value, the weight is issued and dynamically corrected, so that closed-loop correction is completed. According to the method, deep coupling of feedforward prediction compensation and feedback residual adjustment is executed, and accurate regulation and control of the air volume and cooling and heating loads of the laboratory are achieved.

The invention discloses a multi-modal data fusion air conditioner optimization control method and system, and belongs to the technical field of intelligent building equipment control. According to the method, temperature, humidity, energy consumption, user behaviors and meteorological data are collected through a multi-source sensor, the data are subjected to dynamic window standardization processing and then input into a gated convolution LSTM network to predict the system state, an optimization strategy is generated in combination with an online reinforcement learning algorithm, multi-modal instructions are dynamically weighted and fused, and execution parameters are adjusted in real time through a feedback correction mechanism. The system comprises a multi-source sensing array, an edge computing unit, a strategy optimization engine and an intelligent execution controller. According to the method, through collaborative optimization of multi-modal spatial-temporal feature fusion and deep reinforcement learning, the problem of unbalance of energy efficiency and comfort is solved, the energy efficiency level and the user comfort of the air conditioning system are remarkably improved, and the method has the characteristics of real-time response and high stability, is suitable for intelligent air conditioning control of modern buildings and has wide application prospects.

The invention provides a water flow dynamic distribution control method driven by air conditioner terminal load prediction, and relates to the technical field of air conditioner engineering.The method comprises the steps that 1, the people flow density, the environment temperature and humidity and the equipment running state of each air conditioner terminal service area are collected in real time, and a load prediction mechanism is constructed based on a spatial-temporal feature fusion algorithm; the minimum cooling capacity demand of each tail end in the future time period is predicted; 2, based on the minimum cooling capacity requirement, areas with similar load characteristics are classified into the same cluster through hot area clustering, and building scale dynamic cooling load distribution is generated with cluster mass center data as the benchmark; and step 3, calculating an energy flexibility penalty coefficient based on the dynamic cooling load distribution in combination with the real-time deviation between the indoor temperature and the comfortable temperature difference, and generating a regional water flow regulation weight. According to the method, dynamic distribution of the water flow is driven through load prediction, the water pump frequency and the refrigerating unit strategy are dynamically adjusted in combination with real-time energy consumption feedback, and self-adaptive adjustment of the branch water flow is achieved.

The invention relates to the technical field of lime kiln control, and discloses a lime kiln partition intelligent temperature control system and a storage medium, and the system comprises a data collection unit which is used for collecting state data of each region of a lime kiln; the working condition recognition unit recognizes working conditions based on the state data; the temperature control unit is provided with a PID (Proportion Integration Differentiation) control strategy and a prediction control strategy, and the opening degrees of the fuel regulating valves and the air regulating valves in different areas in the lime kiln are calculated according to the corresponding control strategies selected on the basis of working conditions; the discharging control unit is provided with a balance control strategy, the balance control strategy obtains the current discharging speed through the current productivity of the lime kiln and the material level height in the lime kiln, and the execution unit correspondingly controls the lime kiln according to the control quantity. The method effectively solves the problems of difficulty in multi-area coordination, poor working condition adaptability, high energy consumption and the like in a traditional control mode, and has the remarkable advantages of improving the temperature control precision, ensuring the production stability and reducing the energy consumption.

The invention relates to the technical field of green building energy consumption, and discloses a green building energy consumption real-time monitoring and intelligent adjusting system based on the Internet of Things, and the system comprises an Internet of Things multi-source sensing module which integrates a building internal and external environment sensing unit and an equipment operation state collection unit, and generates a comprehensive energy consumption characteristic signal through a heterogeneous data fusion gateway; the dual-channel decision module receives the signal, the load prediction unit outputs a building cooling and heating load prediction signal and a regional energy efficiency imbalance risk signal, the energy efficiency optimization unit generates an optimal equipment adjustment strategy signal, and the dynamic adjustment unit outputs a real-time energy consumption safety threshold; the intelligent execution control module and the self-adaptive equipment regulation and control unit adjust heating and ventilation equipment parameters, the multi-equipment collaborative management unit optimizes the running state of the lighting and air conditioning equipment group and collects feedback signals, and the man-machine interaction early warning platform generates a comprehensive energy efficiency risk index. According to the system, real-time monitoring and intelligent adjustment of energy consumption of the green building are realized, and refinement and collaboration of energy consumption management are improved.

The invention discloses a data center machine room energy-saving optimization method and system based on thermal environment prediction. The method comprises two stages of offline modeling and online prediction optimization. In the off-line stage, a CFD simulation model is constructed based on a machine room physical structure, equipment layout and thermal load parameters, and high-precision temperature field data is generated; using the thermal environment prediction model to input equipment parameters and load change to output future space temperature distribution; meanwhile, an XGBoost hybrid energy consumption prediction model is constructed based on the wind speed ratio or the fan frequency, the number of running fans and related characteristics. In the online stage, the lowest energy consumption and the minimum temperature deviation serve as targets, and a Pareto optimal solution set is generated through an MOEA / D algorithm; the optimal wind speed ratio / frequency and equipment number combination is selected as required to control operation of the air conditioner; and dynamically updating model parameters by sliding a time window to realize long-term robust control of the system. According to the method, intelligent energy-saving control of the machine room is realized by fusing CFD simulation, time sequence prediction, energy consumption modeling and a multi-objective optimization algorithm.

The invention discloses a cold storage temperature optimization control system and method for a chilled water storage air conditioning system, and relates to the technical field of chilled water storage air conditioning management.The method comprises the steps that 1, a plurality of operation parameters in the system operation process are collected; performing time synchronization and abnormal value elimination on the operation parameters to form a dynamic operation data set; and 2, judging the current hydraulic circulation state based on the dynamic operation data set, and outputting a circulation deviation signal when any index of the total flow of the system, the flow distribution of each branch or the temperature difference change rate of the supplied water and the returned water exceeds a set corresponding threshold value. By constructing the dynamic operation data set and monitoring key parameters such as the system temperature, the flow and the water pump operation state in real time, a unified multi-dimensional data basis is established, support is provided for follow-up operation state recognition and control strategy execution, and the real-time performance and accuracy of control are remarkably improved.

The invention discloses a low-carbon transformation method, system and device for a building air conditioning system. The objective of the invention is to solve the problems of static model, single target, one-sided evaluation and non-standardized process in the existing reconstruction technology. According to the method, building multi-dimensional data are collected; constructing a building energy consumption prediction physical simulation model coupled with a user behavior prediction model based on machine learning to dynamically reflect a real operation condition; a multi-dimensional objective function is defined, and a Pareto optimal transformation scheme set is generated; constructing an evaluation model based on an analytic hierarchy process and a fuzzy comprehensive evaluation method, and calculating a comprehensive evaluation value of each scheme; and selecting an optimal scheme according to the comprehensive evaluation value, and generating a detailed implementation report. The method can scientifically and efficiently determine the global optimal transformation strategy considering energy conservation, carbon reduction, comfort and economy, and significantly improves the scientificity and comprehensive benefits of building transformation decision.

The embodiment of the invention provides an air conditioner control method and device and a storage medium, the method is used for conducting cooperative control on multiple air conditioner systems deployed in different buildings of a target park, and the method comprises the steps that people flow trend prediction data of the target park in the future time period is obtained, the people flow trend prediction data represents migration and / or distribution conditions of people among different buildings; based on the people flow trend prediction data, target loads of the multiple air conditioning systems are determined; based on the respective target loads of the multiple air conditioning systems, the multiple air conditioning systems serve as a whole, combined planning is conducted on the operation parameters of the multiple air conditioning systems, and a target control strategy used for conducting cooperative control on the multiple air conditioning systems is obtained; and on the basis of the target control strategy, control operation is executed on the multiple air conditioning systems.

The invention discloses an indoor environment automatic adjustment method based on self-supervised learning, and the method comprises the steps: collecting the multi-modal data of an indoor environment and a user behavior, completing the synchronization and standardization processing, and constructing a causal graph model which comprises an environment variable, a user behavior variable and an adjustment response variable; adjusting causal representation vectors are generated through reverse causal modeling, building structure parameters, user preferences and climate regionalization information are fused, and a unified cross-modal embedding space is constructed; and further training an adjustment strategy migration model based on a federal migration learning mechanism, and generating a personalized control instruction in combination with local terminal data. The method has the advantages of being high in causal reasoning ability, accurate in cross-modal fusion expression, high in control strategy adaptability and the like, and is suitable for application scenes such as intelligent buildings, energy-saving air conditioning systems and environment sensing type home furnishing.

The embodiment of the invention discloses an air conditioner maintenance data classification method and system based on machine learning, and the method comprises the steps: integrating multi-source heterogeneous maintenance records generated in the maintenance process of air conditioner equipment, building a correlation index through a common identification field, and fusing dispersed data into a maintenance data set in a uniform format; performing hierarchical semantic analysis on unstructured texts in the set to generate structured semantic features, and performing time sequence feature extraction on structured data; then constructing a hybrid classification model training framework fusing semantic and time sequence features, and generating a maintenance data classification model through feature space alignment, dynamic weight distribution, hyper-parameter optimization and an early stop strategy; and finally, classifying newly-added maintenance records by applying the model, checking by combining an expert knowledge base, manually rechecking conflict results, and returning corrected data as an incremental sample back to the model to realize continuous optimization.

According to the data center evaporation cold total heat recovery double-energy-storage air conditioning system and the control method, the obvious energy efficiency improvement and economic optimization effects are achieved, the future server heat load, environment parameters and electricity price changes are accurately pre-judged through a composite prediction model of the central control module, and the real-time charge state of the double-energy-storage module is combined, so that the energy efficiency is improved. A collaborative operation instruction with the optimal cost is generated; by means of deep coupling of the evaporative cooling module and the total heat recovery module, a natural cold source is utilized to the maximum extent, and the running time of a conventional refrigeration module is shortened; through cooperative scheduling of the cold energy storage unit and the heat storage unit, efficient cold / heat storage is achieved in the electricity price valley value period, stored energy is released preferentially in the peak value period, and frequent starting and stopping of equipment are avoided; and on the basis of the multi-dimensional constraint optimization decision model, the total operation cost is minimized on the premise that the system meets the safety temperature and humidity requirements of the data center.

A housing is provided for an air conditioner circuit, comprising: an access panel configured to partially cover the air conditioner circuit and including a panel surface formed on an outside of the housing, a panel opening in the panel surface passing from the outside of the housing toward an inside of the housing; a refrigerant sensor configured to detect a presence of a refrigerant in air proximate to the refrigerant sensor; and a sensor cover attached to an outside of the housing and configured to cover the panel opening and the refrigerant sensor, wherein the refrigerant sensor is located at least partly inside the panel opening.

The invention relates to a liquid air energy storage and terrestrial heat coordinated underground space air regulation and control system and method. Comprising a first-stage compressor, a second-stage compressor, a third-stage compressor, an expansion refrigerator, a first-stage compression heat exchanger, a second-stage compression heat exchanger, a third-stage compression heat exchanger, a cold box, a separator, a liquid air storage tank, a cryogenic pump, an evaporator, a cold storage circulating pump, a cold storage box, a compression heat exchange circulating pump, a compression heat storage box, a first heater, a second heater and a third heater. The system comprises a first air expander, a second air expander, a third air expander and a generator. The regeneration heater is used for guiding the compression heat generated by the compressor into the regeneration heater for regeneration and / or guiding the geothermal energy output by the geothermal energy output end into the regeneration heater for regeneration; the rotary wheel dehumidification device is used for performing cryogenic drying on the wet air; the fresh air processing unit is composed of a fresh air filter, a regeneration fan, a regeneration filter and an air supply fan.

A heat pump system for a vehicle may include: a HVAC module, a heat-exchanger, a first expansion, a first connection line, a chiller, a second expansion valve, a gas injection device, a second connection line, and a third connection line, in order to improve cooling and heating performance by applying a gas injection device that selectively operates in an air conditioning mode of vehicle interior to increase the flow rate of the refrigerant.

A liquid desiccant system includes a liquid desiccant loop having an absorber unit in fluid communication with a desorber unit and liquid desiccant flowing between the absorber unit and the desorber unit. The liquid desiccant system includes a supply airflow path passing through the absorber unit and forming an absorber liquid / air interface within the absorber unit and a conditioned airflow exiting the absorber unit. The liquid desiccant system includes a regeneration airflow path passing through the desorber unit and forming a desorber liquid / air interface within the desorber unit and an exhaust airflow exiting the desorber unit. A heat exchanger is thermally coupled to the supply airflow path for removing heat from supply airflow upstream of the absorber unit. A heat exchanger is thermally coupled to the regeneration airflow path adding heat to regeneration airflow upstream of the desorber unit.

The invention discloses a wind-feeling-free radiation type five-constant air conditioner multi-target self-adaptive optimization method and system, and belongs to the technical field of digital monitoring. A personnel density heat and humidity load model and a building heat and humidity response RC network model are established, long and short term memory neural network training is combined, and a humidity load increment rate and a temperature rising rate prediction value are output; a non-dominated sorting genetic algorithm is utilized to dynamically adjust temperature and humidity control weights, an optimal parameter combination is generated, and LSTM parameters are optimized through incremental learning; edge computing nodes are deployed, and LSTM reasoning and NSGA-II non-dominated sorting operation is accelerated by means of a tensor reasoning engine and a field-programmable gate array; a double-time scale strategy is adopted, a quick response layer directly outputs a control quantity during load fluctuation, a deep optimization layer is started to synchronously optimize energy efficiency and comfort after stabilization, energy efficiency is saved, real-time response in a personnel sudden increase scene is realized, algorithm time is compressed to match personnel sudden increase time scale, and energy efficiency and comfort are synchronously improved.

The utility model relates to the technical field of air conditioning, in particular to an air supply structure, an air supply system and a koji room. The air supply structure comprises an air supply branch pipe, a first air valve assembly and a second air valve assembly. One end of the air supply branch pipe is an air inlet end, and an air supply section with a plurality of air supply holes in the pipe wall is formed on the air supply branch pipe; the first air valve assembly comprises a first driving mechanism and a first air valve arranged in the air supply section, and the first driving mechanism is configured to drive the first air valve to move in the air supply section so as to be close to or away from the air inlet end; the second air valve assembly comprises a second air valve arranged in the air supply section, and the second air valve is located between the first air valve and the air inlet end. According to the method, targeted air supply can be conducted on the local heating area in the space, unnecessary whole-area air supply is reduced, cooling capacity is concentrated in the hot spot area, the method can adapt to constantly-changing hot spot positions, and the air supply area and the air supply amount can be adjusted.

The invention relates to an electrochromic window multi-scene control method, system and device based on indoor human body thermal comfort and a medium. The method comprises the steps that a perception data set is constructed; based on the sensing data set, performing multi-parameter coupling calculation of solar incidence azimuth deviation constraint and dynamic projection overlapping to obtain a direct radiation component, performing window space coupling analysis and double space compensation calculation to obtain a scattered radiation component, and performing fusion to obtain an individual thermal radiation influence value; determining a scene category based on the perception data set, and establishing a thermal radiation evaluation benchmark by adopting a mode matched with the scene category; and if the thermal radiation evaluation benchmark exceeds a preset threshold value, the required transmissivity of the window faces is obtained through a full-transmissivity radiation distribution method, the corresponding window faces are adjusted to the target transmission gradient according to the required transmissivity, and coupling control over the wind direction and / or power of the air conditioning system is selectively triggered. According to the invention, by constructing a multi-dimensional dynamic sensing system and an intelligent control framework, collaborative optimization of human body thermal comfort and building energy efficiency is realized.

The invention discloses an intelligent analysis and management method and system for an integrated controller, relates to the field of integrated control, and aims to complete complex air conditioning system identification model training and off-line optimization of an optimal PID parameter strategy by using historical data at a cloud end with sufficient computing power. And generating an expert strategy library containing various working conditions and corresponding optimal control parameters thereof. Then, a lightweight proxy model with small calculation amount and high reasoning speed is trained based on the strategy library; the proxy model is deployed on a resource-constrained edge controller. Therefore, the edge end does not need to execute complex online optimization calculation, and only needs to input the real-time working condition data into the agent model, so that the current optimal PID parameter can be quickly deduced. According to the cloud training and edge reasoning architecture, online, real-time and intelligent self-tuning of controller parameters is realized, and a gap between an advanced algorithm and industrial landing is effectively filled up.

The application discloses a kind of in-service air conditioner performance detection device and method.The device is composed of wind receiving chamber, exhaust chamber, return air chamber, differential pressure gauge, two mixers, heating wire and humidifier, return air temperature and humidity probe and return air motor.The device uses electric heating wire heat balance air conditioner refrigeration capacity, through heating and humidification method, air conditioner blows out the air to the detection required temperature and humidity state, and is connected to the return air opening of air conditioner, circulates and operates to reach stable state and has continuous condensate, uses electric energy meter to collect the electric energy of heating wire 1h, and synchronously collects the condensate amount generated by air conditioner 1h, according to the data collected, the performance of in-service air conditioner can be calculated, without disassembling air conditioner, avoid damage to in-service air conditioner.

The invention relates to an energy-saving control strategy for a medical building air-conditioning ventilation system based on climate change characteristics and load prediction. The energy-saving control strategy comprises the following steps of: acquiring all original data by utilizing various sensors, actuators and the like of a sensing layer; calculating, optimizing and deciding on an intelligent control layer (including building comprehensive cooling and heating load prediction, clean operation department area cooling and heating demand calculation, dynamic water supply temperature optimization, a particle swarm optimization (PSO) algorithm for domain optimization, constraint check and other algorithm modules) on a central management server; and an optimization result is issued to the execution layer and the executed equipment layer, so that energy-saving control is finally realized. The method overcomes the defects that the existing hospital building load prediction technology mostly adopts a macroscopic and rough prediction model, and the global optimization particle swarm optimization algorithm is slow in convergence and long in solving time when coping with a large medical building adopting multiple types of cold and heat source equipment. The device is suitable for large-scale hospital projects in hot-summer and warm-winter areas.

The invention discloses a new energy ventilation and heat exchange device, and relates to the technical field of air conditioning devices.The device comprises a shell, a mounting barrel is fixedly connected to the interior of the shell, and a ventilation and heat exchange mechanism used for extracting high-temperature air in a workshop is arranged in the mounting barrel; an auxiliary mechanism for assisting the ventilation and heat exchange mechanism in extracting high-temperature air is further arranged in the mounting cylinder, air in the workshop can be extracted by changing the distance between a flow guide plate and fan blades and the included angle between a matching plate and the fan blades and rotating the fan blades, the ventilation and heat exchange effects are achieved, and the service life of the workshop is prolonged. And through linkage cooperation of the auxiliary mechanism and the gain mechanism, the heat production rule of'stage work 'of equipment in the workshop is adapted, efficient ventilation of'adjustment as needed' is achieved, the situation that high-temperature air in the workshop cannot be exhausted in time is avoided, and the stability of air adjustment in the workshop can be effectively improved.

The invention relates to the technical field of refrigeration cycle, and discloses a dry filter of an air conditioner refrigeration cycle system, which comprises a shell, a liquid inlet at the front end of the shell and a liquid outlet at the tail end of the shell, and a front filter plate and a rear filter plate are respectively mounted in the hollow annular table in a sliding manner. The space of the front drying cavity is increased, so that when small particles generated by pulverization of a drying agent are led to the rear drying cavity, the drying agent in the rear drying cavity is kept in a compact state at the moment, and it is ensured that the rear drying cavity has the capacity of adsorbing moisture in a refrigerant; when the space of the rear drying cavity is increased, small particles generated by pulverization of the drying agent are discharged out of the drying cavity, at the moment, the drying agent in the front drying cavity is kept in a compact state, and it is ensured that the front drying cavity has the capacity of adsorbing moisture in the refrigerant. Therefore, small particles generated by pulverization of the drying agent can be effectively cleaned, and moisture in the refrigerant can be reliably removed.

According to the rural air conditioning device, coal or biomass straw is adopted as fuel, the energy storage technology is combined, flue gas waste heat generated by a kitchen range device is efficiently recycled and stored, the stored energy is used for dragging an absorption type refrigerating device to be used for refrigerating and heating air, and an adopted regenerator can flexibly adjust the operation mode and is used for peak clipping and valley filling; the energy-saving kitchen range is used for refrigerating, heating or drying clothes, the power consumption is low, the comprehensive heat utilization efficiency of the kitchen range is greatly improved, the market application space is obvious, and the expected economic, social and environment-friendly benefits are remarkable.

The invention provides an optimization control method for improving the energy efficiency ratio of the load of a multi-machine-head water chiller-heater unit, which comprises a first compressor system, a second compressor system and a control cabinet, the first compressor system and the second compressor system are both provided with corresponding power meters and microcomputer control modules, and the power meters and the microcomputer control modules are used for detecting the system power. The system further comprises an evaporator, a condenser, a temperature sensor, a flow meter and a pressure sensor, the temperature sensor, the flow meter and the pressure sensor are arranged on corresponding pipelines, the temperature sensor, the flow meter and the pressure sensor are all connected with the microcomputer control module, and differential loading and unloading strategies are adopted according to the load difference of the compressor. The operation parameters corresponding to the optimal COP are screened through multi-cycle iteration, and energy efficiency maximization under partial loads is achieved. The problem that in the prior art, when a multi-machine-head unit runs in a partial load mode, the energy efficiency is low due to lack of fine coordination control is solved, and the energy-saving potential of the unit is remarkably improved.