Intelligent control and adjustment method, device and equipment for refrigeration equipment and medium

Abstract

The invention relates to the technical field of refrigeration systems, and discloses an intelligent control and adjustment method, device and equipment for refrigeration equipment and a medium, and the method comprises the steps that necessary data including the environment temperature and refrigeration equipment performance parameters are acquired, and a prediction model is established according to the necessary data; based on the target use time period and the preset temperature range of the current place, pre-calculating the pre-cooling time according to the prediction model, determining the starting time for realizing the preset temperature value, and starting the refrigeration equipment; based on the current environment temperature, the duration of the current indoor temperature within the preset temperature range after the refrigeration equipment is turned off is calculated; and on the basis of the duration and the target use time period, the shutdown time of the refrigeration equipment is calculated, and the refrigeration equipment is controlled to be shut down. According to the method, the refrigeration strategy is automatically adjusted according to the environment temperature change, it is ensured that the indoor temperature is always within the comfortable range, and unnecessary carbon emission and energy consumption are reduced.

Description

Technical Field

[0001] The present application relates to the technical field of refrigeration systems, and in particular to an intelligent control and regulation method, device, equipment and medium for refrigeration equipment. Background Art

[0002] With the development of science and technology and the improvement of people's living standards, the requirements for indoor environmental comfort are getting higher and higher. As an important tool for regulating indoor temperature, intelligent control of refrigeration equipment is particularly important. Traditional refrigeration equipment usually adopts fixed temperature settings or simple timing control, which cannot be intelligently adjusted according to the actual environment and usage needs, resulting in energy waste and inconvenience in use.

[0003] Therefore, the timed start and stop of traditional refrigeration equipment during the refrigeration process cannot be intelligently started and stopped to meet the actual needs of users, and the problem of energy waste caused by timed switches needs to be solved urgently. Summary of the invention

[0004] The main purpose of this application is to solve the problem that the timed start and stop of traditional refrigeration equipment during the refrigeration process cannot be intelligently started and stopped to meet the actual needs of users, and the timer switch causes energy waste. Therefore, the first aspect of this application proposes to provide an intelligent control and adjustment method for refrigeration equipment, including: Obtaining necessary data including ambient temperature and refrigeration equipment performance parameters, and establishing a prediction model based on the necessary data; Based on the target usage time period and the preset temperature range of the current place, pre-calculate the pre-cooling time according to the prediction model, determine the start time to achieve the preset temperature value, and start the refrigeration equipment; Based on the current ambient temperature, calculate the duration of the current indoor temperature within the preset temperature range after the refrigeration equipment is turned off; Based on the duration and the target usage time period, the deactivation time of the refrigeration equipment is calculated, and the refrigeration equipment is controlled to be shut down.

[0005] Furthermore, the step of acquiring necessary data including ambient temperature and refrigeration equipment performance parameters, and establishing a prediction model based on the necessary data includes: Obtain outdoor temperature data from an outdoor temperature sensor or a third-party API interface and indoor initial temperature data collected by an indoor temperature sensor in real time, and transmit the outdoor temperature data and the indoor initial temperature data to a central control unit through a wireless communication module; According to the indoor space parameters, a dynamic model of cooling capacity and indoor temperature change is established, the outdoor temperature measurement value and the indoor initial temperature measurement value are input into the dynamic model, and the dynamic model is trained using a machine learning algorithm to obtain a prediction model of the cooling effect after training.

[0006] Further, the step of precalculating the precooling time based on the target usage time period and the preset temperature range of the current place according to the prediction model, determining the start time for achieving the preset temperature value, and starting the refrigeration equipment includes: Based on the type of the place where the refrigeration equipment is used, obtaining a corresponding target usage time period; Get the preset temperature range; Calculate the cooling time required for the indoor temperature to reach a preset temperature range under the current ambient temperature based on the prediction model; Based on the duration of the cooling time, determine the time point at which the refrigeration equipment needs to be started when the target usage time period reaches a preset temperature range; If the time point for starting the refrigeration equipment is reached, the refrigeration equipment is controlled to start.

[0007] Furthermore, the step of acquiring the corresponding target usage time period based on the type of the usage location of the refrigeration equipment includes: Get the device usage location type input by the user; If the current space type is home, the target usage time period is determined based on the user's commuting time and working date; If the current space type is an office space, the target usage time period is determined based on the user's office hours and office dates; If the currently used space type is a commercial venue, the target use time period is determined based on the business hours of the commercial venue.

[0008] Furthermore, the step of calculating, based on the current ambient temperature, the duration for which the current indoor temperature can be within the preset temperature range after the refrigeration equipment is turned off includes: Calculate the rate of change of indoor temperature at the current ambient temperature; Calculating a first time duration required for the current indoor temperature to exceed the limit of the preset temperature range based on the change rate; Obtain the cooling capacity of the chilled water pump and calculate the cooling time corresponding to the current cooling capacity; The duration for which the current indoor temperature can be within the preset temperature range is calculated based on the first duration and the cooling time.

[0009] Further, after the step of calculating the rate of change of the indoor temperature under the current ambient temperature, the following steps are included: Get the traffic monitoring data in the database; The number of people loads corresponding to the current space based on the time period between the calculation of the crowd flow monitoring data and the end time of the target usage time period; Based on the occupant load number, a prediction model is used to calculate and update a rate of change of the indoor temperature under the existing ambient temperature.

[0010] Furthermore, the step of calculating the deactivation time of the refrigeration equipment based on the duration and the target usage time period, and controlling the refrigeration equipment to shut down includes: When it is recognized that the sum of the current time and the duration exceeds the end time of the target usage time period, the current time is determined to be the deactivation time; The host of the refrigeration equipment is controlled to be shut down based on the deactivation time, wherein the chilled water pump continues to operate.

[0011] The second aspect of the present application further provides an intelligent control and adjustment device for refrigeration equipment, comprising: A model building module, used to obtain necessary data including ambient temperature and refrigeration equipment performance parameters, and to build a prediction model based on the necessary data; A startup calculation module is used to pre-calculate the pre-cooling time according to the prediction model based on the target usage time period and the preset temperature range of the current place, determine the startup time to achieve the preset temperature value, and start the refrigeration equipment; A duration calculation module, used to calculate, based on the current ambient temperature, the duration for which the current indoor temperature can remain within the preset temperature range after the refrigeration equipment is turned off; The shutdown control module is used to calculate the deactivation time of the refrigeration equipment based on the duration and the target usage time period, and control the refrigeration equipment to be shut down.

[0012] A third aspect of the present application provides a computer device, comprising: processor; Memory for storing computer programs; Wherein, when the processor executes the computer program, the intelligent control and regulation method for the refrigeration equipment described in any one of the above is implemented.

[0013] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the intelligent control and regulation method for refrigeration equipment described in any one of the above is implemented.

[0014] Beneficial effects: By acquiring the ambient temperature and refrigeration equipment performance parameters and establishing a prediction model, this application can accurately pre-calculate the pre-cooling time and reasonably determine the start and stop time of the refrigeration equipment, thereby effectively avoiding the energy waste caused by traditional timing control and improving energy utilization efficiency. At the same time, based on the target usage time period and preset temperature range of the current place, the start and stop time of the refrigeration equipment is intelligently adjusted to ensure that the indoor temperature is always within a comfortable range during the time period required by the user, significantly improving the user experience. In addition, through the prediction model and dynamic adjustment, the intelligent control of the refrigeration equipment is realized, reducing the need for human intervention and making the equipment operation more automated and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of the steps of an intelligent control and adjustment method for refrigeration equipment according to an embodiment of the present application; Figure 2 This is a schematic structural block diagram of an intelligent control and adjustment device for refrigeration equipment according to an embodiment of the present application; Figure 3 is a schematic block diagram of the structure of a computer device according to an embodiment of the present application; The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0017] It will be appreciated by those skilled in the art that, unless expressly stated, the singular forms "one", "above", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of features, integers, steps, operations, elements, modules, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, modules, components, and / or groups thereof. It should be understood that when an element is said to be "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may also be an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any module and all combinations of one or more associated listed items.

[0018] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as generally understood by those skilled in the art to which this application belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as here.

[0019] Reference Figure 1 The present application provides an intelligent control and adjustment method for refrigeration equipment, comprising the following steps: S1. Obtain necessary data including ambient temperature and refrigeration equipment performance parameters, and establish a prediction model based on the necessary data; In the step, the system first obtains the current outdoor temperature and the indoor initial temperature through the temperature sensors installed indoors and outdoors. These sensors can be independent devices or integrated into the refrigeration equipment. In addition, outdoor weather forecast data can be obtained through a third-party API interface to supplement the real-time temperature information. The acquired temperature data is transmitted to the central control unit through a wireless communication module (such as Wi-Fi, Bluetooth, etc.). The central control unit establishes a dynamic model of cooling capacity and indoor temperature changes based on indoor space parameters (such as room size, wall material, etc.). This model describes the change of indoor temperature over time when the refrigeration equipment is working under given conditions. The acquired outdoor temperature and indoor initial temperature data are input into the dynamic model, and the model is trained using a machine learning algorithm (such as support vector machine, neural network, etc.), and finally a model that can predict the cooling effect is obtained.

[0020] S2. Based on the target usage time period and preset temperature range of the current place, pre-calculate the pre-cooling time according to the prediction model, determine the start time to achieve the preset temperature value, and start the refrigeration equipment; First, the system obtains the corresponding target usage time period according to the type of use place where the refrigeration equipment is located (such as home, office, commercial place, etc.). For example, for home places, the target usage time period can be determined based on the user's commuting time and working day; for office places, the target usage time period can be determined based on the user's office hours and office days; for commercial places, the target usage time period can be determined based on the business hours of the commercial place. The system also obtains the temperature range preset by the user, such as 22°C to 26°C. The preset temperature can be a fixed temperature preset by the user, or it can be the most suitable ambient temperature for the human body calculated by data based on the current season and weather temperature. Then, based on the trained prediction model, the cooling time required for the indoor temperature to reach the preset temperature range under the current ambient temperature is calculated. According to the calculated cooling time, it is determined how long before the start of the target usage time period the refrigeration equipment needs to be started. When the start time point is reached, the system controls the refrigeration equipment to start to ensure that the indoor temperature reaches the preset range within the target usage time period.

[0021] S3. Based on the current ambient temperature, calculate the duration for which the current indoor temperature can remain within the preset temperature range after the refrigeration equipment is turned off; After the refrigeration equipment has been running for a period of time, the system calculates the rate of change of the indoor temperature under the current ambient temperature. The trend of change can be predicted by the current indoor and outdoor temperature, house area, and indoor heat load. Specifically, the model is trained through the historical data of temperature changes under natural conditions in the past, and then the temperature change trend under the current natural state, that is, the rate of change, is estimated based on the model. Based on the rate of change, the system calculates the time (first duration) required for the current indoor temperature to exceed the preset temperature range under natural conditions (that is, non-refrigeration conditions). At the same time, the system can obtain the cold storage capacity of the chilled water pump and calculate the cooling time corresponding to the current cold storage capacity. Combining the first duration and the cooling time, the system calculates the duration of the current indoor temperature that can be maintained within the preset temperature range after the refrigeration equipment is turned off. Since the chilled water pump itself has a cold storage function, even after the host of the refrigeration equipment is turned off, the cold storage function of the chilled water pump itself can still be used to extend the duration of the current temperature. In addition, if the user needs to advance the time of shutting down the host in advance in order to further save energy, so as to save more energy, the user can set a fixed time to shut down the refrigeration equipment, and calculate if the temperature needs to be maintained within the preset temperature range at the end of the target usage time period. Based on the fixed time set by the user to shut down the refrigeration equipment in advance, calculate how much the water temperature of the chilled water pump needs to be lowered before shutting down the refrigeration equipment, so that the current environment can be maintained within the preset temperature range at the end of the target usage time period, and based on the calculation result, the water temperature of the chilled water pump is lowered accordingly before shutting down the refrigeration equipment.

[0022] Step S4: Calculate the deactivation time of the refrigeration equipment based on the duration and the target usage time period, and control the refrigeration equipment to shut down.

[0023] When the system recognizes that the current time plus the duration exceeds the end time of the target usage time period, it determines that the current time is the deactivation time of the refrigeration equipment. The system controls the host of the refrigeration equipment to shut down, but the chilled water pump continues to run to use the remaining cold storage to maintain the indoor temperature within the preset range.

[0024] In one embodiment, the step of acquiring necessary data including ambient temperature and refrigeration equipment performance parameters, and establishing a prediction model based on the necessary data includes: S11, obtaining outdoor temperature data and indoor initial temperature data collected by indoor temperature sensors in real time through an outdoor temperature sensor or a third-party API interface, and transmitting the outdoor temperature data and the indoor initial temperature data to a central control unit through a wireless communication module; S12. According to the indoor space parameters, a dynamic model of cooling capacity and indoor temperature change is established, the outdoor temperature measurement value and the indoor initial temperature measurement value are input into the dynamic model, and the dynamic model is trained using a machine learning algorithm to obtain a prediction model of the cooling effect after training.

[0025] In this embodiment, the outdoor temperature sensor is installed outdoors for real-time monitoring of the outdoor temperature. The indoor temperature sensor is installed indoors for collecting the indoor initial temperature. These sensors transmit temperature data to the central control unit through a wireless communication module (such as Wi-Fi, Bluetooth, etc.). The central control unit can be a controller installed locally or a cloud server. In order to improve the accuracy and reliability of the data, the system can also obtain outdoor weather forecast data through a third-party API interface. These data include information such as temperature changes, humidity, wind speed, etc. in the next few hours, which helps to more accurately predict the trend of indoor temperature changes. The central control unit establishes a dynamic model that describes the relationship between cooling capacity and indoor temperature changes based on indoor space parameters (such as room area, wall material, number of windows, etc.). The model can be a physical model that describes the change of indoor temperature over time when the refrigeration equipment is working under given conditions. The acquired outdoor temperature and indoor initial temperature data are input into the dynamic model, and the model is trained using a machine learning algorithm (such as a decision tree, random forest, support vector machine, neural network, etc.). During the training process, the system will continuously adjust the parameters of the model so that the prediction results of the model are as close as possible to the actual temperature change data. Finally, a model that can predict the cooling effect is obtained. The model can be used to predict the changing trend of indoor temperature when the refrigeration equipment is running under different environmental conditions.

[0026] In one embodiment, the step of precalculating the precooling time according to the prediction model based on the target usage time period and the preset temperature range of the current place, determining the start time for achieving the preset temperature value, and starting the refrigeration equipment includes: S21. Based on the type of the place where the refrigeration equipment is used, obtaining a corresponding target usage time period; S22, obtaining a preset temperature range; S23, calculating the cooling time required for the indoor temperature to reach a preset temperature range under the current ambient temperature based on the prediction model; S24, based on the duration of the cooling time, determining the time point at which the refrigeration equipment needs to be started when the target usage time period reaches a preset temperature range; S25: If the time point for starting the refrigeration equipment is reached, control the refrigeration equipment to start.

[0027] In this embodiment, the system obtains the corresponding target usage time period according to the type of use place where the refrigeration equipment is located (such as home, office, commercial place, etc.). For example, for home-type places, the target usage time period can be determined based on the user's commuting time and working day; for office-type places, the target usage time period can be determined based on the user's office hours and working days; for commercial places, the target usage time period can be determined based on the business hours of the commercial place. The user can select the type of place where the equipment is used through the interface of the central control unit, and the system will automatically obtain the corresponding target usage time period according to the user's selection. For example, if the user selects a home-type place, the system will determine the target usage time period based on the user's commuting time and working day; if the user selects an office-type place, the system will determine the target usage time period based on the user's office hours and working days; if the user selects a commercial place, the system will determine the target usage time period based on the business hours of the commercial place. The user can set a preset temperature range, such as 22°C to 26°C, through the interface of the central control unit. The central control unit can store these temperature range values ​​in the memory for subsequent calculation and use. The preset temperature range can be adjusted according to the user's comfort requirements, for example, it can be set to 22°C to 26°C in summer and 18°C ​​to 22°C in winter. The system inputs the current ambient temperature (including outdoor temperature and indoor temperature) into the trained prediction model and calculates the cooling time required for the indoor temperature to reach the preset temperature range. The calculation result of the cooling time will be used to determine the start time of the cooling equipment. To improve the accuracy of the calculation, the system can consider multiple factors, such as changes in outdoor temperature, changes in indoor heat load, performance parameters of the cooling equipment, etc. For example, if the outdoor temperature is high, the system will predict that the indoor temperature will rise faster, so a longer cooling time is required; if the indoor heat load is large, the system will predict that the indoor temperature will fall slowly, so a longer cooling time is also required. Based on the calculated cooling time, the system determines how long before the target usage time period begins that the cooling equipment needs to be started. For example, if the cooling time is 1 hour and the target usage time period starts at 9 am, the system will determine that the cooling equipment needs to be started at 8 am. In order to ensure that the indoor temperature reaches the preset range within the target usage time period, the system will consider a certain safety margin. For example, if the cooling time is 1 hour, the system may start the cooling equipment 1.2 hours in advance to ensure that the indoor temperature is stable within the preset range during the target usage time period. When the system recognizes that the current time has reached the start-up time point, it controls the refrigeration equipment to start up to ensure that the indoor temperature reaches the preset range within the target usage time period. During the startup process, the system monitors the changes in the indoor temperature. If the indoor temperature is close to the preset range, the system can appropriately reduce the power of the refrigeration equipment to avoid the indoor temperature being too low.

[0028] In one embodiment, the step of acquiring the corresponding target usage time period based on the type of the usage location of the refrigeration equipment includes: S31, obtaining the device usage location type input by the user; S32: If the current space type is home, determine the target usage time period based on the user's commuting time and working date; S33: If the current space type is an office space, determine the target usage time period based on the user's office hours and office dates; S34: If the currently used space type is a commercial venue, determine the target use time period based on the business hours of the commercial venue.

[0029] In this embodiment, the user can select the type of place where the device is used, such as home, office, commercial place, etc. through the interface of the central control unit. The central control unit stores this information in the memory for subsequent calculation and use. In order to facilitate the user's selection, the system can provide multiple place type options, such as home, office, commercial place, hospital, school, etc. The user can select the appropriate place type according to the actual use scenario. If the current space type is a home type, the system will determine the target use time period according to the user's commuting time and working date. For example, if the user's working hours are from 9 am to 6 pm, the system will determine the target use time period from 6 pm to 9 am the next day. In order to improve accuracy, the system can consider the user's personal habits, such as whether he is at home on weekends, whether he travels on holidays, etc. The user can set this information through the interface of the central control unit, and the system will automatically adjust the target use time period according to the user's settings. If the current space type is an office type, the system will determine the target use time period according to the user's office hours and office dates. For example, if the user's office hours are from 9 am to 6 pm, the system will determine the target use time period from 9 am to 6 pm. In order to improve accuracy, the system can consider the actual use of the office, such as whether there is overtime, whether there is a meeting, etc. The user can set this information through the interface of the central control unit, and the system will automatically adjust the target usage time period according to the user's settings. Among them, during irregular startup time periods, such as weekends or holidays, a confirmation tweet is sent to the user's device before startup. If the user's confirmation instruction is detected, pre-cooling can be turned on. If the current space type is a commercial venue, the system will determine the target usage time period based on the business hours of the commercial venue. For example, if the business hours of a commercial venue are from 10 am to 10 pm, the system will determine the target usage time period as 10 am to 10 pm. In order to improve accuracy, the system can take into account the actual usage of commercial venues, such as whether there are special activities, whether there is a break, etc. Users can set this information through the interface of the central control unit, and the system will automatically adjust the target usage time period according to the user's settings.

[0030] In one embodiment, the step of calculating, based on the current ambient temperature, the duration for which the current indoor temperature can remain within the preset temperature range after the refrigeration device is turned off, comprises: S41, calculating the rate of change of the indoor temperature under the current ambient temperature; S42, calculating a first time required for the current indoor temperature to exceed the limit of the preset temperature range based on the change rate; S43, obtaining the cold storage capacity of the chilled water pump and calculating the cooling time corresponding to the current cold storage capacity; S44, calculating the total time that the current indoor temperature remains within a preset range based on the first duration and the cooling time; In this embodiment, the system calculates the indoor temperature change rate at the current ambient temperature by the temperature change of the indoor temperature sensor within a certain period of time. For example, if the indoor temperature can rise by 1°C within 10 minutes under natural conditions according to historical records, the change rate is 0.1°C / minute. In order to improve the accuracy of the calculation, the system can consider multiple factors, such as changes in outdoor temperature, changes in indoor heat load, performance parameters of refrigeration equipment, etc. For example, if the outdoor temperature is high, the system will predict that the indoor temperature will rise faster, so the change rate will be larger; based on the calculated indoor temperature change rate, the system calculates the time required for the current indoor temperature to exceed the preset temperature range (the first duration). For example, if the current indoor temperature is 22°C, the preset temperature range is 22°C to 26°C, and the change rate is 0.1°C / minute, then the time required for the indoor temperature to exceed 26°C is 40 minutes. In order to improve the accuracy of the calculation, the system can consider the change trend of the indoor temperature. For example, if the indoor temperature change trend is relatively stable, the system will predict that the indoor temperature will exceed the preset temperature range for a longer time; if the indoor temperature change trend is more drastic, the system will predict that the indoor temperature will exceed the preset temperature range for a shorter time. The system then obtains the cold storage capacity of the chilled water pump, which is the total cold storage capacity of the chilled water pump and its related cold storage system. The cold storage capacity is usually expressed in joules (J). The system calculates the cooling time corresponding to the current cold storage capacity. The cooling time refers to the cooling time that the cold storage capacity can provide under the current indoor heat load and the cooling effect of the chilled water pump. The formula is as follows: ; Among them: Q 蓄冷 is the cooling capacity of the chilled water pump (unit: J); P 热负荷 is the indoor heat load (unit: W); P 泵 is the cooling effect of the chilled water pump (unit: W); based on the first duration and the cooling time, the system calculates the duration that the current indoor temperature can be maintained within the preset temperature range after the refrigeration equipment is turned off. The formula is as follows: t 总 =min(t,t 蓄冷 ) Where: t is the time required for the indoor temperature to reach the preset upper temperature limit from the current value (unit: s) t 蓄冷 is the cooling time that the cold storage can provide (unit: s).

[0031] In one embodiment, after the step of calculating the rate of change of the indoor temperature under the current ambient temperature, the following steps are included: S51, obtaining the pedestrian flow monitoring data in the database; S52, calculating the number of personnel loads corresponding to the current space from the time period between the end time of the target usage time period and the time period based on the passenger flow monitoring data; S53: Based on the number of personnel loads, use a prediction model to calculate and update the rate of change of the indoor temperature under the existing ambient temperature.

[0032] The system obtains traffic monitoring data from the database, which can come from cameras, infrared sensors and other devices. Traffic data can help the system understand the number of people and activities in the current space. Based on the traffic monitoring data, the system calculates the number of people in the current space from the current time to the end of the target usage time period. The number of people will affect the rate of change of the indoor temperature. The next flow of people can also be predicted from historical data, such as taking a weekly or monthly data cycle to identify how much people are in the current place on the date or time point in the corresponding cycle, especially in large places such as shopping malls and schools with large traffic and frequent personnel flow. The system uses the number of people as input and uses the prediction model to calculate and update the rate of change of the indoor temperature under the existing ambient temperature. The updated rate of change will be used in subsequent calculations to improve the accuracy of the prediction.

[0033] In one embodiment, the step of calculating the deactivation time of the refrigeration device based on the duration and the target usage time period, and controlling the refrigeration device to shut down includes: S61, when it is identified that the sum of the current time and the duration exceeds the end time of the target usage time period, determining that the current time is the deactivation time; S62: Control the host of the refrigeration equipment to shut down based on the deactivation time, wherein the chilled water pump continues to run.

[0034] The system will monitor the current time in real time and add it to the calculated duration to determine whether it exceeds the end time of the target usage time period. For example, if the current time is 8 pm, the duration is 30 minutes, and the end time of the target usage time period is 10 pm, then the system will calculate whether 8 pm plus 30 minutes exceeds 10 pm. If it exceeds 10 pm, the system determines that the current time is the deactivation time. When the system determines that the current time is the deactivation time, the host controlling the refrigeration equipment is turned off, but the chilled water pump continues to run to use the remaining cold storage to maintain the indoor temperature within the preset range. This can save energy without affecting comfort.

[0035] Referring to FIG2 , an intelligent control and adjustment device for refrigeration equipment includes: A model building module 100 is used to obtain necessary data including ambient temperature and refrigeration equipment performance parameters, and to build a prediction model based on the necessary data; The startup calculation module 200 is used to pre-calculate the pre-cooling time according to the prediction model based on the target usage time period and the preset temperature range of the current place, determine the startup time to achieve the preset temperature value, and start the refrigeration equipment; The duration calculation module 300 is used to calculate the duration of the current indoor temperature within the preset temperature range after the refrigeration equipment is turned off based on the current ambient temperature; The shutdown control module 400 is used to calculate the deactivation time of the refrigeration device based on the duration and the target usage time period, and control the refrigeration device to shut down.

[0036] Furthermore, the above-mentioned model building module 100 includes: A data acquisition unit is used to acquire the outdoor temperature data and the indoor initial temperature data collected by the indoor temperature sensor in real time through an outdoor temperature sensor or a third-party API interface, and transmit the outdoor temperature data and the indoor initial temperature data to a central control unit through a wireless communication module; The model training unit is used to establish a dynamic model of cooling capacity and indoor temperature changes according to indoor space parameters, input the outdoor temperature measurement value and the indoor initial temperature measurement value into the dynamic model, and use a machine learning algorithm to train the dynamic model to obtain a prediction model of the cooling effect after training.

[0037] Furthermore, the startup calculation module 200 includes: A usage time period acquisition unit, configured to acquire a corresponding target usage time period based on the type of the usage location of the refrigeration equipment; A temperature range acquisition unit, used to acquire a preset temperature range; A cooling time calculation unit, used to calculate the cooling time required for the indoor temperature to reach a preset temperature range under the current ambient temperature based on the prediction model; A start-up time determination unit, configured to determine, based on the duration of the cooling time, a time point at which the refrigeration equipment needs to be started when the target usage time period reaches a preset temperature range; The start control unit is used to control the start of the refrigeration equipment if the start time of the refrigeration equipment is reached.

[0038] Furthermore, the above-mentioned usage time period acquisition unit includes: A location type acquisition subunit is used to acquire the device usage location type input by the user; A first determination subunit is used to determine the target usage time period based on the user's commuting time and working date if the current space type is a home type; A second determination subunit is used to determine the target usage time period based on the user's office hours and office dates if the current space type is an office space type; The third determining subunit is configured to determine the target usage time period based on the business hours of the commercial venue if the currently used space type is a commercial venue.

[0039] Furthermore, the duration calculation module 300 includes: A temperature change rate calculation unit, used to calculate the change rate of the indoor temperature under the current ambient temperature; A first duration calculation unit, configured to calculate a first duration required for the current indoor temperature to exceed the limit of the preset temperature range based on the change rate; A cold storage capacity calculation unit is used to obtain the cold storage capacity of the chilled water pump and calculate the cooling time corresponding to the current cold storage capacity; A duration calculation unit is used to calculate a duration during which the current indoor temperature can be within the preset temperature range based on the first duration and the cooling time.

[0040] Furthermore, after the temperature change rate calculation unit, it includes: A human flow monitoring unit, used to obtain human flow monitoring data in a database; A personnel load calculation unit, used to calculate the number of personnel loads corresponding to the current space in the time period between the time period of the target usage time period and the end time of the target usage time period based on the personnel flow monitoring data; The change rate updating unit is used to calculate and update the change rate of the indoor temperature under the existing ambient temperature based on the number of personnel loads using a prediction model.

[0041] Furthermore, the above-mentioned shutdown control module 400 includes: a deactivation time determination unit, configured to determine that the current time is the deactivation time when it is recognized that the sum of the current time and the duration exceeds the end time of the target usage time period; A shutdown execution unit is used to control the host of the refrigeration equipment to shut down based on the deactivation time, wherein the freezing water pump continues to run.

[0042] Reference Figure 3 In an embodiment of the present application, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3As shown. The computer device includes a processor, a memory, a network interface and a database connected by a bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores operations, computer programs and databases. The internal memory provides an environment for the operation of the operations and computer programs in the non-volatile storage medium. The database of the computer device is used to store data such as an intelligent control and adjustment method for refrigeration equipment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an intelligent control and adjustment method for refrigeration equipment is implemented, including the steps of: obtaining necessary data including ambient temperature and refrigeration equipment performance parameters, and establishing a prediction model based on the necessary data; based on the target use time period and the preset temperature range of the current place, pre-calculating the pre-cooling time according to the prediction model, and determining the start time to achieve the preset temperature value, and starting the refrigeration equipment; based on the current ambient temperature, calculating the duration of the current indoor temperature in the preset temperature range after the refrigeration equipment is turned off; based on the duration and the target use time period, calculating the deactivation time of the refrigeration equipment, and controlling the refrigeration equipment to turn off.

[0043] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, an intelligent control and adjustment method for refrigeration equipment is implemented, including the following steps: obtaining necessary data including ambient temperature and performance parameters of refrigeration equipment, and establishing a prediction model based on the necessary data; based on the target usage time period and preset temperature range of the current place, pre-calculating the pre-cooling time according to the prediction model, and determining the start time for achieving the preset temperature value, and starting the refrigeration equipment; based on the current ambient temperature, calculating the duration of the current indoor temperature within the preset temperature range after the refrigeration equipment is turned off; based on the duration and the target usage time period, calculating the deactivation time of the refrigeration equipment, and controlling the refrigeration equipment to be turned off.

[0044] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0045] The above description is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An intelligent control and adjustment method for refrigeration equipment, characterized in that: include: Obtaining necessary data including ambient temperature and refrigeration equipment performance parameters, and establishing a prediction model based on the necessary data; Based on the target usage time period and the preset temperature range of the current place, pre-calculate the pre-cooling time according to the prediction model, determine the start time to achieve the preset temperature value, and start the refrigeration equipment; Based on the current ambient temperature, calculate the duration of the current indoor temperature within the preset temperature range after the refrigeration equipment is turned off; Based on the duration and the target usage time period, the deactivation time of the refrigeration equipment is calculated, and the refrigeration equipment is controlled to be shut down.

2. The intelligent control and adjustment method for refrigeration equipment according to claim 1, characterized in that: The step of obtaining necessary data including ambient temperature and refrigeration equipment performance parameters, and establishing a prediction model based on the necessary data, includes: Obtain outdoor temperature data from an outdoor temperature sensor or a third-party API interface and indoor initial temperature data collected by an indoor temperature sensor in real time, and transmit the outdoor temperature data and the indoor initial temperature data to a central control unit through a wireless communication module; According to the indoor space parameters, a dynamic model of cooling capacity and indoor temperature change is established, the outdoor temperature measurement value and the indoor initial temperature measurement value are input into the dynamic model, and the dynamic model is trained using a machine learning algorithm to obtain a prediction model of the cooling effect after training.

3. The intelligent control and adjustment method for refrigeration equipment according to claim 1, characterized in that: The step of precalculating the precooling time based on the target usage time period and the preset temperature range of the current place according to the prediction model, determining the start time for achieving the preset temperature value, and starting the refrigeration equipment includes: Based on the type of the place where the refrigeration equipment is used, obtaining a corresponding target usage time period; Get the preset temperature range; Calculate the cooling time required for the indoor temperature to reach a preset temperature range under the current ambient temperature based on the prediction model; Based on the duration of the cooling time, determine the time point at which the refrigeration equipment needs to be started when the target usage time period reaches a preset temperature range; If the time point for starting the refrigeration equipment is reached, the refrigeration equipment is controlled to start.

4. The intelligent control and adjustment method for refrigeration equipment according to claim 3 is characterized in that: The step of obtaining a corresponding target usage time period based on the type of the usage location of the refrigeration equipment includes: Get the device usage location type input by the user; If the current space type is home, the target usage time period is determined based on the user's commuting time and working date; If the current space type is an office space, the target usage time period is determined based on the user's office hours and office dates; If the current usage space type is a commercial venue, the target usage time period is determined based on the business hours of the commercial venue.

5. The intelligent control and adjustment method for refrigeration equipment according to claim 1, characterized in that: The step of calculating, based on the current ambient temperature, the duration for which the current indoor temperature can be within the preset temperature range after the refrigeration equipment is turned off comprises: Calculate the rate of change of indoor temperature at the current ambient temperature; Calculating a first time duration required for the current indoor temperature to exceed the limit of the preset temperature range based on the change rate; Obtain the cooling capacity of the chilled water pump and calculate the cooling time corresponding to the current cooling capacity; The duration for which the current indoor temperature can be within the preset temperature range is calculated based on the first duration and the cooling time.

6. The intelligent control and adjustment method for refrigeration equipment according to claim 5, characterized in that: After the step of calculating the rate of change of the indoor temperature at the current ambient temperature, the method further comprises: Get the traffic monitoring data in the database; The number of people loads corresponding to the current space based on the time period between the calculation of the crowd flow monitoring data and the end time of the target usage time period; Based on the occupant load number, a prediction model is used to calculate and update a rate of change of the indoor temperature under the existing ambient temperature.

7. The intelligent control and adjustment method for refrigeration equipment according to claim 1, characterized in that: The step of calculating the deactivation time of the refrigeration equipment based on the duration and the target usage time period, and controlling the refrigeration equipment to shut down includes: When it is recognized that the sum of the current time and the duration exceeds the end time of the target usage time period, the current time is determined to be the deactivation time; The host of the refrigeration equipment is controlled to be shut down based on the deactivation time, wherein the chilled water pump continues to operate.

8. An intelligent control and adjustment device for refrigeration equipment, characterized in that: include: A model building module, used to obtain necessary data including ambient temperature and refrigeration equipment performance parameters, and to build a prediction model based on the necessary data; A startup calculation module is used to pre-calculate the pre-cooling time according to the prediction model based on the target usage time period and the preset temperature range of the current place, determine the startup time to achieve the preset temperature value, and start the refrigeration equipment; A duration calculation module, used to calculate, based on the current ambient temperature, the duration for which the current indoor temperature can remain within the preset temperature range after the refrigeration equipment is turned off; The shutdown control module is used to calculate the deactivation time of the refrigeration equipment based on the duration and the target usage time period, and control the refrigeration equipment to shut down.

9. A computer device, characterized in that: include: processor; Memory for storing computer programs; Wherein, when the processor executes the computer program, the intelligent control and adjustment method for the refrigeration equipment according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the intelligent control and regulation method for the refrigeration equipment according to any one of claims 1 to 7 is implemented.

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