Refrigeration house control method, controller, air conditioner and refrigeration house

Abstract

The invention provides a control method of a refrigeration house, a controller, an air conditioner and the refrigeration house. Under the condition that the target goods are not put in storage or taken out of storage, the first information is received, the quality information and the current temperature information of the target goods are obtained in advance, the first target thermal load data are calculated in combination with the environment parameters (such as the temperature parameters) of the current cold storage, and therefore the first target thermal load data are obtained before the goods are put in storage or taken out of storage. And dynamically adjusting environmental parameters (such as temperature parameters) of the refrigeration house according to a calculation result. The method effectively solves the problem that the temperature control of the refrigeration house, especially the refrigeration house with frequent goods input and output, is not accurate enough in the prior art. By adjusting the operation state of the environment adjusting equipment in advance, for example, the compressor frequency, the fan rotating speed and the control valve opening degree of the refrigeration equipment are optimized, the temperature of the refrigeration house can be accurately reduced before goods are put in storage, or the temperature of the refrigeration house can be properly increased before goods are taken out of storage, and therefore the problem of temperature adjustment lag is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of cold storage, and in particular to a control method, a controller, an air conditioner and a cold storage. Background Art

[0002] Cold storage is a special facility used to store goods in a low-temperature environment. It can control the internal temperature within the target range through refrigeration equipment to extend the shelf life and preservation quality of goods. Cold storage is mainly used for food, medicine, chemical products and other items that need to be stored at low temperatures, which can effectively slow down the process of corruption, deterioration or activity reduction of goods.

[0003] In the related art, for cold storage, especially cold storage with frequent incoming and outgoing goods, there is a technical problem of inaccurate temperature control. Summary of the invention

[0004] The purpose of the present invention is to overcome the above technical deficiencies and provide a control method, controller, air conditioner and cold storage to solve the technical problem in the related art that the temperature control of cold storage, especially cold storage with frequent inflow and outflow, is not accurate enough. In order to achieve the above technical objectives, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for controlling a cold storage, the method comprising: When the target goods have not yet been put into the warehouse or have not yet been taken out of the warehouse, receiving first information; the first information is information indicating that the target goods will be put into the warehouse or will be taken out of the warehouse; wherein the first information at least includes quality information and current temperature information of the target goods; Obtaining the current environmental parameters of the cold storage; wherein the environmental parameters at least include temperature parameters; Calculating first target heat load data based on the first information and temperature parameters; According to the first target heat load data, the preset environmental adjustment equipment is controlled to adjust the environmental parameters of the current cold storage.

[0005] In a second aspect, the present invention provides a controller, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor so that the at least one processor can perform the above method.

[0006] In a third aspect, the present invention provides an air conditioner, characterized in that it comprises the above-mentioned controller.

[0007] In a fourth aspect, the present invention provides a cold storage comprising the above-mentioned air conditioner and environmental parameter detection device; wherein the controller in the air conditioner is communicatively connected with the environmental parameter detection device; the environmental parameter detection device is at least used to collect temperature parameters and send them to the controller.

[0008] Beneficial effects: The present invention receives the first information when the target goods have not yet been put into storage or have not yet been shipped out, obtains the quality information and current temperature information of the target goods in advance, and calculates the first target heat load data in combination with the environmental parameters (such as temperature parameters) of the current cold storage, so that the environmental parameters (such as temperature parameters) of the cold storage are dynamically adjusted according to the calculation results before the goods are actually put into storage or shipped out. This method effectively solves the problem of inaccurate temperature control for cold storage, especially cold storage with frequent inflow and outflow in the related art. By adjusting the operating state of the environmental adjustment equipment in advance, such as optimizing the compressor frequency, fan speed and control valve opening of the refrigeration equipment, the temperature of the cold storage can be accurately reduced before the goods are put into storage, or the temperature of the cold storage can be appropriately increased before the goods are shipped out, thereby avoiding the problem of temperature adjustment lag. At the same time, the present invention can adapt to the changes in the types of goods and heat loads, dynamically adjust the cold storage environment, improve the temperature control accuracy and cold storage operation efficiency, reduce energy consumption, extend the fresh-keeping time of goods, and effectively improve the comprehensive use efficiency of the cold storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is a flow chart of a control method for a cold storage provided by an embodiment of the present invention; Figure 2 It is a flow chart of a control method for a cold storage provided by an embodiment of the present invention; Figure 3 It is a flow chart of a control method for a cold storage provided by an embodiment of the present invention; Figure 4 The present invention provides a block diagram of a cold storage. DETAILED DESCRIPTION

[0010] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0011] In the relevant technology, cold storage is used in cold chain logistics, food preservation, medicine storage and other fields. Its core function is to ensure that the goods are kept in the best storage state in the cold storage environment through precise temperature and humidity control. However, especially in the cold storage environment with frequent inbound and outbound goods, the control methods in the existing technology have many shortcomings and are difficult to meet actual needs.

[0012] A typical cold storage control system may include: 1. Refrigeration equipment, which may include compressors, condensers, evaporators and other devices, is used to achieve temperature regulation of cold storage; 2. Monitoring equipment, which may include temperature and humidity sensors, pressure sensors, etc., is used to monitor the internal environmental parameters of the cold storage in real time; 3. The controller can receive the data collected by the monitoring equipment through the PLC (programmable logic controller) or embedded controller, and adjust the refrigeration equipment; 4. Management software, which can be a warehouse entry and exit system. The warehouse entry and exit system is a software system on the host computer for items entering and leaving the warehouse. It can be used to improve warehouse management efficiency, ensure the accuracy of inventory data, reduce human errors, optimize inventory structure, and support supply management.

[0013] In the actual operation of the cold storage, when goods enter or leave the cold storage, the heat load inside the cold storage will change significantly. For example, when new goods enter the cold storage, the heat they carry will increase the heat load of the cold storage, causing the internal temperature to rise; when a large number of goods leave the cold storage, the heat load inside the cold storage will decrease significantly, which can easily lead to over-refrigeration.

[0014] Existing cold storage temperature control methods usually rely on simple fixed temperature settings, and passively adjust the temperature after detecting changes in the temperature inside the cold storage. This method has the following defects in cold storage scenarios with frequent inflow and outflow of goods: On the one hand, the existing technology adjusts the refrigeration equipment after detecting the temperature change, resulting in the temperature of the cold storage being unable to respond in time to the heat load changes caused by the goods entering and leaving the cold storage. The temperature does not drop fast enough after entering the cold storage, and the temperature is too low after leaving the cold storage, wasting energy.

[0015] On the other hand, when goods are frequently transported in and out, the fixed temperature control method cannot adjust the operating parameters of the refrigeration equipment according to the actual heat load, which can easily lead to over-refrigeration or insufficient refrigeration, significantly increasing energy consumption.

[0016] Therefore, in the related art, for cold storage, especially cold storage with frequent incoming and outgoing goods, there is a technical problem that the temperature control is not accurate enough.

[0017] In order to solve this technical problem, the present invention proposes a control method for cold storage. The present invention receives first information (for example, the time, quality, type, etc. of the target goods entering or leaving the warehouse), calculates the first target heat load data before the goods enter or leave the warehouse, and adjusts the refrigeration equipment in advance to ensure that the temperature can reach the appropriate range before the target time. When the goods are actually entering or leaving the warehouse, the second information such as the actual quality is obtained through the real-time detection equipment, the second target heat load data is calculated, the operating status of the refrigeration equipment is corrected, and precise temperature control is achieved.

[0018] like Figure 1 As shown, this embodiment provides a control method for a cold storage, the execution subject of the method may be a controller of the cold storage, and the method may include: Step S12: When the target goods have not yet been put into the warehouse or have not yet been taken out of the warehouse, receiving first information; the first information is information indicating that the target goods will be put into the warehouse or will be taken out of the warehouse; wherein the first information at least includes quality information and current temperature information of the target goods.

[0019] In this embodiment, the receiving action may be represented by the controller of the cold storage receiving the first information from the external device side.

[0020] Specifically, the external device may be a smart mobile device of the transporter, for example, a smart phone, a dedicated logistics handheld terminal or a portable scanning device, etc. The smart mobile device may be used to record and upload detailed information of the target goods (including the quality, type, estimated time of entry or exit of the goods, etc.).

[0021] The external device may be a terminal device of a warehouse management system (WMS), which may be a terminal device of the original storage warehouse or cold storage of the target goods (in the warehousing scenario), or a terminal device of the cold storage to which the target goods are to be transported (in the outbound scenario).

[0022] The external device may also be an intelligent vehicle-mounted terminal device installed on a transport vehicle, such as a vehicle dispatching system or a GPS tracking device, which can upload the transport status and estimated arrival time of the target goods in real time and transmit the relevant data to the controller of the cold storage.

[0023] The external device may also be a central management platform for cold chain logistics, which may serve as a host computer of the external device, communicate with the controller of the cold storage, and uniformly transmit cargo entry or exit plans, cargo lists, and related heat load data.

[0024] In this implementation, the first information may be structured information, such as a JSON file, an XML (Extensible Markup Language) file, a CSV (Comma Separated Values) file, an Excel file, and the like.

[0025] In this embodiment, the first information may be unstructured information, for example, it may be a free-format text file (e.g., a .txt file) which may contain descriptive information; it may be an image file containing cargo information (e.g., a cargo label, a shipping list, etc.) which may be in JPEG, PNG, or PDF format; it may be an audio file (e.g., MP3, WAV format) generated by a transporter recording cargo information by voice, and the like.

[0026] Specifically, the first information may include mass information of the target cargo, for example, in units of “kilogram (kg)” or “ton (t)”.

[0027] The first information may include type information of the target goods, for example, "apple", "frozen pork" and so on.

[0028] The first information may include the time information of the target goods to be put into the warehouse or the time information to be taken out of the warehouse. The format of the time information may be "YYYY-MM-DD", for example, "2024-01-20, 14:00".

[0029] The first information may also include storage requirements. The storage requirements may be suitable temperature and humidity ranges for the target goods, such as “temperature range: 2°C-8°C, humidity range: 85%-95%”.

[0030] The first information may also include the current temperature information of the target goods. The current temperature information may be the temperature information of the goods under cold chain transportation (in the case of storage), or the temperature information of non-cold chain transportation (in the case of storage), such as the outdoor ambient temperature. The current temperature information may be the temperature information of the cold storage (in the case of outbound transportation). Specifically, the current temperature information of the target cargo may be collected by a cold chain monitoring system installed on a transport vehicle (in the warehousing scenario).

[0031] The current temperature information of the target cargo may be collected by a sensor installed in the cargo transport container (in the warehousing scenario).

[0032] The current temperature information of the target goods can be obtained through weather forecasts or on-site temperature sensors to obtain the ambient temperature as a reference value for the current temperature of the goods (in the warehousing scenario).

[0033] The first information may also include packaging information of the target goods, such as "plastic bag" or "carton" and the like.

[0034] In this embodiment, the quality information of the target goods may be manually input into the smart mobile device by the transport personnel, may be measured by a weighing device, or may be recorded by a logistics management system.

[0035] In this embodiment, the type information of the target goods may be manually input into the smart mobile device by the transport personnel, or may be obtained by the terminal device automatically reading the barcode / RFID tag on the goods, or may be recorded by the logistics management system.

[0036] In this embodiment, the time information of the target goods entering the warehouse or leaving the warehouse can be automatically generated by the logistics management system, or can be manually input into the smart mobile device or terminal device by the transportation personnel or warehouse management personnel.

[0037] Step S14: Acquire the current environmental parameters of the cold storage; wherein the environmental parameters at least include temperature parameters.

[0038] In this embodiment, the environmental parameters may include temperature parameters, that is, data of the current real-time temperature of the cold storage.

[0039] In this embodiment, the environmental parameter may be a humidity parameter, that is, data of the real-time humidity of the current cold storage.

[0040] In this embodiment, the environmental parameters can be obtained by using an environmental parameter detection device preset inside the cold storage, which can be a temperature sensor or a humidity sensor.

[0041] In this embodiment, the controller can issue instructions to the environmental parameter detection device (temperature sensor, humidity sensor) to collect the current temperature parameters and humidity parameters. Specifically, the controller of the cold storage sends a collection instruction to the detection device by establishing a communication connection with the detection device (such as a temperature sensor and a humidity sensor). The communication method can be wired communication (for example, RS-485, CAN bus) or wireless communication (for example, Wi-Fi, ZigBee). After the temperature sensor receives the collection instruction, it detects the current air temperature of the cold storage in real time and transmits the data back to the controller. After the humidity sensor receives the collection instruction, it detects the current air humidity of the cold storage in real time and transmits the data back to the controller. The controller stores the collected environmental parameters (temperature and humidity) in a local storage module or memory. It can be understood that the stored environmental parameters will serve as the input basis for the subsequent calculation of the target heat load data.

[0042] Temperature sensors and humidity sensors can be set in the center of the cold storage, around the goods or in the corners of the cold storage. The controller can set the collection frequency according to the operation requirements of the cold storage, for example, collecting environmental parameters every 1 minute or 5 minutes. The controller can also send a collection instruction immediately after receiving the first information to obtain real-time environmental parameters.

[0043] In this embodiment, the environmental parameters may also include air flow rate parameters, that is, the speed of air flow inside the cold storage. It can be understood that the air flow rate will affect the uniformity of temperature and humidity inside the cold storage; a higher air flow rate can improve heat transfer efficiency, but may have an adverse effect on certain goods (such as air-dried food).

[0044] In this embodiment, the environmental parameters may also include carbon dioxide concentration parameters. It is understandable that some fruit and vegetable cold storages require strict control of carbon dioxide concentration to extend the shelf life (such as atmosphere-controlled cold storages).

[0045] It is understandable that, in the outbound scenario, the temperature parameter is often equal to the temperature information in the first information, because the target goods are stored in a cold storage at this time.

[0046] Step S16: Calculate first target heat load data based on the first information and temperature parameters.

[0047] In this embodiment, in the warehousing scenario, the target goods have not yet entered the cold storage, and their temperature is often higher than the temperature inside the cold storage, so the goods entering the cold storage will increase the heat load of the cold storage. Therefore, it is necessary to calculate the energy required by the cold storage to cool the goods to the cold storage temperature.

[0048] Therefore, based on the first information and the temperature parameter, the first target heat load data may be calculated as follows: First, the controller may parse the first information to obtain at least the quality information of the target goods and the current temperature information of the target goods.

[0049] Specifically, the cold storage controller may receive the first information via wired or wireless communication, and the first information may be structured data (eg, JSON, XML, CSV, etc.) or unstructured data (eg, text files, image files, voice recordings, etc.).

[0050] If it is structured data, the controller directly parses the data fields and extracts the quality information of the target goods. If it is unstructured data, the controller uses natural language processing (NLP), optical character recognition (OCR) or speech recognition (ASR) technology to parse the unstructured information and extract the quality of the target goods.

[0051] Then, the controller may calculate the temperature difference based on the current temperature information of the target cargo and the temperature parameter acquired in step S14.

[0052] In the formula, if >0, indicating that the goods need to be cooled. <0, indicating that the current temperature of the goods is lower than or equal to the cold storage temperature, and there is no need to increase the heat load.

[0053] Finally, the mass information, temperature difference and preset specific heat capacity data may be input into a preset heat load calculation model to obtain the first target heat load data.

[0054] Specifically, the preset specific heat capacity data may be an average specific heat capacity data or a priori specific heat capacity value. For example, when the cold storage is a cold storage dedicated to frozen meat items, and the target goods for each entry and exit are frozen meat items, the specific heat capacity data of the frozen meat items may be pre-configured.

[0055] It is understandable that when the target cargo type is unclear or the cargo types are diverse, an average specific heat capacity data can be used. For example, for a mixed cold storage, assuming that most of the cargo is food, the average specific heat capacity data of food, such as 3000J / (kg.℃), can be used. If the cold storage is a special cold storage (for example, a cold storage dedicated to frozen meat), the prior specific heat capacity data of the cold storage can be directly configured. For example, the specific heat capacity of frozen pork is 2050J / (kg.℃), and the specific heat capacity of frozen chicken is 1800J / (kg.℃).

[0056] The preset heat load calculation model may be: In the formula, can be expressed as the first target heat load, It can be expressed as the specific heat capacity of the target cargo, It can be expressed as a temperature difference, It can be expressed as the target cargo quality.

[0057] The controller can store the calculated first target heat load data to the controller to instruct the cold storage refrigeration equipment to cool down in advance, ensuring that the cold storage temperature can maintain the target value when the goods are put into storage.

[0058] In this embodiment, in the scenario of outbound delivery, a batch of target goods is about to be removed from the cold storage, and their temperature is already equal to the cold storage temperature. Therefore, after the goods are removed, the heat load of the cold storage will be reduced. Therefore, it is necessary to calculate the heat load reduction caused by the removal of the goods, so as to guide the power adjustment of the cold storage refrigeration equipment to avoid over-cooling.

[0059] Therefore, based on the first information and the temperature parameter, the first target heat load data may be calculated as follows: First, the controller may parse the first information to obtain at least the quality information of the target goods and the current temperature information of the target goods.

[0060] It is understandable that, in the outbound scenario, the current temperature information of the target goods is actually equal to the temperature parameter obtained in step S14.

[0061] It is understandable that since the temperature of the outgoing goods is equal to the cold storage temperature, In practice it is 0, but the total heat load of the cargo maintained at the cold storage temperature still needs to be considered in the heat load reduction calculation.

[0062] Then, confirm Temperature difference.

[0063] Should The temperature difference can be the temperature difference experienced by lowering the target goods from the external ambient temperature to the cold storage temperature, and can be used to describe the energy consumption of the cold storage to maintain the low temperature state of the goods.

[0064] Finally, this quality information, The temperature difference and the preset specific heat capacity data are input into a preset heat load calculation model to obtain the first target heat load data.

[0065] Similar to the warehousing scenario, the preset specific heat capacity data can be an average specific heat capacity data or a priori specific heat capacity value.

[0066] The preset heat load calculation model can be: In the formula, It is the temperature difference experienced by the goods from the external environment temperature to the cold storage temperature, and is used to describe the energy consumption of the cold storage to maintain the low temperature state of the goods.

[0067] In a specific scenario example: The target cargo mass is 800kg, the specific heat capacity is 2050J / (kg.℃), and the current cold storage temperature is The external ambient temperature is -18℃ is 25℃.

[0068] but The temperature difference is: =25-(-18)=43℃.

[0069] The heat load reduction is: =800*2050*43=70520000J.

[0070] The controller can store the calculated heat load reduction data in the controller to guide the cold storage refrigeration equipment to reduce power and avoid energy waste.

[0071] Step S18: According to the first target heat load data, the preset environment adjustment equipment is controlled to adjust the current environment parameters of the cold storage.

[0072] In this embodiment, the environment conditioning device may include a refrigeration device. Specifically, the refrigeration device may include: The compressor increases the pressure and temperature of the refrigerant by compressing it; Condenser: cools and liquefies the high-temperature and high-pressure refrigerant, releasing heat; Expansion valve: expands the refrigerant by reducing pressure, lowering its temperature; Evaporator: The refrigerant absorbs heat in the evaporator to cool down the interior of the cold storage; Cold storage fan: assists cold air circulation and improves refrigeration efficiency.

[0073] In this embodiment, according to the first target heat load data, the controller can generate control parameters (compressor frequency, fan speed, etc.), and then send a control signal to the refrigeration equipment to adjust the temperature parameters of the cold storage.

[0074] Specifically, in the warehousing scenario (heat load increases), the controller can increase the compressor frequency, increase the cold storage fan speed, and increase the condenser heat dissipation, etc. It is understandable that increasing the operating frequency of the compressor can improve the refrigeration capacity, and increasing the fan speed can accelerate the circulation and heat exchange of cold air.

[0075] Specifically, in the outbound scenario (heat load reduction), the controller can reduce the compressor frequency, reduce the cold storage fan speed, reduce the condenser heat dissipation, etc. The controller can also control the refrigeration equipment to enter standby mode, etc.

[0076] In a specific implementation, in the warehousing scenario, the controller can control the preset environmental adjustment equipment according to the first target heat load data to adjust the environmental parameters of the current cold storage by the following method.

[0077] First, the controller determines a target temperature based on the first target heat load data.

[0078] For example, the first target heat load data may be input into a preset target temperature gradient table to obtain a target temperature; wherein the target temperature gradient table is configured with a plurality of heat load intervals and corresponding target temperatures.

[0079] It can be understood that, the larger the first target heat load data is, the lower the target temperature is.

[0080] Accordingly, the target temperature gradient table may also include a field for the target goods type, and different target goods correspond to different target temperature gradients. It is understandable that the target temperature gradient for frozen meat is often different from the target temperature gradient for tropical fruits.

[0081] It is also understandable that, for a certain type of target cargo, in the target temperature gradient table, the larger the heat load data is, the lower the target temperature is.

[0082] In a specific embodiment, the target temperature gradient table may be a multidimensional table, which may include the following fields: Cargo types: Different cargo types correspond to different temperature regulation requirements; Heat load interval: can have multiple heat load intervals; Corresponding target temperature: Each heat load interval corresponds to a target temperature.

[0083] For example: Target temperature gradient table for frozen meat: Target temperature gradient table for tropical fruits: Therefore, in this specific embodiment, first, the controller extracts the cargo type information (e.g., "frozen meat") from the first information and searches for the corresponding cargo type in the target temperature gradient table. If the target cargo type is not clear, the controller may also use the default average temperature gradient table.

[0084] Then, the controller calculates the heat load according to the first target heat load data. , find the heat load range it is in. For example, if If the energy consumption is 15kWh, then for frozen meat, the heat load range is: 10-20.

[0085] Finally, the controller reads the corresponding target temperature in the matched heat load interval. For example, for frozen meat, the target temperature for the heat load interval of 10-20 is -18°C.

[0086] In a specific embodiment, if the cold storage needs to accommodate multiple types of goods at the same time (for example, frozen meat and tropical fruits), the controller can perform a weighted average calculation of the target temperatures of different types of goods to determine the comprehensive target temperature of the cold storage: In the formula, It can be expressed as the target heat load of the i-th category cargo, It can be expressed as the target temperature of the i-th type of goods, and n means there are n types of target goods in total.

[0087] Then, the controller generates and stores a control parameter based on the target temperature; wherein the control parameter is a control parameter for controlling the operation of the refrigeration equipment of the cold storage.

[0088] Specifically, first, the controller can calculate the adjustment temperature difference based on the target temperature and the temperature parameter obtained in step S14 (that is, the actual temperature of the cold storage). The adjustment temperature difference is the difference between the temperature parameter and the target temperature. In the warehousing scenario, in most cases, the target temperature should be lower than the value of the temperature parameter. In other words, the adjustment temperature difference is a positive value. It can be understood that when the target goods are about to enter the warehouse, the actual temperature of the current cold storage (the temperature parameter obtained in S14) should be lowered in advance.

[0089] Then, the controller generates control parameters of the refrigeration equipment based on the adjusted temperature difference; wherein the control parameters of the refrigeration equipment include the operating frequency of the compressor, the opening of the control valve or the rotation speed of the fan.

[0090] In a specific embodiment, the controller may generate control parameters of the refrigeration equipment based on the adjusted temperature difference in the following manner.

[0091] As for the compressor operating frequency, it is understandable that the compressor operating frequency directly determines the cooling capacity. Therefore, the larger the temperature difference, the higher the compressor frequency should be, so as to reduce the cold storage temperature faster. Therefore, the control logic of the compressor can be: In the formula, can be expressed as the compressor operating frequency generated by the controller, It can be expressed as the adjustment coefficient, It can be expressed as the minimum operating frequency of the compressor. It is to adjust the temperature difference.

[0092] As for the fan speed, it is understandable that the fan speed affects the circulation speed of the cold air in the cold storage; therefore, the larger the temperature difference, the higher the fan speed should be to distribute the cold air more evenly. Therefore, the control logic of the fan speed can be: In the formula, Indicates the fan speed. Indicates the minimum fan speed. It is to adjust the temperature difference. is the adjustment coefficient.

[0093] Similarly, the opening of the control valve determines the refrigerant flow rate, which directly affects the refrigeration capacity. Therefore, the larger the adjustment temperature difference, the larger the opening of the control valve should be to increase the refrigerant flow rate. The control logic of the opening of the control valve can be the same as the control logic of the compressor and the control logic of the fan speed.

[0094] After generating the control parameters, the controller may store the generated control parameters in a storage module of the controller in a structured form. The stored control parameters can be directly retrieved and a control signal generated and sent to the refrigeration device when the target time arrives.

[0095] Finally, when the target time is reached, the controller generates a corresponding control signal based on the control parameters, and sends the control signal to the refrigeration equipment to adjust the temperature parameters of the current cold storage; wherein the target time is the time that triggers the sending of a control instruction to the environmental conditioning device to perform an environmental conditioning operation.

[0096] In a specific implementation, in the outbound scenario, the target goods are removed from the cold storage, and the heat load of the cold storage is reduced. Since the heat load brought by the goods is reduced by outbound, the original refrigeration capacity of the cold storage may cause the cold storage temperature to be lower than the ideal target temperature. Therefore, the controller needs to dynamically increase the target temperature to reduce the operating load of the refrigeration equipment.

[0097] As in the inbound scenario, the target temperature in the outbound scenario can be determined by the target temperature gradient table. The target temperature gradient table can include the following fields: Cargo type: adjust the target temperature range according to the target cargo type; Heat load interval: divided into several intervals according to the heat load reduction; Corresponding target temperature: Each heat load reduction interval corresponds to a target temperature.

[0098] For example, in the outbound delivery scenario, the target temperature gradient table can be: Target temperature gradient table for frozen meat: Target temperature gradient table for tropical fruits: Therefore, in this specific embodiment, first, the controller can extract the type of goods from the first information, for example, the type of goods shipped is frozen meat. Then, the controller calculates Temperature difference, and then the quality information, The temperature difference and the preset specific heat capacity data are input into the preset heat load calculation model to obtain the first target heat load data (that is, the heat load reduction) in the outbound scenario.

[0099] Next, based on the first target heat load data in the outbound scenario, the heat load range is searched and the target temperature is determined. For example, if the heat load reduction is 15 kWh, the corresponding heat load range for frozen meat is 10-20. The corresponding target temperature is -15°C.

[0100] Next, after the target temperature is determined, the adjustment temperature difference can be calculated. The adjustment temperature difference is the difference between the temperature parameter and the target temperature. In the outbound scenario, the target temperature is usually higher than the current temperature. Therefore, it is necessary to increase the cold storage temperature by reducing the operating load of the refrigeration equipment.

[0101] Finally, the controller can convert the regulated temperature difference into the control parameters of the refrigeration equipment. For example: The control logic of the compressor can be: In the formula, can be expressed as the compressor operating frequency generated by the controller, It can be expressed as the adjustment coefficient, It can be expressed as the minimum operating frequency of the compressor. It is to adjust the temperature difference.

[0102] The control logic of the fan speed can be: In the formula, Indicates the fan speed. Indicates the minimum fan speed. It is to adjust the temperature difference. is the adjustment coefficient.

[0103] The same control logic can also be used to control the opening of the valve.

[0104] In this embodiment, the environment conditioning device may further include a humidity conditioning device. Specifically, the humidity conditioning device may include: Humidifier: atomize or evaporate water to increase the air humidity inside the cold storage; Dehumidifier: Reduces the air humidity inside the cold storage by condensing moisture in the air.

[0105] Therefore, in the warehousing scenario, the controller can control the preset humidity adjustment device according to the first target heat load data in the following manner to adjust the humidity parameters of the current cold storage.

[0106] It is understandable that the first target heat load data is calculated based on the mass, specific heat capacity, and the difference between the current temperature of the target goods and the current temperature of the cold storage. The first target heat load data not only reflects the target goods' demand for temperature regulation, but also indirectly reflects the possible impact of the goods on humidity. For example, goods with a large heat load (such as moist frozen meat) may bring additional humidity; goods with a small heat load (such as dry nuts) may absorb moisture in the cold storage.

[0107] Therefore, first, the controller can parse the category information from the first information, and then determine the target humidity range of the goods based on the category information. For example, from the humidity requirement table, the suitable humidity range for frozen meat is 90% to 95%, while the suitable humidity range for tropical fruits is 85% to 90%. If there are multiple target goods to be stored in the cold storage, the controller can calculate a comprehensive target humidity range based on the humidity requirements of each type of goods to take into account the storage requirements of different goods.

[0108] Then, the controller determines the humidity adjustment direction. If the current humidity of the cold storage is higher than the target humidity range and the first target heat load data is larger (indicating that wet goods are entering the warehouse), the controller determines that the humidity may rise further after entering the warehouse. In this case, the controller starts the dehumidifier in advance to reduce the humidity to the target range. If the current humidity of the cold storage is lower than the target humidity range and the first target heat load data is smaller (indicating that dry goods are entering the warehouse), the controller determines that the humidity may fall further after entering the warehouse. In this case, the controller starts the humidifier in advance to increase the humidity to within the target range.

[0109] This embodiment receives the first information when the target goods have not yet been put into storage or have not yet been shipped out, obtains the quality information and current temperature information of the target goods in advance, and calculates the first target heat load data in combination with the environmental parameters (such as temperature parameters) of the current cold storage, so that the environmental parameters (such as temperature parameters) of the cold storage are dynamically adjusted according to the calculation results before the goods are actually put into storage or shipped out. This method effectively solves the problem of inaccurate temperature control for cold storage, especially cold storage with frequent inflow and outflow in the related art. By adjusting the operating state of the environmental adjustment equipment in advance, such as optimizing the compressor frequency, fan speed and control valve opening of the refrigeration equipment, the temperature of the cold storage can be accurately reduced before the goods are put into storage, or the temperature of the cold storage can be appropriately increased before the goods are shipped out, thereby avoiding the problem of temperature adjustment lag. At the same time, this method can adapt to the changes in the types of goods and heat loads, dynamically adjust the cold storage environment, improve the temperature control accuracy and cold storage operation efficiency, reduce energy consumption, extend the fresh-keeping time of goods, and effectively improve the comprehensive use efficiency of the cold storage.

[0110] like Figure 2 As shown, in some embodiments, the method further comprises: Step S110: when the target goods are actually put into storage or actually taken out of storage, second information is determined; wherein the second information at least includes quality information and current temperature information of the target goods actually put into storage or actually taken out of storage.

[0111] Specifically, when the target goods are actually put into storage, the goods are transported to the cold storage. At this time, it is necessary to obtain the actual quality information and current temperature information of the batch of goods in order to dynamically adjust the cold storage environment parameters.

[0112] When the target goods pass through a preset quality detection device (such as an electronic scale or a floor scale), the quality detection device measures the actual quality of the goods in real time and transmits the quality data to the cold storage controller. The controller can obtain the actual current temperature information of the goods from the temperature detection device of the target goods (such as an infrared temperature sensor or a temperature sensor attached to the surface of the goods).

[0113] It is understandable that the temperature may vary depending on the mode of transportation (cold chain or non-cold chain transportation) and the external environment. For example, cold chain transportation goods may be kept at 0°C, and non-cold chain transportation goods may be close to the external environment temperature, such as 25°C. The controller combines the actual quality information transmitted by the quality detection device and the current temperature information of the temperature detection device to generate the second information.

[0114] When the target goods are actually shipped out of the warehouse, the goods are transported out of the cold storage. At this time, it is necessary to obtain the actual quality information and current temperature information of the batch of goods in order to adjust the cold storage environment parameters to ensure that the storage environment of the remaining goods is not affected. When the target goods pass through a preset quality detection device (such as an electronic scale or a pallet weighing system), the quality detection device measures the actual quality of the goods in real time and transmits the quality data to the controller. The controller obtains the current temperature information of the goods when they are shipped out through the target goods temperature detection device. Since the goods have been stored in the cold storage before being shipped out, the current temperature of the goods is usually the same as the ambient temperature in the cold storage. For example, if the temperature of the cold storage is -18°C, the current temperature of the goods is usually close to -18°C. The controller generates the second information by combining the actual quality information transmitted by the quality detection device and the current temperature information of the temperature detection device.

[0115] It is understandable that when the target goods have not yet been put into or out of the warehouse, the first target heat load data calculated by the controller based on the first information (such as predicted quality, expected temperature, etc.) may be based on assumptions and expectations. Moreover, when actually put into or out of the warehouse, the actual quality and actual temperature of the target goods may be inconsistent with the parameters predicted in the first information due to the transportation process, environmental changes or cargo loss. For example, in the warehousing scenario, the actual weight of the goods may be less than the predicted weight due to loss during transportation; cold chain transportation conditions may be limited, and the temperature of the goods may be higher than expected. In the outbound scenario, the actual quantity of outbound goods may be lower than expected due to order adjustments. Therefore, by determining the second information at the time of actual warehousing or outbound delivery, the actual parameters of the goods can be accurately reflected, avoiding the problem of inaccurate environmental adjustment due to prediction deviation.

[0116] Secondly, in the warehousing scenario, the entry of the target goods will increase the heat load of the cold storage. If the actual mass of the goods is large or the current temperature is high, the increased heat load will be significantly higher than expected, which may cause the temperature of the cold storage to rise too quickly, thereby affecting the preservation quality of other stored goods. In the outbound scenario, the outbound of the target goods will reduce the heat load of the cold storage. If the actual mass of the goods is small, the reduced heat load will be lower than expected, which may cause the temperature in the cold storage to drop too low, resulting in energy waste or freezing damage to the remaining goods. Therefore, after determining the second information, the operating status of the environmental conditioning equipment (such as refrigeration equipment, humidity conditioning equipment, etc.) can be corrected in real time to dynamically adjust the environmental parameters of the cold storage to the optimal state.

[0117] Step S112: Obtain the temperature parameters of the current cold storage.

[0118] The details may be as described in step S14, which will not be repeated here.

[0119] Step S114: Calculate second target heat load data based on the second information and temperature parameters.

[0120] The details may be as described in step S16, which will not be repeated here.

[0121] Step S116: According to the second target heat load data, the preset environment adjustment equipment is controlled to correct the current environment parameters of the cold storage.

[0122] The details may be as described in step S18, which will not be repeated here.

[0123] This implementation method collects real-time second information (including actual mass and current temperature) when the target goods are actually put into or taken out of the warehouse, combines it with the current temperature parameters of the cold storage, dynamically calculates the second target heat load data, and adjusts the preset environmental adjustment equipment accordingly, thereby effectively correcting the environmental parameters of the cold storage. This method can solve the problem of inaccurate temperature and humidity adjustment caused by the deviation between the actual parameters of the goods and the parameters obtained in advance, and ensure the precise control of the cold storage environment. By dynamically responding to the actual changes of the goods, this method significantly improves the operating efficiency and energy utilization rate of the cold storage, while ensuring the storage quality and safety of the goods, extending the shelf life of the goods, and reducing operating costs.

[0124] In some embodiments, the step of determining the second information when the target goods are actually put into storage or actually taken out of storage includes: Step S112: receiving quality information representing the target goods transmitted by a preset quality inspection device.

[0125] In this embodiment, the quality detection device can be a floor scale (ground weighing system), or an electronic scale, etc.

[0126] Step S114: Generate the second information based on the quality information.

[0127] This embodiment effectively solves the problem that there may be deviations between the predicted data and the actual data of the goods by receiving the actual quality information transmitted by the preset quality detection device when the target goods are actually put into or taken out of the warehouse, and generating the second information based on the information. By collecting the actual quality of the goods in real time, it can dynamically reflect the actual impact of the target goods on the heat load of the cold storage, thereby providing an accurate basis for the subsequent adjustment of environmental parameters. Compared with the method that relies solely on predicted data, this method significantly improves the accuracy of cold storage environment adjustment, avoids the problem of over- or under-adjustment caused by prediction deviation, further optimizes the operating efficiency of the cold storage, reduces energy consumption, and ensures the storage quality of the goods and the reliability of the cold storage operation.

[0128] like Figure 3 As shown, in some embodiments, the first information also includes type information of the target goods; Therefore, in the warehousing scenario, the step of calculating the first target heat load data based on the first information and the temperature parameter may include: Step S162: Based on the category information, determine the specific heat capacity data of the target cargo from a preset specific heat capacity data table; wherein the specific heat capacity data table is configured with a plurality of cargo categories and the corresponding specific heat capacity data.

[0129] Specifically, the preset specific heat capacity data table can be a structured database or table, which can be used to store specific heat capacity data corresponding to different types of goods. The basic fields of the data table include: Types of goods: different categories of goods, such as frozen meat, fruits, vegetables, dairy products, etc.; Specific heat capacity data: The temperature change capability of each cargo when absorbing or releasing unit heat per unit mass.

[0130] Step S164: Calculate the temperature difference based on the temperature parameter and the current temperature information of the target cargo.

[0131] Step S168: inputting the specific heat capacity data, the mass information and the temperature difference into a preset heat load calculation model to obtain the first target heat load data.

[0132] This embodiment introduces the type information of the target goods, and dynamically calculates the first target heat load data in combination with the temperature parameters and the current temperature information of the target goods, which can effectively improve the accuracy of the cold storage environment parameter adjustment. Specifically, by searching the specific heat capacity data corresponding to the type of goods in the preset specific heat capacity data table, and combining the real-time temperature difference and quality information, these data are input into the heat load calculation model to obtain a more accurate heat load result. Compared with the traditional average specific heat capacity or fixed heat load calculation method, this embodiment can be personalized according to the thermal characteristics of different goods (such as the difference between frozen meat and tropical fruits), ensuring that the dynamic adjustment of cold storage environment parameters (such as temperature and humidity) is more in line with actual needs. This method can not only significantly reduce the risk of over-refrigeration or under-refrigeration, but also optimize energy utilization efficiency, extend the shelf life of goods, reduce the operating cost of cold storage, and further improve the intelligence and operating efficiency of cold storage.

[0133] In some embodiments, the preset environmental conditioning equipment includes a refrigeration device; The step of controlling a preset environment adjustment device according to the first target heat load data to adjust the current environment parameters of the cold storage includes: Step S182: Determine a target temperature based on the first target heat load data.

[0134] For example, the first target heat load data may be input into a preset target temperature gradient table to obtain a target temperature; wherein the target temperature gradient table is configured with a plurality of heat load intervals and corresponding target temperatures.

[0135] It can be understood that, the larger the first target heat load data is, the lower the target temperature is.

[0136] Accordingly, the target temperature gradient table may also include a field for the target goods type, and different target goods correspond to different target temperature gradients. It is understandable that the target temperature gradient for frozen meat is often different from the target temperature gradient for tropical fruits.

[0137] It is also understandable that, for a certain type of target cargo, in the target temperature gradient table, the larger the heat load data is, the lower the target temperature is.

[0138] In this embodiment, the controller can directly calculate the target temperature according to the first target heat load data through a preset mathematical model or formula, without relying on a static temperature gradient table.

[0139] In this embodiment, the controller can dynamically adjust the target temperature according to the priority or importance of the target cargo type information. For example, if the target cargo type is temperature-sensitive cargo such as frozen meat, the target temperature will first meet the temperature requirements of frozen meat.

[0140] In this embodiment, the controller can predict the target temperature through a machine learning model based on historical data.

[0141] In this embodiment, the controller may determine the target temperature based on built-in expert system rules, according to preset conditions and logical relationships.

[0142] Step S184: Based on the target temperature, generate and store control parameters; wherein the control parameters are control parameters for controlling the operation of the refrigeration equipment of the cold storage.

[0143] Step S186: When the target time is reached, a corresponding control signal is generated based on the control parameters, and the control signal is sent to the refrigeration equipment to adjust the temperature parameters of the current cold storage; wherein the target time is the time that triggers the sending of a control instruction to the environmental conditioning device to perform an environmental conditioning operation.

[0144] This embodiment determines the target temperature based on the first target heat load data, and further generates and stores control parameters. When the target time is reached, a control signal is generated and sent to the refrigeration equipment to accurately adjust the temperature parameters of the cold storage. By rationally planning the target time and generating control parameters in advance before the goods are put into or taken out of the warehouse, the problem of delayed or premature start of temperature regulation is avoided, and dynamic response and precise control of environmental regulation are achieved. This method effectively solves the problem of inaccurate temperature control of the cold storage caused by the failure to respond to the heat load change in a timely manner in the traditional method. It can not only quickly adapt to the temperature requirements of the goods, but also optimize the operating efficiency of the refrigeration equipment and reduce energy waste. At the same time, by pre-storing the control parameters and automatically executing them at the target time, the automation and intelligence level of the cold storage operation is improved, and the storage quality of the goods is guaranteed.

[0145] In some embodiments, the step of generating a control parameter based on the target temperature includes: Step S1842: Calculate the adjustment temperature difference based on the temperature parameter and the target temperature.

[0146] Step S1844: Based on the adjusted temperature difference, control parameters of the refrigeration equipment are generated; wherein the control parameters of the refrigeration equipment include the operating frequency of the compressor, the opening of the control valve or the speed of the fan.

[0147] This embodiment can achieve precise control of the operating status of the refrigeration equipment by calculating the adjustment temperature difference based on the target temperature and the current temperature parameters, and further generating the control parameters of the refrigeration equipment (for example, the compressor operating frequency, the control valve opening and the fan speed). Compared with the traditional adjustment method that relies on fixed parameters, this embodiment dynamically adjusts the control parameters according to the adjustment temperature difference, making the operation of the refrigeration equipment more flexible and efficient. By adjusting the calculation of the temperature difference, it is ensured that the refrigeration equipment avoids over-cooling or under-cooling while meeting the target temperature requirements, effectively reducing energy waste and extending the service life of the equipment. In addition, by dynamically generating control parameters, a rapid response to different adjustment requirements is achieved, which significantly improves the accuracy and operating efficiency of the cold storage temperature adjustment, while ensuring the stability and quality of the cargo storage environment.

[0148] In some embodiments, the step of determining the target temperature based on the first target heat load data includes: Step S1824: inputting the first target heat load data into a preset target temperature gradient table to obtain a target temperature; wherein the target temperature gradient table is configured with a plurality of heat load intervals and corresponding target temperatures.

[0149] This embodiment inputs the first target heat load data into a preset target temperature gradient table to quickly determine the target temperature corresponding to the current heat load, thereby significantly improving the efficiency and accuracy of the target temperature calculation. The multiple heat load intervals and corresponding target temperatures configured in the target temperature gradient table can fully reflect the temperature requirements of the cold storage under different heat load conditions, thereby achieving dynamic adaptive adjustment of the cold storage environment. Compared with the fixed temperature method, this method can flexibly adjust the target temperature according to real-time heat load changes, effectively avoid over-refrigeration or under-refrigeration problems caused by heat load changes, and ensure that the cargo storage environment is always in the optimal state. In addition, the method has simple calculation logic and strong applicability. It can not only adapt to a variety of cargo scenarios, but also reduce the system calculation complexity and improve the intelligence level and overall efficiency of cold storage operation.

[0150] In some embodiments, the first information also includes the time when the target goods will be put into the warehouse or the time when they will be taken out of the warehouse; Between the step of generating and storing the control parameters based on the target temperature, and the step of generating corresponding control signals based on the control parameters when the target time is reached, and sending the control signals to the refrigeration equipment to adjust the temperature parameters of the current cold storage, the method further includes: Step S1851: Calculate the adjustment time based on the temperature parameters and the cold storage attribute parameters; wherein the cold storage attribute parameters include the cold storage volume, the types of goods stored in the cold storage, or the temperature regulation capacity of the cold storage; wherein the adjustment time refers to the time required to adjust the temperature parameters to the target temperature.

[0151] In this embodiment, the temperature parameter may be obtained in step S14.

[0152] In this embodiment, the temperature adjustment capacity of the cold storage may be the refrigeration power of the refrigeration equipment, the cooling capacity per unit time, and the ability to adjust the heat load per unit time.

[0153] In this embodiment, the temperature adjustment capability of the cold storage may also be the refrigerant circulation efficiency.

[0154] In this embodiment, the temperature adjustment capability of the cold storage may also be the operating frequency of the refrigeration equipment, etc.

[0155] In this embodiment, the cold storage attribute parameters can be preset or acquired and updated in real time. It can be understood that the volume of the cold storage is often unchanged, but the types of goods stored in the cold storage are often changing, and the temperature regulation capacity of the cold storage in most cases changes over time and continues to decrease (equipment aging).

[0156] Specifically, in a specific implementation scheme, one or more cold storage attribute parameters may be pre-configured, and during the operation of the cold storage, the one or more cold storage attribute parameters may be dynamically updated. Specifically, the one or more cold storage attribute parameters may be: The pre-configured cold storage attribute parameters can be parameters that have been determined or relatively unchanged during the cold storage design phase, such as cold storage volume and initial temperature adjustment capacity. These parameters can be manually input or configured into the cold storage controller during system initialization.

[0157] The volume of a cold storage refers to the effective internal storage space of the cold storage. The volume of the cold storage determines the basic time required for temperature adjustment. The larger the volume, the longer the time required for temperature adjustment is usually.

[0158] The temperature regulation capacity of the cold storage indicates the theoretical maximum capacity of the refrigeration equipment during the design phase, such as the maximum refrigeration power of the compressor or the cooling capacity per unit time, etc. For example, after the refrigeration equipment is installed, the technical parameters (maximum refrigeration power or cooling capacity per unit time) provided by the equipment manufacturer can be entered into the controller. It is understandable that the initial temperature regulation capacity is used as a basic reference value to provide an initial calculation of the temperature regulation time when the equipment is not aged.

[0159] It is understandable that the actual operating environment and equipment status of the cold storage will change over time and usage, so some cold storage attribute parameters can be acquired in real time and dynamically updated through sensor detection. For example, the types of goods stored in the cold storage, the cold storage attribute parameters can be synchronized in real time through the warehouse management system (WMS) (the cold storage controller can be connected to the WMS system to automatically obtain the information on the types of goods currently stored). You can also use RFID tags or barcode scanning devices to read the types of goods in real time and upload them to the controller.

[0160] Another example is the temperature regulation capability of a cold storage. This cold storage attribute parameter can reflect the temperature regulation capability of the cold storage in a unit of time, but this cold storage attribute parameter often changes due to equipment aging, operating status or maintenance status. The cold storage controller can monitor the operating status of the refrigeration equipment in real time, such as the frequency of the compressor, the speed of the fan, and the working efficiency of the condenser and evaporator. If the operating efficiency of the equipment decreases (for example, refrigerant leakage or equipment aging), the controller will record and update the temperature regulation capability in real time.

[0161] In a specific embodiment, the controller may calculate the adjustment time based on the temperature parameter and the cold storage property parameter in the following manner.

[0162] First, the controller may calculate the adjustment temperature difference based on the temperature parameter (which may be obtained in step S14 ) and the target temperature (determined in step S182 ).

[0163] The controller can then determine the total heat load of the cold store.

[0164] More specifically, the controller can calculate the total heat load of the current goods according to the types of goods stored in the cold storage and their proportions, and then calculate the space heat load according to the volume of the cold storage and the specific heat capacity of the air. Then, the total heat load of the cold storage can be calculated. The total heat load of the cold storage can be the sum of the heat load of the goods and the heat load of the cold storage space.

[0165] Finally, the controller calculates the adjustment time based on the cold storage temperature regulation capability.

[0166] More specifically, the controller can obtain the temperature adjustment capacity of the current cold storage by monitoring the operation status of the equipment. The temperature adjustment capacity can be the capacity to adjust the heat load per unit time. The controller can calculate the adjustment time according to the total heat load and the temperature adjustment capacity, that is, the total heat load of the cold storage is divided by the capacity to adjust the heat load per unit time, thereby obtaining the adjustment time.

[0167] Step S1852: Determine the target time based on the time when the target goods will enter the warehouse or leave the warehouse, and the adjustment time.

[0168] This embodiment calculates the adjustment time based on the current temperature parameters and cold storage attribute parameters (for example, the cold storage volume, the types of stored goods, and the temperature adjustment capacity), and dynamically determines the target sending time of the control signal in combination with the time when the target goods will enter or leave the warehouse, so as to achieve precise control of the refrigeration equipment and advance planning of temperature adjustment. Compared with the traditional passive adjustment method, this method fully considers the actual conditions of the cold storage and the dynamically changing goods situation, ensuring that the refrigeration equipment has adjusted the cold storage temperature to the ideal range when the target goods enter or leave the warehouse, thereby avoiding the lag of temperature adjustment. This method can not only reduce the energy consumption of the cold storage and reduce the risk of excessive or insufficient operation of the equipment, but also effectively ensure the storage quality of the goods, extend the shelf life of the goods, improve the intelligence and operation efficiency of the cold storage, and enhance the adaptability of the cold storage to frequent inbound and outbound scenarios.

[0169] According to an embodiment of the present invention, there is provided a controller, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor so that the at least one processor can perform the above method.

[0170] According to an embodiment of the present invention, there is provided an air conditioner, comprising the above-mentioned controller.

[0171] Specifically, in this embodiment, the air conditioner may include: A compressor, which increases the pressure and temperature of the refrigerant by compressing it; The condenser releases heat by cooling and liquefying the high-temperature and high-pressure refrigerant; an expansion valve, which expands the refrigerant by reducing pressure, lowering its temperature; The evaporator allows the refrigerant to absorb heat and cool the interior of the cold storage; Cold storage fans, which assist in cold air circulation and improve refrigeration efficiency; The controller first receives first information when the target goods have not yet been put into storage or have not yet been taken out of storage; the first information is information indicating that the target goods will be put into storage or will be taken out of storage; wherein the first information at least includes the quality information and the current temperature information of the target goods; then obtains the environmental parameters of the current cold storage; wherein the environmental parameters at least include the temperature parameters; then, based on the first information and the temperature parameters, calculates the first target heat load data; finally, according to the first target heat load data, controls at least one device among the above-mentioned compressor, condenser, expansion valve, evaporator or cold storage fan to adjust the current environmental parameters of the cold storage.

[0172] The controller may be a programmable logic controller (PLC); The controller may be a single chip microcomputer (MCU); The controller may be an embedded microprocessor; The controller may be an edge computing device.

[0173] Specifically, in the warehousing scenario, the controller can dynamically adjust the operating status of the cold storage's refrigeration system (that is, the compressor, condenser, expansion valve, evaporator and cold storage fan in the air conditioner) according to the first target heat load data to ensure that the cold storage can reach the ideal storage temperature when the goods are put into storage, thereby meeting the goods storage needs.

[0174] More specifically, if the first target heat load data is large (for example, the mass of the incoming goods is large or the current temperature is high), a stronger cooling capacity is required, and the controller can increase the operating frequency of the compressor. If the first target heat load data is small, the controller reduces the operating frequency of the compressor to reduce the cooling capacity and avoid excessive energy consumption.

[0175] More specifically, the condenser releases heat by cooling and liquefying the high-temperature and high-pressure refrigerant. The condensation efficiency directly affects the overall efficiency of the refrigeration cycle. Therefore, if the first target heat load data is large, the controller increases the speed of the condensation fan to accelerate heat release and improve condensation efficiency. If the first target heat load data is small, the controller reduces the speed of the condensation fan to reduce unnecessary energy consumption.

[0176] More specifically, the expansion valve expands the refrigerant by reducing the pressure, lowering its temperature, and providing the evaporator with low-temperature and low-pressure refrigerant. The opening of the expansion valve determines the flow rate of the refrigerant. Therefore, if the first target heat load data is large, the controller increases the opening of the expansion valve to provide more low-temperature refrigerant. If the first target heat load data is small, the controller reduces the opening of the expansion valve to maintain a reasonable refrigerant flow rate.

[0177] More specifically, the evaporator absorbs heat through the refrigerant, causing the temperature inside the cold storage to drop. The evaporator efficiency determines the transfer speed of heat inside the cold storage. Therefore, if the first target heat load data is large, the controller increases the flow rate of the refrigerant inside the evaporator. If the first target heat load data is small, the controller appropriately reduces the flow rate of the refrigerant to avoid overcooling.

[0178] More specifically, the cold storage fan ensures uniform temperature distribution inside the cold storage by promoting cold air circulation, while accelerating the cooling effect. Therefore, if the first target heat load data is large, the controller increases the fan speed to accelerate the cold air circulation and ensure that the temperature inside the cold storage drops evenly and quickly. If the first target heat load data is small, the controller reduces the fan speed to reduce energy consumption.

[0179] Specifically, in the outbound scenario, the controller can dynamically adjust the operating state of the cold storage refrigeration system (that is, the compressor, condenser, expansion valve, evaporator and cold storage fan in the air conditioner) according to the first target heat load data. Specifically, in the outbound scenario, due to the large amount of target goods outbound, the heat load inside the cold storage is reduced, resulting in the need to adjust the operating state of the refrigeration system to avoid the cold storage temperature being too low or energy waste.

[0180] More specifically, if the first target heat load data is large (that is, the heat load data is significantly reduced, for example, a large batch of goods is shipped out of the warehouse), the controller reduces the compressor operation frequency and reduces the refrigeration capacity. If the first target heat load data is small (that is, the heat load data is not significantly reduced, for example, a small batch of goods is shipped out of the warehouse), the controller controls the compressor to maintain low-frequency operation to maintain the temperature of the cold storage stable.

[0181] More specifically, if the first target heat load data is large (that is, the heat load data is significantly reduced, for example, a large batch of goods is shipped out of the warehouse), the controller reduces the speed of the condensing fan to reduce the condensation speed of the refrigerant. If the first target heat load data is small (that is, the heat load data is not significantly reduced, for example, a small batch of goods is shipped out of the warehouse), the controller controls the condensing fan to maintain low speed operation.

[0182] More specifically, if the first target heat load data is large (that is, the heat load data is significantly reduced, for example, a large batch of goods is shipped out of the warehouse), the controller reduces the expansion valve opening and reduces the refrigerant flow rate. If the first target heat load data is small (that is, the heat load data is not significantly reduced, for example, a small batch of goods is shipped out of the warehouse), the controller appropriately reduces the expansion valve opening and maintains low flow operation.

[0183] More specifically, if the first target heat load data is large (i.e., the heat load data is significantly reduced, for example, a large batch of goods is shipped out of the warehouse), the controller reduces the flow rate of the refrigerant in the evaporator and reduces the heat exchange rate. If the first target heat load data is small (i.e., the heat load data is not significantly reduced, for example, a small batch of goods is shipped out of the warehouse), the controller maintains low flow rate operation to reduce the generation of excess cooling capacity.

[0184] like Figure 4 As shown, according to an embodiment of the present invention, a cold storage is provided, which includes the above-mentioned air conditioner and environmental parameter detection device; wherein the controller in the air conditioner is communicatively connected with the environmental parameter detection device; the environmental parameter detection device is at least used to collect temperature parameters and send them to the controller.

[0185] Specifically, the environmental parameter detection device may include: Temperature and humidity sensor, which is used to measure the temperature and humidity parameters of the target goods in real time; Heat flow sensor, which is used to collect heat flow data on the surface of goods in real time, so as to accurately calculate the accurate heat load data.

[0186] Pressure sensor, which is used to calculate the actual cargo weight change data.

[0187] Specifically, the heat flow sensor can be directly installed on the surface of the cargo or the outer layer of the cargo stack, and collect heat flow data by detecting the heat exchange between the cargo and the surrounding environment in real time. The heat flow sensor can input the measured heat flux density data and the real-time cargo surface area into the controller for subsequent calculation. For example, the heat load can be equal to the heat flux density data multiplied by the surface area of ​​the cargo multiplied by the measurement time interval.

[0188] It is understandable that by collecting heat flow data in real time through the heat flow sensor and combining it with the ambient temperature of the cold storage and the surface area of ​​the goods, the controller can dynamically update the heat load data and use it to adjust the operating status of the refrigeration equipment in the cold storage. For example, if the heat load data increases (the heat absorption of the goods increases), the refrigeration equipment improves its operating efficiency; if the heat load data decreases (the heat dissipation of the goods decreases), the refrigeration equipment reduces its operating frequency and saves energy.

[0189] According to an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a computer, the computer executes the method described in any of the above embodiments.

[0190] According to an embodiment of the present invention, a computer program product including instructions is also provided. When the instructions are executed by a computer, the computer executes a method in any one of the above embodiments.

[0191] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0192] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.

[0193] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0194] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0195] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A cold storage control method, characterized in that: The method comprises: When the target goods have not yet been put into the warehouse or have not yet been taken out of the warehouse, receiving first information; the first information is information indicating that the target goods will be put into the warehouse or will be taken out of the warehouse; wherein the first information at least includes quality information and current temperature information of the target goods; Obtaining the current environmental parameters of the cold storage; wherein the environmental parameters at least include temperature parameters; Calculating first target heat load data based on the first information and temperature parameters; According to the first target heat load data, the preset environmental adjustment equipment is controlled to adjust the environmental parameters of the current cold storage.

2. The method according to claim 1, characterized in that The method further comprises: When the target goods are actually put into storage or actually taken out of storage, second information is determined; wherein the second information at least includes quality information and current temperature information of the target goods actually put into storage or actually taken out of storage; Get the current temperature parameters of the cold storage; calculating second target heat load data based on the second information and the temperature parameter; According to the second target heat load data, the preset environmental adjustment equipment is controlled to correct the current environmental parameters of the cold storage.

3. The method according to claim 2, characterized in that The step of determining the second information when the target goods are actually put into storage or actually taken out of storage includes: Receiving quality information indicating target goods transmitted by a preset quality detection device; Based on the quality information, the second information is generated.

4. The method according to claim 1, characterized in that: The first information also includes information on the type of target goods; The step of calculating first target heat load data based on the first information and the temperature parameter comprises: Based on the category information, determining the specific heat capacity data of the target goods from a preset specific heat capacity data table; wherein the specific heat capacity data table is configured with a plurality of goods categories and the specific heat capacity data corresponding thereto; Calculate the temperature difference based on the temperature parameter and the current temperature information of the target cargo; The specific heat capacity data, the mass information, and the temperature difference are input into a preset heat load calculation model to obtain the first target heat load data.

5. The method according to claim 1, characterized in that The preset environmental conditioning equipment includes a refrigeration device; The step of controlling a preset environment adjustment device according to the first target heat load data to adjust the current environment parameters of the cold storage includes: determining a target temperature based on the first target heat load data; Based on the target temperature, a control parameter is generated and stored; wherein the control parameter is a control parameter for controlling the operation of the refrigeration equipment of the cold storage; When the target time is reached, a corresponding control signal is generated based on the control parameters, and the control signal is sent to the refrigeration equipment to adjust the temperature parameters of the current cold storage; wherein the target time is the time that triggers the sending of a control instruction to the environmental conditioning device to perform an environmental conditioning operation.

6. The method according to claim 5, characterized in that The step of generating a control parameter based on the target temperature comprises: Based on the temperature parameter and the target temperature, calculating an adjustment temperature difference; Based on the adjusted temperature difference, control parameters of the refrigeration equipment are generated; wherein the control parameters of the refrigeration equipment include the operating frequency of the compressor, the opening of the control valve or the speed of the fan.

7. The method according to claim 5, characterized in that The step of determining the target temperature based on the first target heat load data comprises: The first target heat load data is input into a preset target temperature gradient table to obtain a target temperature; wherein the target temperature gradient table is configured with a plurality of heat load intervals and corresponding target temperatures.

8. The method according to claim 7, characterized in that The first information also includes the time when the target goods will be put into the warehouse or the time when they will be taken out of the warehouse; Between the step of generating and storing the control parameters based on the target temperature, and the step of generating corresponding control signals based on the control parameters when the target time is reached, and sending the control signals to the refrigeration equipment to adjust the temperature parameters of the current cold storage, the method further includes: Calculate the adjustment time based on the temperature parameter and the cold storage attribute parameter; wherein the cold storage attribute parameter includes the cold storage volume, the type of goods stored in the cold storage, or the temperature adjustment capacity of the cold storage; wherein the adjustment time is the time required to adjust the temperature parameter to the target temperature; The target time is determined based on the time when the target goods will enter the warehouse or leave the warehouse, and the adjustment time.

9. A controller, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 8.

10. An air conditioner, characterized in that: Comprising a controller as claimed in claim 9.

11. A cold storage, characterized in that: The cold storage comprises an air conditioner and an environmental parameter detection device as described in claim 10; wherein, a controller in the air conditioner is communicatively connected with the environmental parameter detection device; the environmental parameter detection device is at least used to collect temperature parameters and send them to the controller.

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