Introduction to R717 (Ammonia) Refrigerant Cold Storage

•  [Applicable Goods]

Mainly used for the storage of special items such as biological samples (stem cells, vaccines), fresh-keeping of high-end deep-sea fish such as tuna, and aerospace materials. It requires the storage temperature fluctuation ≤ ±1℃ to ensure the activity and quality stability of the items.

•  [Specifications of Polyurethane Insulation Panels]

Adopt a composite structure of 200mm thick polyurethane insulation panels and 50mm vacuum insulation panels (VIP), with a closed-cell rate ≥ 95% and a thermal conductivity ≤ 0.022W/(m·K). After -80℃ low-temperature shrinkage test, the deformation rate is ≤ 0.5%, which can effectively block the penetration of external heat, reduce the load of the refrigeration system, and have excellent compression resistance and moisture resistance, adapting to the long-term stable operation of ultra-low temperature environments. Compared with the traditional single polyurethane insulation scheme, it saves 30%~40% energy (conventional energy-saving range in the industry). Such storage bodies need to be equipped with R717 cascade refrigeration systems to ensure stable output of ultra-low temperature.

•  [Applicable Goods]

Used for individual quick freezing (IQF) of food, such as dumplings, shrimps, quick-frozen vegetables, ice cream freezing, etc. It needs to pass through the maximum ice crystal formation zone (-1℃~-5℃) within 30 minutes to maximize the taste and nutrition of food.

•  [Specifications of Polyurethane Insulation Panels]

Adopt 180mm thick polyurethane insulation panels with a closed-cell rate ≥ 92% and a thermal conductivity ≤ 0.023W/(m·K). The surface is made of color steel film-coated material, which is corrosion-resistant and easy to clean. It also has good impact resistance, adapting to the scenario of frequent door opening and rapid temperature fluctuation in the quick-freezing storage. It is equipped with a forced air cooling system to ensure quick-freezing efficiency and storage temperature stability.

•  [Applicable Goods]

The most widely used temperature zone, mainly storing meat, quick-frozen pasta, seafood, frozen prepared food, etc. Among them, the maximum shelf life of meat can reach 12-24 months, and that of seafood can reach 9-12 months. The energy consumption benchmark is ≤ 0.8 kWh/m³·day (conventional benchmark value for medium-sized cold storage in the industry, slightly higher for small cold storage and slightly lower for large cold storage).

•  [Specifications of Polyurethane Insulation Panels]

Adopt 150mm~200mm thick polyurethane insulation panels (the lower the storage temperature, the thicker the panel). The closed-cell rate is ≥ 90%, and the thermal conductivity is ≤ 0.024W/(m·K). The panels have passed the -30℃ low-temperature test without deformation or cracking, which can effectively maintain the stability of the storage temperature, reduce cold loss, and have good sound insulation and moisture resistance to avoid moisture and odor of goods.

•  Low-Temperature Refrigeration (-2℃~+4℃)

Suitable for chilled meat, pasteurized milk, medical reagents (2~8℃, need to be divided into independent storage bodies), etc. The humidity is controlled at 85%~95% RH to prevent goods from losing water and deteriorating; the storage of medical reagents needs to be additionally equipped with an uninterrupted temperature and humidity monitoring and backup system.

[Specifications of Polyurethane Insulation Panels]: Adopt 120mm~150mm thick polyurethane insulation panels with a closed-cell rate ≥ 90% and a thermal conductivity ≤ 0.024W/(m·K). It has excellent moisture resistance, which can effectively avoid condensation in the storage and ensure that the goods storage environment meets the standards.

•  High-Temperature Refrigeration (+5℃~+12℃)

Suitable for tropical fruits (such as bananas 11℃~13℃, mangoes 8℃~10℃), chocolate (10±1℃), red wine (12-14℃), etc. It is necessary to accurately control the temperature and humidity to avoid goods rotting, deteriorating or changing taste; the red wine storage needs additional vibration isolation and light-proof treatment, and the fruit storage needs to be equipped with a ventilation system to inhibit ethylene accumulation.

[Specifications of Polyurethane Insulation Panels]: Adopt 75mm~100mm thick polyurethane insulation panels with a closed-cell rate ≥ 88% and a thermal conductivity ≤ 0.025W/(m·K). It is light in weight and easy to install, and has good thermal insulation performance, which can accurately maintain the stability of the storage temperature and reduce energy consumption.

•  Controlled Atmosphere Storage (-1℃~+15℃, adjusted according to products)

Suitable for the storage of fruits and vegetables such as apples and blueberries. The shelf life of fruits and vegetables can be extended by adjusting the O₂ and CO₂ concentrations in the storage (such as apple O₂ concentration 1.5%~2%, CO₂ concentration 1%~3). It is equipped with 100mm~150mm thick polyurethane insulation panels to ensure the stability of storage temperature and gas concentration; the controlled atmosphere storage needs to be linked with the R717 refrigeration system to avoid the impact of gas concentration fluctuation on the refrigeration effect.

•  Constant Temperature and Humidity Storage (temperature accuracy ±0.5℃, humidity accuracy ±3% RH)

Suitable for film archives, Chinese medicinal materials, precision instruments, etc. It adopts 100mm~120mm thick polyurethane insulation panels, combined with a special temperature and humidity control system to ensure that the storage environment meets the standards accurately.

•  Corridor Buffer Room (freezing storage anteroom -5℃~0℃, refrigerated storage anteroom +8℃~+12℃)

Used to reduce cold loss when opening doors, saving 15%~30% energy. It adopts 100mm thick polyurethane insulation panels to adapt to the temperature fluctuation needs of the buffer room.

Built based on the Internet of Things and big data technology, it follows the hierarchical architecture of "perception-transmission-platform-application", realizes full-dimensional real-time control of the cold storage, adapts to multi-terminal operation, and meets the management needs of different roles:

•  Real-Time Monitoring

High-precision sensors are evenly deployed in the storage (one sensor installed every 50㎡~80㎡, with encrypted deployment in key areas) to collect real-time data such as temperature, humidity, R717 refrigerant concentration in the storage, and equipment operation status (compressor current, cold fan vibration, etc.). The temperature accuracy is ±0.1℃, the humidity is ±2%RH, and the data sampling frequency is once per minute. Through LoRa wireless transmission technology (adapted to the low-temperature and high-humidity environment of the cold storage), it ensures real-time and stable data transmission without monitoring blind areas; the ammonia concentration monitoring sets a reasonable alarm threshold to timely prevent safety risks.

•  Intelligent Early Warning

It supports setting personalized three-level early warning thresholds (warning, alarm, emergency threshold) according to the type of goods. When the storage temperature and humidity deviate from the set range, or refrigerant leakage and equipment abnormalities occur, the system immediately triggers alarms synchronously through short messages, APP pushes, emails and sound and light alarms, with a response time shortened to within 3 minutes, reminding staff to deal with it in time to avoid goods loss and safety hazards; it also supports block chain deposit, and the temperature data and operation logs are tamper-proof to meet various compliance needs; when an emergency warning is triggered by ammonia leakage, the system can link the explosion-proof ventilation equipment to automatically start and the refrigeration system to shut down urgently to ensure personnel safety.

•  Remote Control

It supports multi-terminal operation including Web terminal, APP terminal and WeChat applet. Staff can remotely view cold storage operation data, adjust storage temperature settings, and control the start and stop of refrigeration equipment, realizing "unattended and remote control". The number of personnel managing a single storage can be reduced from 3 to 1, greatly improving management efficiency; it also supports seamless docking with ERP and WMS systems to realize full cold chain data connection.

•  Data Review and Energy Efficiency Optimization

The system automatically stores historical operation data, generates temperature and humidity curves, equipment operation reports and energy consumption reports, which can be queried by day/week/month, facilitating staff to review management and optimize operation plans; at the same time, through the AI energy consumption model, it analyzes historical data and generates the optimal refrigeration strategy, realizing a comprehensive energy saving rate of 15%~20% (conventional energy saving range of AI regulation in the industry), avoiding energy waste caused by excessive refrigeration.

Aiming at the pain points of traditional cold storage such as energy waste, large storage temperature fluctuation and impact on goods quality caused by timed defrosting, it adopts AI frost layer prediction technology to realize precise defrosting, energy saving and high efficiency, which has been widely applied and verified in leading cold chain enterprises:

•  Precise Frost Layer Prediction

Through sensors deployed at key positions such as evaporators and air ducts, the system collects 18 types of core data in real time, including evaporator surface temperature, storage temperature and humidity, goods in and out volume, and outdoor environment parameters. Based on the deep learning algorithm and the frost layer growth dynamic prediction model trained with millions of operation data, it predicts the defrosting demand 2-4 hours in advance, completely replacing the extensive mode of traditional "timed defrosting", and avoiding the problems of invalid defrosting and untimely defrosting.

•  Dynamic On-Demand Defrosting

When the frost layer thickness reaches the critical value (2-3mm) that affects the heat exchange efficiency, the system automatically triggers the defrosting program, and immediately switches back to the refrigeration mode after defrosting is completed. It optimizes the defrosting time and energy output through algorithms, avoiding energy waste and temperature shock caused by excessive defrosting, narrowing the storage temperature fluctuation from ±1.2℃ to ±0.2℃ accurately, and extending the goods shelf life by 10%-15%.

•  Energy Saving and Equipment Protection

The defrosting link accounts for 20%-30% of the cold storage energy consumption. The AI intelligent defrosting system can reduce the number of defrosting times by 25%~30%, increase the defrosting efficiency from 70% to more than 95%, directly reduce invalid energy consumption, and reduce the energy consumption per unit goods storage by about 15%; at the same time, it reduces equipment wear, extends the service life of core equipment such as compressors and evaporators, reduces equipment maintenance costs by more than 20%, and avoids the problem of reduced refrigeration efficiency caused by incomplete traditional defrosting.