An intelligent cold-chain logistics temperature monitoring system for the logistics field

Abstract

The application relates to the field of temperature monitoring, in particular to an intelligent cold-chain logistics temperature monitoring system for the logistics field. A data monitoring module regularly monitors the temperature and transportation speed of a truck, calculates the temperature mean value and standard deviation, and then calculates the data value; after comparing the data value and determining that the data value exceeds a preset threshold value, a feedback sound is emitted; a positioning and tracking module monitors the longitude and latitude coordinates of the truck, calculates a plurality of distances, and then obtains the minimum distance according to a quick sorting method; the position information of the transfer station corresponding to the minimum distance and the transportation speed are displayed; a refrigeration power control module monitors the temperature outside the truck; a user can measure the laser round-trip time by emitting laser beams from different angles; the volume of the truck body, the previously measured area of the truck body, the heat conduction value, the heat capacity of the truck, the temperature change amount, the total cooling heat, the total refrigeration power, and the output power of the refrigeration equipment are calculated; and the output power of the refrigeration equipment is controlled to be the total refrigeration power based on the total refrigeration power.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of temperature monitoring, and particularly relates to an intelligent cold-chain logistics temperature monitoring system for the logistics field. BACKGROUND

[0002] Cold-chain logistics refers to maintaining a specific low-temperature environment during transportation, storage, distribution and other processes to ensure the quality and safety of perishable goods. With the rapid development of globalization trade and e-commerce, the importance of cold-chain logistics in modern supply chains is increasingly prominent. Especially after the epidemic, the transportation demand of biological products such as vaccines and medicines has surged, and higher requirements for the reliability and accuracy of cold chains have been put forward. However, there are many challenges in the actual operation of cold-chain logistics, especially in temperature control, transportation timeliness and energy efficiency. First, temperature stability is one of the most critical factors in cold-chain logistics. Temperature deviation can lead to a decrease in the quality of goods, and even deterioration. For example, when transporting vaccines, even a few degrees of temperature fluctuation can affect the effectiveness of the vaccine, causing huge economic losses and public health risks. At present, many cold-chain logistics systems mainly rely on traditional temperature control equipment and manual monitoring, but these systems often have problems such as slow response speed, low accuracy and information lag. The traditional temperature monitoring method only relies on periodic manual inspection and cannot timely detect temperature fluctuations or abnormal changes, which may miss the best intervention opportunity. Second, the transportation path and timeliness are also a big challenge to the management of cold-chain logistics. Cold-chain transportation not only requires proper temperature control, but also needs to ensure the efficiency and punctuality of the transportation process. The arrival time of goods and the optimization of transportation path directly affect the overall efficiency of the cold chain, especially for high-value goods that need to be transported within a strict time. Factors such as traffic and weather during transportation may affect the scheduled arrival time, but existing systems often lack real-time monitoring and prediction of transportation speed, path, traffic conditions, etc., resulting in unsynchronized scheduling and temperature control management, increasing the uncertainty and risk of cold-chain transportation. In addition, the problem of energy efficiency is also an important difficulty in cold-chain logistics. In order to maintain a low-temperature environment, cold-chain logistics usually requires a large number of refrigeration equipment, which will bring huge energy consumption and cost. Traditional refrigeration methods often do not optimize energy efficiency, and many systems will continue to run without distinction, resulting in energy waste. In the context of increasingly stringent environmental protection requirements and rising energy costs, how to achieve accurate refrigeration control and reduce energy consumption has become a problem that needs to be solved in the cold-chain logistics industry. Therefore, an intelligent cold-chain logistics temperature monitoring system for the logistics field is proposed. SUMMARY

[0003] The application aims to solve the technical problems of lack of precise temperature control management, dynamic path and time monitoring, and reasonable refrigeration power adjustment, and provides an intelligent cold-chain logistics temperature monitoring system for the logistics field.

[0004] The technical scheme adopted by the present application to solve its technical problems is: an intelligent cold chain logistics temperature monitoring system for the logistics field, comprising a data monitoring module, a positioning and tracking module, a refrigeration power control module,

[0005] The data monitoring module is arranged in the truck and is used for regularly monitoring the temperature of the truck.

[0006] The positioning and tracking module is arranged in the truck compartment and is used for positioning and tracking the position of the truck.

[0007] The refrigeration power control module is arranged outside the truck and is used for refrigerating the truck compartment.

[0008] Further, the data monitoring module comprises a monitoring unit, a feedback unit and an abnormality analysis unit,

[0009] The monitoring unit is arranged in the truck and is used for regularly monitoring the temperature of the truck, and then transmitting the truck temperatures at different time points regularly monitored to the abnormality analysis unit according to a preset number of time points.

[0010] The abnormality analysis unit is connected with the monitoring unit and the refrigeration power control module, and is used for, after receiving the truck temperature, calculating a temperature mean value according to the truck temperatures at different time points regularly monitored, calculating a temperature standard deviation based on the truck temperatures at different time points regularly monitored, calculating a data value based on the temperature standard deviation and the temperature mean value, and comparing whether the data value exceeds a preset threshold value. And is used for, after comparing that the data value exceeds the preset threshold value, generating an alarm prompt information and transmitting it to the feedback unit.

[0011] The feedback unit is connected with the abnormality analysis unit and is arranged in the truck cab, and is used for, after receiving the alarm prompt information, issuing a feedback sound.

[0012] Further, the formula for the abnormality analysis unit to calculate the temperature mean value according to the temperatures at different time points regularly monitored is:

[0013] Wherein, μ is the temperature mean value, the unit is ℃, N is the preset number of time points, x e is the truck temperature at the e-th time point, the unit is ℃.

[0014] Further, the formula for the abnormality analysis unit to calculate the temperature standard deviation based on the temperatures at different time points regularly monitored is:

[0015]

[0016] Wherein, σ is the standard deviation.

[0017] Further, the formula for the abnormality analysis unit to calculate the data value based on the standard deviation and the mean value is:

[0018]

[0019] wherein Z e is a data value.

[0020] Further, the positioning tracking module comprises a GPS positioning device, a cloud server, a display module,

[0021] The monitoring unit is configured to monitor the transport speed of the truck and transmit the transport speed to the cloud server.

[0022] The GPS positioning device is arranged in the truck cabin and is configured to monitor the latitude and longitude coordinates of the truck and transmit the latitude and longitude coordinates of the truck to the cloud server.

[0023] The cloud server is connected with the monitoring unit, the GPS positioning device and the refrigeration power control module, and is configured to deploy the position information of a plurality of cold chain transfer stations by a manager, and calculate a plurality of distances based on the position information of the plurality of cold chain transfer stations and the latitude and longitude coordinates of the truck after receiving the latitude and longitude coordinates of the truck, sort the plurality of distances to obtain a minimum distance according to a quick sorting method, and transmit the position information of the transfer station corresponding to the minimum distance to the display module. The cloud server is further configured to calculate an arrival time based on the minimum distance and the transport speed after receiving the transport speed, and transmit the arrival time to the display module.

[0024] The display module is connected with the cloud server and is configured to display the position information of the transfer station corresponding to the minimum distance and the arrival time after receiving the position information of the transfer station corresponding to the minimum distance and the arrival time.

[0025] Further, the formula for calculating the plurality of distances based on the position information of the plurality of cold chain transfer stations and the latitude and longitude coordinates of the truck is:

[0026]

[0027] wherein d i is the ith distance, the unit is m, r is the radius of the earth, the unit is km, is the longitude coordinate of the truck, the unit is degree, is the longitude coordinate of the ith cold chain transfer station position information, the unit is degree, Δλ is the difference between the latitude coordinate of the truck and the latitude of the ith cold chain transfer station position information, the unit is degree, is the difference between the longitude coordinate of the truck and the longitude of the ith cold chain transfer station position information, the unit is degree,

[0028] The formula for calculating the arrival time based on the minimum distance and the transport speed is:

[0029]

[0030] Wherein, t remaining is the arrival time, unit h, d min is the minimum distance, unit m, v is the transport speed, unit m / s.

[0031] Further, the refrigeration power control module includes an external temperature sensor, a calculation unit, a control unit,

[0032] The abnormality analysis unit is used to transmit the temperature mean to the calculation unit after calculating.

[0033] The cloud server transmits the arrival time to the calculation unit after calculating the arrival time based on the minimum distance and the transport speed.

[0034] The external temperature sensor is arranged outside the truck for monitoring the temperature outside the truck and transmitting it to the calculation unit.

[0035] The calculation unit is connected with the external temperature sensor, the cloud server, and the abnormality analysis unit, and is used to calculate the heat conduction value based on the pre-measured carriage area, the preset carriage heat conduction coefficient, the temperature outside the truck, and the temperature mean after receiving the arrival time, the temperature outside the truck, the carriage volume, the pre-measured carriage area, and the temperature mean, calculate the truck heat capacity based on the carriage volume, the preset air ratio truck heat capacity, and the preset air density, calculate the temperature change based on the temperature outside the truck and the temperature mean, calculate the total cooling heat based on the temperature change and the truck heat capacity, calculate the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time, and the preset refrigeration efficiency, and then transmit it to the control unit.

[0036] The control unit is connected with the calculation unit, and is used to control the refrigeration equipment output power to be the total refrigeration power based on the total refrigeration power after receiving the total refrigeration power.

[0037] Further, the formula for calculating the heat conduction value based on the pre-measured carriage area, the preset carriage heat conduction coefficient, the temperature outside the truck, and the temperature mean is: Q IN =A×U×(T OUT -μ),

[0038] Wherein, A is the pre-measured carriage area, unit m 2 , U is the preset carriage heat conduction coefficient, unit W / m 2 K, T OUT is the temperature outside the truck, unit ℃, Q IN is the heat conduction value, unit J,

[0039] The formula for calculating the truck heat capacity based on the carriage volume, the preset air ratio truck heat capacity, and the preset air density is:

[0040] C CAR= V x p AIR x c AIR

[0041] Wherein, V is the volume of the carriage, unit m 3 , p AIR is the preset air density, unit kg / m 3 , c AIR is the preset air specific heat of the truck, unit J / kgK, C CAR is the specific heat of the truck, unit J / K,

[0042] The formula for calculating the temperature change based on the temperature outside the truck and the average temperature is: Delta T = T OUT - mu

[0043] Wherein, Delta T is the temperature change, unit ℃.

[0044] Further, the calculation unit calculates the total cooling heat based on the temperature variable and the specific heat of the truck, and the formula is: Q COOL = C CAR x Delta T,

[0045] Wherein, Q COOL is the total cooling heat, unit J,

[0046] The formula for calculating the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time and the preset refrigeration efficiency is:

[0047]

[0048] Wherein, t remaining is the arrival time, unit h, P COOL is the total refrigeration power, unit W / h, and delta is the preset refrigeration efficiency.

[0049] The beneficial effects of the present application are:

[0050] 1. The data monitoring module monitors the temperature inside the truck in real time, processes the temperature data by using timing measurement calculation, ensures the accuracy and stability of temperature control. By calculating the average temperature and standard deviation of each time period, it can effectively identify temperature fluctuation abnormalities, and judge whether it exceeds the normal range through the set threshold. When the temperature exceeds the threshold, the module will trigger an audible feedback to alert the operator in time, so as to avoid the influence of temperature deviation on the quality of goods. In addition, the module also tracks and records the transportation speed of the truck, and transmits this information to the positioning tracking module, to ensure that temperature management and transportation progress are closely coordinated.

[0051] 2.The present application relates to temperature monitoring, in particular to an intelligent cold chain logistics temperature monitoring system for the logistics field. The data monitoring module monitors the temperature and transportation speed of the truck at regular intervals, calculates the mean and standard deviation of the temperature, and then calculates the data value. After comparing the data value with the preset threshold value, a feedback sound is emitted. The positioning and tracking module provides the manager with the location information of several cold chain transfer stations. The latitude and longitude coordinates of the truck are monitored, the distances are calculated, and the minimum distance is obtained according to the quicksort method. Then, the transfer station location information corresponding to the minimum distance and the transportation speed are displayed. The refrigeration power control module monitors the temperature outside the truck. The user measures the round-trip time of the laser by emitting a laser beam at different angles. The volume of the truck body and the pre-measured area of the truck body are obtained by the round-trip time. The heat conduction value, the heat capacity of the truck, the temperature change, the total cooling heat, and the total refrigeration power are calculated. Based on the total refrigeration power, the output power of the refrigeration equipment is controlled to be the total refrigeration power.

[0052] 3.The refrigeration power control module calculates the heat conduction and temperature change in real time by monitoring the external temperature and the physical characteristics of the truck body, and then determines the required refrigeration power. The accurate size of the truck body is obtained by laser measurement technology, and the heat capacity of the truck body and the heat that needs to be cooled are calculated to provide the refrigeration equipment with accurate power requirements. When the arrival time and external temperature information are transmitted to the module, the system can calculate the optimal refrigeration power output, thereby adjusting the working state of the refrigeration equipment in real time to ensure that the temperature inside the truck body is maintained within the preset range. This module not only improves energy utilization efficiency, but also dynamically responds to environmental changes to ensure the stability and safety of cold chain transportation. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 is a schematic diagram of the system module of the present application. DETAILED DESCRIPTION

[0054] The concept and technical effects of the present application will be described below in conjunction with examples to fully understand the purpose, features and effects of the present application. Please refer to Figure 1 .

[0055] An intelligent cold chain logistics temperature monitoring system for the logistics field includes a data monitoring module, a positioning and tracking module, and a refrigeration power control module,

[0056] The data monitoring module is arranged in the truck and is used for monitoring the temperature of the truck at regular intervals.

[0057] The positioning and tracking module is arranged in the truck body and is used for positioning and tracking the position of the truck.

[0058] The refrigeration power control module is arranged outside the truck and is used for refrigerating the truck body.

[0059] In this embodiment, the data monitoring module includes a monitoring unit, a feedback unit, an anomaly analysis unit,

[0060] The monitoring unit is arranged in the truck and is used for monitoring the temperature of the truck at regular intervals, and then transmitting the truck temperatures at different time points monitored at regular intervals to the anomaly analysis unit according to a preset number of time points. The monitoring unit is a digital temperature sensor.

[0061] The anomaly analysis unit is connected with the monitoring unit and the refrigeration power control module, and is used for, after receiving the temperature of the truck, calculating a temperature mean value according to the truck temperatures at different time points monitored at regular intervals, calculating a temperature standard deviation based on the truck temperatures at different time points monitored at regular intervals, calculating a data value based on the temperature standard deviation and the temperature mean value, and comparing whether the data value exceeds a preset threshold value. And for, after comparing that the data value exceeds the preset threshold value, generating an alarm prompt information, transmitting it to the feedback unit, the anomaly analysis unit can adopt a microcontroller based on ARM architecture.

[0062] The feedback unit is connected with the anomaly analysis unit and is arranged in the cab of the truck, and is used for, after receiving the alarm prompt information, issuing a feedback sound, and the feedback unit is a loudspeaker. When receiving the alarm prompt information, the loudspeaker issues a feedback sound to remind the truck driver.

[0063] In this embodiment, the monitoring unit regularly collects temperature data inside the truck and transmits it to the anomaly analysis unit. Through segmented processing of temperature data, the accuracy of temperature change monitoring is effectively improved. In addition, the monitoring unit is also responsible for real-time tracking of the transportation speed of the truck, and transmits this information to the positioning tracking module to ensure that temperature monitoring is synchronized with transportation progress. The anomaly analysis unit can accurately analyze the internal temperature fluctuations of the truck by calculating the temperature mean value and standard deviation, and timely identify abnormalities. The data value calculated by the temperature standard deviation and mean value is compared with the preset threshold value. When the temperature fluctuation exceeds the threshold value, the system can immediately detect and identify abnormal conditions. After receiving the alarm prompt information from the anomaly analysis unit, the feedback unit can quickly issue a feedback sound to remind the driver or operator to pay attention to temperature changes and take appropriate handling measures. This alarm mechanism ensures the timely discovery and response to abnormal conditions, thereby reducing the impact of temperature control problems on the safety of goods.

[0064] In this embodiment, the formula for calculating the temperature mean value by the anomaly analysis unit according to the temperatures at different time points monitored at regular intervals is:

[0065]

[0066] Wherein, μ is the temperature mean value, unit is ℃, N is the preset number of time points, x e is the truck temperature at the e-th time point, unit is ℃.

[0067] In the embodiment, the formula for calculating the temperature standard deviation by the abnormality analysis unit based on the temperature of different time points of the timing monitoring is:

[0068]

[0069] wherein σ is the standard deviation.

[0070] In the embodiment, the formula for calculating the data value by the abnormality analysis unit based on the standard deviation and the mean is:

[0071]

[0072] wherein Z e is the data value.

[0073] For example, assuming that we have the temperature data of the truck at 5 time points of the timing monitoring, if N is 5, x1, x2, x3, x4, and x5 are 10℃, 12℃, 8℃, 11℃, and 9℃ respectively, μ is 10℃, σ is 1.41℃, and Z t is -1.42, an abnormality occurs.

[0074] In the embodiment, the positioning tracking module comprises a GPS positioning device, a cloud server, and a display module,

[0075] The monitoring unit is configured to monitor the transport speed of the truck and transmit the same to the cloud server.

[0076] The GPS positioning device is arranged in the truck cabin and is configured to monitor the latitude and longitude coordinates of the truck and transmit the same to the cloud server, and the GPS positioning device adopts a GPS locator.

[0077] The cloud server is connected with the monitoring unit, the GPS positioning device, and the refrigeration power control module, and is configured to deploy the position information of a plurality of cold chain transfer stations by the manager, and calculate a plurality of distances based on the position information of the plurality of cold chain transfer stations and the latitude and longitude coordinates of the truck after receiving the latitude and longitude coordinates of the truck, sort the plurality of distances according to the quick sorting method to obtain a minimum distance, and transmit the position information of the transfer station corresponding to the minimum distance to the display module. The cloud server is also configured to calculate the arrival time based on the minimum distance and the transport speed after receiving the transport speed, and transmit the same to the display module.

[0078] The display module is connected with the cloud server, and is configured to display the position information of the transfer station corresponding to the minimum distance and the arrival time after receiving the same. The display module adopts an OLED display screen.

[0079] In this embodiment, the GPS positioning device monitors the latitude and longitude coordinates of the truck in real time and transmits this information to the cloud server. This function ensures accurate tracking of the truck's location, allowing managers to know the dynamic position of the truck at any time. The cloud server not only receives the truck location data, but also provides managers with the location information of the cold chain transfer stations. Based on the distance calculation between the current position of the truck and the transfer station, the system determines the nearest transfer station by quicksort method, optimizing the selection of transfer stations and ensuring that the goods can reach the appropriate transfer station as soon as possible. After receiving the transport speed of the truck, the cloud server combines the shortest distance and speed data to calculate the expected time of arrival of the truck at the target transfer station in real time. This information is transmitted to the refrigeration power control module for corresponding temperature adjustment, and at the same time, it is transmitted to the display module for the manager to grasp the transportation progress. The display module receives the transfer station information corresponding to the shortest distance and the arrival time transmitted by the cloud server, and displays it intuitively to the manager, facilitating real-time monitoring of the truck's transportation and expected arrival time, ensuring the timeliness and coordination of the transportation process.

[0080] In this embodiment, the cloud server calculates the distance formula based on the location information of several cold chain transfer stations and the latitude and longitude coordinates of the truck:

[0081]

[0082] where d i is the ith distance, unit is m, r is the radius of the earth, unit is km, is the longitude coordinate of the truck, unit is degree, is the longitude coordinate of the ith cold chain transfer station location information, unit is degree, Δλ is the difference between the latitude coordinate of the truck and the latitude of the ith cold chain transfer station location information, unit is degree, is the difference between the longitude coordinate of the truck and the longitude of the ith cold chain transfer station location information, unit is degree,

[0083] The formula for calculating the arrival time based on the minimum distance and transport speed is:

[0084]

[0085] where t renaining is the arrival time, unit is h, d min is the minimum distance, unit is m, v is the transport speed, unit is m / s,

[0086] For example, the longitude coordinate of the truck is 30°, the longitude coordinate of the position information of the ith cold chain transfer station is 31°, the radius of the earth is 6371 km, the difference in longitude coordinate between the truck and the ith cold chain transfer station is-0.000155 rad, and the difference in latitude between the user position and the key path point is 0.000079 rad. The ith distance is 10000 m, assuming that the ith distance is the minimum distance, the transport speed is 2 m / s, and the arrival time is 1.4 h.

[0087] In the present embodiment, the refrigeration power control module comprises an external temperature sensor, a calculation unit, a control unit,

[0088] The abnormality analysis unit is configured to transmit the temperature mean to the calculation unit after calculating the temperature mean.

[0089] The cloud server is configured to transmit the arrival time to the calculation unit after calculating the arrival time based on the minimum distance and the transport speed.

[0090] The external temperature sensor is configured to monitor the temperature outside the truck and transmit the temperature outside the truck to the calculation unit.

[0091] The calculation unit is connected with the external temperature sensor, the cloud server, and the abnormality analysis unit, and is configured to receive the arrival time, the temperature outside the truck, the volume of the truck compartment, the pre-measured area of the truck compartment, and the temperature mean, calculate a heat conduction value based on the pre-measured area of the truck compartment, a pre-set truck heat conduction coefficient, the temperature outside the truck, and the temperature mean, calculate a truck heat capacity based on the volume of the truck compartment, a pre-set air ratio truck heat capacity, and a pre-set air density, calculate a temperature change based on the temperature outside the truck and the temperature mean, calculate a total cooling heat based on the temperature change and the truck heat capacity, calculate a total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time, and a pre-set refrigeration efficiency, and transmit the total refrigeration power to the control unit. The calculation unit can be an embedded computer.

[0092] The control unit is connected with the calculation unit, and is configured to control the output power of the refrigeration equipment to be the total refrigeration power based on the total refrigeration power after receiving the total refrigeration power. The control unit can be a PLC.

[0093] In this embodiment, the external temperature sensor monitors the external environment temperature of the truck and transmits the temperature data to the computing unit. This function provides real-time feedback of the external environment for the computing of the temperature control of the truck cabin, ensuring that the temperature control system can respond to external climate changes in a timely manner. The computing unit combines the physical parameters of the truck cabin, the external temperature, the temperature inside the truck, and the preset heat conduction coefficient to calculate the heat conduction value. At the same time, the truck heat capacity is calculated using the volume of the truck cabin, the air specific truck heat capacity, and the air density, ensuring accurate estimation of heat changes. The computing unit calculates the total cooling heat required based on the temperature change and the truck heat capacity of the truck cabin. This calculation helps to predict the temperature change inside the truck, thereby determining the required cooling power and avoiding the impact of excessive or insufficient cooling on the temperature control during transportation. Based on the heat conduction value, the total cooling heat, the arrival time, and the cooling efficiency, the computing unit can obtain the accurate total cooling power and transmit the result to the control unit. The control unit adjusts the output power of the cooling equipment according to this power, thereby achieving precise regulation of the temperature inside the truck cabin and ensuring temperature stability during transportation.

[0094] In this embodiment, the computing unit calculates the heat conduction value based on the pre-measured truck cabin area, the preset truck heat conduction coefficient, the temperature outside the truck, and the temperature average formula as follows: IN Q OUT = A x U x (T 2 - μ),

[0095] where A is the pre-measured truck cabin area, with a unit of m 2 K, T OUT is the temperature outside the truck, with a unit of °C, and Q IN is the heat conduction value, with a unit of J,

[0096] The formula for calculating the truck heat capacity based on the truck cabin volume, the preset air specific truck heat capacity, and the preset air density is as follows:

[0097] C CAR = V x p AIR x c AIR

[0098] where V is the truck cabin volume, with a unit of m 3 , p AIR is the preset air density, with a unit of kg / m 3 , c AIR is the preset air specific truck heat capacity, with a unit of J / kgK, and C CAR is the truck heat capacity, with a unit of J / K,

[0099] The formula for calculating the temperature change based on the temperature outside the truck and the temperature average is as follows: ΔT = T OUT - μ

[0100] wherein, ΔT is the temperature change, unit is ℃.

[0101] In the embodiment, the formula for calculating the total cooling heat based on the temperature variable and the truck heat capacity is Q COOL = C CAR × ΔT,

[0102] wherein, Q COOL is the total cooling heat, unit is J,

[0103] The formula for calculating the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time and the preset refrigeration efficiency is:

[0104]

[0105] wherein, t remaining is the arrival time, unit is h, P COOL is the total refrigeration power, unit is W / h, and δ is the preset refrigeration efficiency.

[0106] For example, assuming that the pre-measured truck compartment area is 10 m 2 , the preset truck compartment heat conduction coefficient is 5 W / m 2 K, the outside temperature is 30 ℃, the truck temperature is 20 ℃, the heat conduction value is 500 J, the preset air density is 1.2 kg / m 3 , the preset air specific truck heat capacity is 1000 J / kgK, the truck heat capacity is 6000 J / K, the temperature change rate is 10 ℃, the total cooling heat is 6000 J / K, the preset refrigeration efficiency is 0.8, and the total refrigeration power is 5800 W / h.

[0107] The above embodiments are only part of the embodiments of the present application, but not all the embodiments, and other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative labor are within the protection scope of the present application.

Claims

1. An intelligent cold chain logistics temperature monitoring system for the field of logistics, characterized by: Including data monitoring module, positioning tracking module, refrigeration power control module, The data monitoring module is arranged in the truck, and is used for monitoring the temperature of the truck at regular time intervals. The positioning tracking module is arranged in the truck cabin, and is used for positioning and tracking the position of the truck. The refrigeration power control module is arranged outside the truck, and is used for refrigerating the truck cabin. The data monitoring module comprises a monitoring unit, a feedback unit and an abnormality analysis unit, The monitoring unit is arranged in the truck, and is used for monitoring the temperature of the truck at regular time intervals, and then transmitting the truck temperatures at different time points monitored at regular time intervals to the abnormality analysis unit according to a preset number of time points. The abnormality analysis unit is connected with the monitoring unit and the refrigeration power control module, and is used for, after receiving the truck temperatures, calculating a temperature mean value according to the truck temperatures at different time points monitored at regular time intervals, calculating a temperature standard deviation based on the truck temperatures at different time points monitored at regular time intervals, calculating a data value based on the temperature standard deviation and the temperature mean value, and comparing whether the data value exceeds a preset threshold value. And for, after comparing that the data value exceeds the preset threshold value, generating an alarm prompt information and transmitting the alarm prompt information to the feedback unit; The feedback unit is connected with the abnormality analysis unit, and is arranged in the truck cab, and is used for, after receiving the alarm prompt information, issuing a feedback sound. The formula for calculating the temperature mean value by the abnormality analysis unit according to the temperature of different time points of timing monitoring is: , wherein, is the average temperature, in °C, is the number of preset time points, is the temperature of the truck at the e-th time point, in °C; The formula for calculating the temperature standard deviation based on the temperatures at different time points monitored at regular time intervals by the abnormality analysis unit is: ， wherein is the standard deviation; The formula for calculating the data value based on the standard deviation and the mean value by the abnormality analysis unit is: ， wherein is a data value; The positioning tracking module comprises a GPS positioning device, a cloud server and a display module, The monitoring unit is used for monitoring the transport speed of the truck, and then transmitting the transport speed to the cloud server; The GPS positioning device is arranged in the truck cabin, and is used for monitoring the latitude and longitude coordinates of the truck, and then transmitting the latitude and longitude coordinates of the truck to the cloud server; The cloud server is connected with the monitoring unit, the GPS positioning device and the refrigeration power control module, and is used for deploying a plurality of cold chain transfer station position information by a manager; and for, after receiving the latitude and longitude coordinates of the truck, calculating a plurality of distances based on the plurality of cold chain transfer station position information and the latitude and longitude coordinates of the truck, sorting the plurality of distances according to the quick sorting method to obtain a minimum distance, and then transmitting the transfer station position information corresponding to the minimum distance to the display module; and for, after receiving the transport speed, calculating an arrival time based on the minimum distance and the transport speed, and then transmitting the arrival time to the display module; The display module is connected with the cloud server, and is used for, after receiving the transfer station position information corresponding to the minimum distance and the arrival time, displaying the transfer station position information corresponding to the minimum distance and the arrival time; The formula for calculating the plurality of distances based on the plurality of cold chain transfer station position information and the latitude and longitude coordinates of the truck by the cloud server is: ， wherein is the i-th distance in m, r is the radius of the earth in km, in degrees, is and is the difference in latitude in degrees, in degrees, The formula for calculating the arrival time based on the minimum distance and the transport speed is: wherein is the time of arrival in h, is the minimum distance in m and v is the transport speed in m / s.

2. The intelligent cold chain logistics temperature monitoring system for logistics field according to claim 1, characterized in that: The refrigeration power control module comprises an external temperature sensor, a calculation unit and a control unit, The abnormality analysis unit is used for, after calculating the temperature mean value, transmitting the temperature mean value to the calculation unit; The cloud server transmits the arrival time to the computing unit after calculating the arrival time based on the minimum distance and the transport speed; The external temperature sensor is arranged outside the truck and is used for monitoring the temperature outside the truck and transmitting the temperature to the computing unit; The computing unit is connected with the external temperature sensor, the cloud server and the abnormality analysis unit, and is used for calculating the heat conduction value according to the pre-measured carriage area, the preset carriage heat conduction coefficient, the temperature outside the truck and the temperature mean value after receiving the arrival time, the temperature outside the truck, the carriage volume, the pre-measured carriage area and the temperature mean value, calculating the truck heat capacity based on the carriage volume, the preset air ratio truck heat capacity and the preset air density, calculating the temperature change based on the temperature outside the truck and the temperature mean value, calculating the total cooling heat based on the temperature change and the truck heat capacity, calculating the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time and the preset refrigeration efficiency, and transmitting the total refrigeration power to the control unit; The control unit is connected with the computing unit and is used for controlling the refrigeration device output power to be the total refrigeration power based on the total refrigeration power after receiving the total refrigeration power.

3. The intelligent cold chain logistics temperature monitoring system for logistics field according to claim 2, characterized in that: The calculation unit calculates the heat conduction value according to a formula of a previously measured carriage area, a preset carriage heat conduction coefficient, a temperature outside the truck, and a temperature mean value. ),​ wherein, is a pre-measured carriage area, in , is a pre-set carriage heat conduction coefficient, in W / m2·K is a temperature outside the truck, in ℃ is a heat conduction value, in J, The formula for calculating the truck heat capacity based on the carriage volume, the preset air ratio truck heat capacity and the preset air density is: wherein, is the volume of the vehicle cabin, in m3 , is the preset air density, in kg / m3 , is the preset air specific heat capacity of the truck, in J / kgK is the specific heat capacity of the truck, in J / K, The formula for calculating the temperature change amount based on the temperature outside the truck and the average temperature is: ; wherein, Temperature change, in °C.

4. The intelligent cold chain logistics temperature monitoring system for logistics field according to claim 3, characterized in that: The calculation unit calculates the total cooling heat based on the temperature variable and the formula for the heat capacity of the cargo compartment , wherein, Qcool is the total heat to be cooled, in J, The formula for calculating the total refrigeration power based on the heat conduction value, the total cooling heat, the arrival time, and the preset refrigeration efficiency is: , is the time to reach, in h, is the total refrigeration power, in W / h, is the preset refrigeration efficiency.

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