Constant Temperature Control Method and System Applied to Pharmaceutical Cold Chain Transportation Process

Abstract

The present invention relates to the field of constant temperature control, and particularly to a constant temperature control method and system applied to the process of pharmaceutical cold chain transportation. The method first obtains the temperature data of each temperature sensor in the carriage at each moment during the pharmaceutical cold chain transportation process, and obtains the temperature data outside the carriage at each moment. According to the change characteristics of the temperature data of the temperature sensors at each moment, a plurality of sample time periods are extracted, and then the temperature control time periods in each sample time period are extracted. The differences between the temperature data outside the carriage within the sample time period and the optimal temperature of the medicine, the differences between the temperature data of each temperature sensor at each moment within the temperature control time period and the optimal temperature of the medicine, and the length of the temperature control time period are analyzed to obtain the correction coefficient of each sample time period, and the PID controller is adjusted. The adjusted PID controller is used to control the temperature. The present invention can improve the effect of temperature control in the carriage during the pharmaceutical cold chain transportation process.

Description

Technical Field

[0001] The present invention relates to the field of constant temperature control, and particularly to a constant temperature control method and system applied to the pharmaceutical cold chain transportation process. Background Art

[0002] Pharmaceutical cold chain transportation is an important link to ensure that the quality of temperature-sensitive drugs is not affected during transportation. With the continuous growth of the demand for biopharmaceuticals, vaccines, and other temperature-sensitive drugs, the requirements for cold chain transportation are becoming increasingly strict. During the transportation of drugs, especially for drugs such as biological agents and vaccines that require strict temperature control, maintaining a constant temperature inside the carriage is the key to ensuring the safety and effectiveness of the drugs. How to maintain temperature stability in a complex transportation environment and avoid the risks brought by local temperature fluctuations has become a major challenge in cold chain transportation.

[0003] In related technologies, a PID control system is usually used to control the temperature inside the carriage during the pharmaceutical cold chain transportation process. However, due to inevitable temperature fluctuations during pharmaceutical cold chain transportation, especially during operations such as opening and closing the carriage door and loading and unloading drugs, there is often a relatively obvious temperature gradient inside the carriage. When the PID parameters are set too large, in order to adjust the temperature of the area near the carriage door that is more affected by the environment, the temperature of the internal area will be adjusted excessively, resulting in a serious temperature overshoot phenomenon. When the PID parameters are set too small, the temperature adjustment speed inside the carriage will be too slow, and the uneven temperature situation inside the carriage cannot be alleviated quickly, resulting in the inability of the existing method to effectively control the temperature inside the carriage during the pharmaceutical cold chain transportation process. Summary of the Invention

[0004] In order to solve the technical problem that the existing method cannot effectively control the temperature inside the carriage during the pharmaceutical cold chain transportation process, the purpose of the present invention is to provide a constant temperature control method and system applied to the pharmaceutical cold chain transportation process, and the specific technical solutions adopted are as follows:

[0005] The present invention proposes a constant temperature control method applied to the pharmaceutical cold chain transportation process, and the method includes:

[0006] Obtain the temperature data of each temperature sensor inside the carriage at each moment during the pharmaceutical cold chain transportation process, the distance between each temperature sensor and the carriage door, and simultaneously obtain the temperature data outside the carriage at each moment;

[0007] Take the temperature sensor closest to the carriage door as the reference sensor, and obtain the temperature change degree at each moment according to the correlation of the temperature data at each moment between each temperature sensor and the reference sensor, and the change of the temperature data of each temperature sensor at each moment; obtain a plurality of sample time periods according to the temperature change degree at each moment; take any one of the sample time periods as the target sample time period, and obtain the temperature control time period of the target sample time period according to the distribution of the temperature data of all temperature sensors at the same moment within the target sample time period;

[0008] Take the temperature control time period of the target sample time period as the target temperature control time period, and obtain the temperature control optimization degree of the target sample time period according to the difference between the overall level of the temperature data of the outside of the carriage at all moments within the target sample time period and the optimal temperature of the medicine, the difference between the temperature data of each temperature sensor at each moment within the target temperature control time period and the optimal temperature of the medicine, and the length of the target temperature control time period; obtain the correction coefficient of the target sample time period according to the difference in length between the target sample time period and the target temperature control time period, the difference between the overall level of the temperature data of the outside of the carriage at all moments within the target sample time period and the optimal temperature of the medicine, and the difference in the temperature control optimization degree between the target sample time period and other sample time periods except the target sample time period;

[0009] Based on the correction coefficient of each sample time period, adjust the PID controller, and use the adjusted PID controller to control the temperature.

[0010] Further, the obtaining the temperature change degree at each moment includes:

[0011] Take any one temperature sensor as the target temperature sensor, and obtain the first temperature sequence of the reference sensor with respect to the time delay variable, and the first temperature sequence is Obtain the second temperature sequence of the target temperature sensor with respect to the time delay variable, and the second temperature sequence is where a i represents the temperature data of the reference sensor at the i-th moment, and t end represents the serial number of the last moment; Δt represents the time delay variable, 0 ≤ Δt ≤ (d - d') × ω, and Δt is an integer, where d represents the distance between the target temperature sensor and the carriage door; d' represents the distance between the reference sensor and the carriage door; ω represents the preset maximum time delay;

[0012] Take the Pearson correlation coefficient between the first temperature sequence and the second temperature sequence as the data change correlation degree between the reference sensor and the target sensor with respect to the time delay variable, and take the time delay variable corresponding to the maximum value of the data change correlation degree as the temperature change lag duration of the target temperature sensor;

[0013] Take the absolute value of the difference in the temperature data of the target temperature sensor between each moment and the next adjacent moment as the temperature change amount of the target temperature sensor at each moment;

[0014] Based on the calculation formula of the temperature change degree, obtain the temperature change degree at each moment, and the calculation formula of the temperature change degree is:

[0015]

[0016] where A k represents the temperature change degree at the k-th moment; t end represents the serial number of the last moment; T max represents the maximum value of the temperature change lag time of all temperature sensors; T i represents the temperature change lag time of the i-th temperature sensor; represents the temperature change amount of the i-th temperature sensor at the (k + T i )-th moment; I represents the number of temperature sensors.

[0017] Further, the obtaining of multiple sample time periods includes:

[0018] Take any moment as the target moment, and take the nearest preset first number of moments to the target moment as the reference moments of the target moment. If the temperature change degree of the target moment is greater than the temperature change degrees of all reference moments, then take the target moment as the carriage door opening moment, traverse all moments, and extract all carriage door opening moments;

[0019] Extract multiple temperature normal moments from all moments, where the temperature data of all temperature sensors at the same temperature normal moment are within the normal temperature range. Take any carriage door opening moment as the target opening moment, and take the temperature normal moment that is after the target opening moment and closest to the target opening moment as the temperature recovery moment of the target opening moment;

[0020] Take the time period between the target opening moment and the temperature recovery moment of the target opening moment as a sample time period.

[0021] Further, the obtaining of the temperature control time period of the target sample time period includes:

[0022] Take the standard deviation of the temperature data of all temperature sensors at the same moment within the target sample time period as the temperature dispersion degree at each moment within the target sample time period;

[0023] Within the target sample time period, take the moment corresponding to the maximum value of the temperature dispersion degree as the carriage door closing moment of the target sample time period;

[0024] Take the time period between the closing time of the car door in the target sample time period and the last moment of the target sample time period as the temperature control time period of the target sample time period.

[0025] Furthermore, the obtaining of the temperature control preference degree of the target sample time period includes:

[0026] Take the average value of the temperature data at all moments outside the car in the target sample time period as the overall temperature value outside the car in the target sample time period, and take the difference between the overall temperature value outside the car in the target sample time period and the optimal temperature of the medicine as the temperature difference value in the target sample time period;

[0027] Based on the calculation formula of the overshoot degree, obtain the overshoot degree of the target sample time period. The calculation formula of the overshoot degree is:

[0028]

[0029] Among them, B represents the overshoot degree of the target sample time period; E i represents the overshoot factor of the i-th temperature sensor in the target sample time period; I represents the number of temperature sensors; μ represents the temperature difference value in the target sample time period; D represents the optimal temperature of the medicine; a (i,t) represents the temperature data of the i-th temperature sensor at the t-th moment in the target temperature control time period; S represents the target temperature control time period; ∈ represents the belonging symbol; max() represents the maximum value function;

[0030] After comprehensively considering the overshoot degree of the target sample time period and the length of the target temperature control time period and performing negative correlation normalization processing, obtain the temperature control preference degree of the target sample time period.

[0031] Furthermore, the obtaining of the correction coefficient of the target sample time period includes:

[0032] Take the difference between the length of each sample time period and the length of the temperature control time period of each sample time period as the opening duration of the car door in each sample time period;

[0033] According to the differences in the opening duration of the car door, the differences in the temperature difference values, and the differences in the temperature control preference degrees between the target sample time period and each other sample time period, obtain the relative reference value between each other sample time period and the target sample time period;

[0034] Take the other sample time periods corresponding to the preset second largest number of the relative reference values as the reference sample time periods of the target sample time period;

[0035] Obtain the correction coefficient of the target sample period based on the relative reference value between each reference sample period and the target sample period, the difference in the overshoot degree between each reference sample period and the target sample period, and the difference in the length of the temperature control period.

[0036] Further, the obtaining of the relative reference value between each other sample period and the target sample period includes:

[0037] Based on the calculation formula of the relative reference value, obtain the relative reference value between each other sample period and the target sample period, and the calculation formula of the relative reference value is:

[0038]

[0039] Wherein, represents the relative reference value between the j-th other sample period except the target sample period and the target sample period; φ j represents the temperature control preference degree of the j-th other sample period except the target sample period; φ represents the temperature control preference degree of the target sample period; F j represents the environmental difference degree between the j-th other sample period except the target sample period and the target sample period; L j represents the opening duration of the carriage door of the j-th other sample period except the target sample period; L represents the opening duration of the carriage door of the target sample period; μ j represents the temperature difference value of the j-th other sample period except the target sample period; μ represents the temperature difference value of the target sample period; norm() represents the normalization function; ε represents the preset adjustment parameter, and the value range is [0.001, 0.01].

[0040] Further, the obtaining of the correction coefficient of the target sample period includes:

[0041] Based on the calculation formula of the correction coefficient, obtain the correction coefficient of the target sample period, and the calculation formula of the correction coefficient is:

[0042]

[0043] Wherein, ψ represents the correction coefficient of the target sample period; represents the relative reference value between the n-th reference sample period and the target sample period; B n represents the overshoot degree of the n-th reference sample period; B represents the overshoot degree of the target sample period; H nrepresents the length of the temperature control period of the nth reference sample period; H represents the length of the temperature control period of the target sample period; N represents the number of reference sample periods of the target sample period.

[0044] Further, adjusting the PID controller based on the correction coefficient of each sample period and controlling the temperature using the adjusted PID controller includes:

[0045] Taking the last sample period as the current sample period and taking the other sample periods except the current sample period as historical sample periods;

[0046] Based on the calculation method of the environmental difference degree between the jth other sample period except the target sample period and the target sample period, calculating the environmental difference parameter between the current sample period and each historical sample period;

[0047] Taking the correction coefficient of the historical sample period corresponding to the minimum value of the environmental difference parameter as the critical gain adjustment coefficient of the PID controller;

[0048] Obtaining the critical gain and critical period of the PID control system, and taking the product value of the critical gain adjustment coefficient and the critical gain as the adjusted critical gain;

[0049] Inputting the adjusted critical gain and critical period into the Ziegler-Nichols algorithm to obtain the adjusted proportional coefficient, adjusted integral coefficient, and adjusted derivative coefficient;

[0050] Controlling the temperature in the carriage by using a PID controller with the adjusted proportional coefficient, adjusted integral coefficient, and adjusted derivative coefficient.

[0051] The present invention also provides a constant temperature control system applied to the pharmaceutical cold chain transportation process. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of any one of the constant temperature control methods applied to the pharmaceutical cold chain transportation process are implemented.

[0052] The present invention has the following beneficial effects:

[0053] By collecting temperature data at multiple positions inside the constant-temperature carriage, combining with the temperature change data during multiple historical carriage door opening processes, performing segmented analysis and optimization adjustment, dynamically improving the PID control parameters, analyzing the time length for the temperature to return to the normal level after the carriage is closed, the overshoot degree during the temperature control process, and the environmental impact differences, a critical gain correction mechanism based on historical sample similarity is constructed to achieve the adaptive optimization of PID parameters. The present invention can minimize the overshoot phenomenon during the temperature control process to the greatest extent while significantly improving the temperature control speed, thereby reducing the interference of the external environment of the carriage on the temperature of the medicine, improving the temperature control accuracy and stability during the pharmaceutical cold chain transportation process, and thus achieving more effective constant-temperature control. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0055] Figure 1 It is a flowchart of a constant-temperature control method applied to the pharmaceutical cold chain transportation process provided by an embodiment of the present invention;

[0056] Figure 2 It is a schematic diagram of the internal device of a constant-temperature carriage provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following, in combination with the drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of a constant-temperature control method and system applied to the pharmaceutical cold chain transportation process according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0058] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0059] The following specifically describes the specific solutions of a constant-temperature control method and system applied to the pharmaceutical cold chain transportation process provided by the present invention in conjunction with the drawings.

[0060] Please refer to Figure 1, which shows a flowchart of a constant temperature control method applied to the pharmaceutical cold chain transportation process provided by an embodiment of the present invention. The method includes:

[0061] Step S1: Obtain the temperature data of each temperature sensor in the carriage at each moment during the pharmaceutical cold chain transportation process, the distance between each temperature sensor and the carriage door, and simultaneously obtain the temperature data outside the carriage at each moment.

[0062] The internal devices of the constant temperature carriage during the pharmaceutical cold chain transportation process are as follows:

[0063] (1) Temperature sensor:

[0064] Model: PT100 RTD sensor, which has high precision and is suitable for the cold chain transportation environment;

[0065] Maximum temperature measurement range: -50°C to +150°C;

[0066] Accuracy: ±0.1°C, suitable for cold chain transportation that requires high-precision control;

[0067] The temperature sensors should be installed at multiple positions inside the carriage, including near the door, the center of the carriage, and the drug storage area.

[0068] (2) Compressor:

[0069] Model: Secop automotive compressor, suitable for refrigeration and cold chain transportation applications;

[0070] Compressor power: The power is 35W to 80W, suitable for cold chain transportation of small and medium-sized vehicles;

[0071] Installation location: The compressor should be installed outside the carriage, usually at the rear of the vehicle or in a dedicated compressor compartment, to ensure good ventilation and heat dissipation.

[0072] (3) Heater:

[0073] An electric film heater is adopted;

[0074] Power: 100W to 500W, adjusted according to the size of the carriage;

[0075] Installation location: The heater should be installed in the area with lower temperature in the carriage, such as near the door or the edge of the carriage, to compensate for the heat loss caused by the opening and closing of the door.

[0076] (4) Fan / air circulation system:

[0077] An ssDC fan is installed inside the carriage;

[0078] The fan power range is 5W to 20W, ensuring the air circulates inside the carriage and avoiding too large a temperature gradient;

[0079] Installation location: The fan is installed in an area of the carriage that is relatively far from the temperature control source to ensure unobstructed air circulation.

[0080] Please refer to Figure 2 , which shows a schematic diagram of an internal device for a constant-temperature carriage provided by an embodiment of the present invention.

[0081] In the embodiment of the present invention, temperature data at each moment during the pharmaceutical cold chain transportation process is first collected by various temperature sensors installed inside the carriage, and at the same time, the distance between each temperature sensor inside the carriage and the carriage door is recorded. Here, the distance between the temperature sensor and the carriage door can be considered as the distance between the temperature sensor and the center point of the carriage door.

[0082] At the same time, in the embodiment of the present invention, temperature sensors also need to be installed outside the carriage, and the temperature sensors outside the carriage are used to collect temperature data at each moment outside the carriage.

[0083] It should be noted that the temperature sensors mentioned in the subsequent steps of the embodiment of the present invention all refer to the temperature sensors inside the carriage.

[0084] Step S2: Use the temperature sensor closest to the carriage door as the reference sensor. According to the correlation of the temperature data at each moment between each temperature sensor and the reference sensor, and the change in the temperature data of each temperature sensor at each moment, obtain the degree of temperature change at each moment; according to the degree of temperature change at each moment, obtain multiple sample time periods; use any one of the sample time periods as the target sample time period, and according to the distribution of the temperature data of all temperature sensors at the same moment within the target sample time period, obtain the temperature control time period of the target sample time period.

[0085] During the pharmaceutical cold chain transportation process, the carriage door may be opened and closed multiple times, and the temperature data collected by multiple temperature sensors is continuous and uninterrupted. Therefore, when the carriage door of the constant temperature carriage is opened and closed, the temperature data collected by multiple temperature sensors will gradually show a temperature gradient. In order to analyze the time required for the temperature in different areas to reach normal, it is first necessary to segment the pharmaceutical cold chain transportation process in terms of time based on the temperature data of each temperature sensor. When the carriage door is opened during the pharmaceutical cold chain transportation process, the temperature data of the temperature sensor closest to the carriage door changes first and is more obvious. As the temperature spreads, the temperature data collected by multiple temperature sensors inside the carriage will also change. That is to say, when the temperature data of the temperature sensor far from the carriage door changes, there will be a certain time delay compared to the temperature sensor close to the carriage door. Therefore, in the embodiment of the present invention, the temperature sensor closest to the carriage door is first used as the reference sensor, and then based on the correlation of the temperature data at each moment between each temperature sensor and the reference sensor, the time delay when each temperature sensor has a temperature change compared to when the reference sensor has a temperature change is analyzed, and combined with the change characteristics of the temperature data collected by each temperature sensor, the degree of temperature change at each moment is obtained. Subsequently, based on the degree of temperature change, the opening moment of the carriage door during the pharmaceutical cold chain transportation process can be accurately analyzed.

[0086] Preferably, in an embodiment of the present invention, the method for obtaining the degree of temperature change at each moment specifically includes:

[0087] First, any one temperature sensor is used as the target temperature sensor, and a first temperature sequence of the reference sensor with respect to the time delay variable is obtained. The first temperature sequence is A second temperature sequence of the target temperature sensor with respect to the time delay variable is obtained. The second temperature sequence is where a i represents the temperature data of the reference sensor at the i-th moment, t end represents the serial number of the last moment; Δt represents the time delay variable, 0 ≤ Δt ≤ (d - d') × ω, and Δt is an integer, where d represents the distance between the target temperature sensor and the carriage door; d' represents the distance between the reference sensor and the carriage door; ω represents the preset maximum time delay. In an embodiment of the present invention, ω is set to 20 seconds, and the specific value of ω can also be set by the implementer according to the specific implementation scenario and is not limited herein.

[0088] The Pearson correlation coefficient between the first temperature sequence and the second temperature sequence is used as the degree of data change correlation between the reference sensor and the target sensor with respect to the time delay variable. The greater the degree of data change correlation at a specific time delay variable, the more likely it is that this specific time delay variable is the duration when the temperature data change of the target temperature sensor lags behind that of the reference sensor. Therefore, the time delay variable corresponding to the maximum value of the data change correlation can be used as the temperature change lag duration of the target temperature sensor.

[0089] As an example, in an embodiment of the present invention, the expression for the temperature change lag duration of the target temperature sensor can be specifically, for example:

[0090] T = argmax[ρ(A′(Δt), B′(Δt))]

[0091] Wherein, T represents the temperature change lag duration of the target temperature sensor; Δt represents the time delay variable; A′(Δt) represents the first temperature sequence of the reference sensor with respect to the time delay variable; B′(Δt) represents the second temperature sequence of the target temperature sensor with respect to the time delay variable; ρ(A′(Δt), B′(Δt)) represents the degree of data change correlation between the reference sensor and the target sensor with respect to the time delay variable; argmax[] represents the function of taking the independent variable corresponding to the maximum function value.

[0092] By the same method as above, the temperature change lag duration of each temperature sensor can be obtained. It should be noted that when the reference sensor is selected as the target temperature sensor, the temperature change lag duration of the target temperature sensor is directly set to the value 0 at this time.

[0093] Then, the absolute value of the difference between the temperature data of the target temperature sensor between each moment and the next adjacent moment is used as the temperature change amount of the target temperature sensor at each moment. It should be noted that there is no next adjacent moment for the last moment of the target temperature sensor. At this time, the average value of the temperature change amounts of the target temperature sensor at all moments before the last moment can be used as the temperature change amount of the target temperature sensor at the last moment. At the same time, by the same method as above, the temperature change amount of each temperature sensor at each moment can be obtained.

[0094] Finally, based on the calculation formula of the temperature change degree, the temperature change degree at each moment is obtained. The calculation formula of the temperature change degree is:

[0095]

[0096] Wherein, A k represents the temperature change degree at the kth moment; t end represents the serial number of the last moment; Tmax Represents the maximum value of the temperature change lag duration of all temperature sensors; T i Represents the temperature change lag duration of the i-th temperature sensor; Represents the temperature change amount of the i-th temperature sensor at the (k + T i -th moment; I represents the number of temperature sensors.

[0097] Among them, in the process of calculating the temperature change degree A k at the k-th moment, the temperature change lag duration of each temperature sensor is added to eliminate the influence of the time lag caused by temperature propagation, facilitating the subsequent extraction of the opening moment of the carriage door. It is divided into two cases: k ≤ t end - T max and k > t end - T max These two cases are to ensure that the duration range is not exceeded during the calculation process.

[0098] When the carriage door is opened, after each temperature sensor has experienced the corresponding temperature change lag duration, its temperature data changes most violently. Therefore, according to the temperature change degree at each moment, the opening moment of the carriage door can be identified, and multiple sample time periods can be obtained. A certain sample time period can be considered as the time period from a certain carriage door opening, to the carriage door closing, and then to the temperature control system completing the internal temperature control of the carriage for this time. Subsequently, in combination with the temperature data of the temperature sensors in each sample time period, the parameters of the PID control system can be accurately obtained, thereby effectively controlling the temperature inside the carriage.

[0099] Preferably, in an embodiment of the present invention, the method for obtaining multiple sample time periods specifically includes:

[0100] Taking any moment as the target moment, and taking the nearest preset first number of moments to the target moment as the reference moments of the target moment. From the above analysis, it can be seen that if the temperature change degree at the target moment is larger locally, it means that the temperature data of each temperature sensor changes most violently after experiencing the corresponding temperature change lag duration starting from the target moment, and further indicates that the target moment is more likely to be the opening moment of the carriage door. Therefore, if the temperature change degree at the target moment is greater than the temperature change degrees of all reference moments, the target moment is taken as the carriage door opening moment, and all moments are traversed to extract all the carriage door opening moments. Among them, the preset first number is set to 10, and the specific value of the preset first number can also be set by the implementer according to the specific implementation scenario, which is not limited here.

[0101] Extract multiple normal temperature moments from all moments. Among them, the temperature data of all temperature sensors at the same normal temperature moment are within the normal temperature range. The normal temperature range during the pharmaceutical cold chain transportation is a known range, and different pharmaceuticals require different normal temperature ranges. During the pharmaceutical cold chain transportation, the carriage door will experience multiple opening and closing operations. Each time after opening and closing, it will trigger the temperature control system to control and adjust the temperature inside the carriage, so that the temperature returns to the normal temperature range. Then, take any carriage door opening moment as the target opening moment, and take the normal temperature moment that is after the target opening moment and closest to the target opening moment as the temperature recovery moment of the target opening moment. The temperature recovery moment of the target opening moment can be considered as the initial moment when the temperatures of all areas inside the carriage reach the normal temperature range after the carriage door is opened and closed this time and after being controlled by the temperature control system. By the same method as above, the temperature recovery moments of each carriage door opening moment can be obtained.

[0102] Furthermore, the time period between the target opening moment and the temperature recovery moment of the target opening moment can be used as a sample time period. By the same method as above, multiple sample time periods can be obtained.

[0103] When the carriage door is opened, the temperature control process will be affected by the outside temperature. After the carriage door is opened, the stability of the temperature inside it will gradually decrease. And when the door is closed, with the operation of the in-vehicle compressor or heater, the temperature inside it will gradually return to normal. Therefore, in the embodiment of the present invention, first analyze any sample time period, take any sample time period as the target sample time period, and then identify the closing moment of the carriage door within the target sample time period according to the distribution of the temperature data of all temperature sensors at the same moment within the target sample time period, and obtain the temperature control time period of the target sample time period. Subsequently, based on the length of the temperature control time period, the parameters of the PID control system can be adjusted more precisely, so as to effectively control the temperature inside the carriage.

[0104] Preferably, in an embodiment of the present invention, the method for obtaining the temperature control time period of the target sample time period specifically includes:

[0105] First, take the standard deviation of the temperature data of all temperature sensors at the same moment within the target sample time period as the temperature dispersion degree of each moment within the target sample time period.

[0106] After the carriage door is closed, as the temperature is controlled, the temperature inside the carriage will gradually tend to be stable. And when the carriage door is closed, at this time, the temperature control has not been carried out yet, and the consistency of the temperature data of each temperature sensor at this time is worse, and the dispersion degree is higher. Therefore, within the target sample time period, the moment corresponding to the maximum value of the temperature dispersion degree can be taken as the closing moment of the carriage door of the target sample time period.

[0107] Furthermore, the time period between the closing moment of the carriage door in the target sample time period and the last moment of the target sample time period is used as the temperature control time period of the target sample time period.

[0108] The temperature control time periods of each sample time period can be obtained by the same method as above.

[0109] Step S3: Use the temperature control time period of the target sample time period as the target temperature control time period. According to the difference between the overall level of the temperature data of all moments in the target sample time period outside the carriage and the optimal temperature of the medicine, the difference between the temperature data of each temperature sensor at each moment in the target temperature control time period and the optimal temperature of the medicine, and the length of the target temperature control time period, obtain the temperature control preference degree of the target sample time period; according to the difference in length between the target sample time period and the target temperature control time period, the difference between the overall level of the temperature data of all moments in the target sample time period outside the carriage and the optimal temperature of the medicine, and the difference in temperature control preference degree between the target sample time period and other sample time periods except the target sample time period, obtain the correction coefficient of the target sample time period.

[0110] There is a temperature control time period in each sample time period. Since the same PID parameters are used for temperature control, this method may cause a large number of samples to have a long control time or a large overshoot in some environments, ultimately affecting the stability of the medicine. When there is a temperature overshoot in a certain area, the temperature after the overshoot will show the opposite situation to that before the control. For example, when the initial constant temperature outside the carriage is greater than the optimal temperature of the medicine, due to the fixed PID parameters, the temperature in some areas may be adjusted too much and lower than the optimal temperature during the adjustment process. Therefore, in the embodiment of the present invention, first, the temperature control time period of the target sample time period is used as the target temperature control time period, and then, according to the difference between the overall level of the temperature data of all moments in the target sample time period outside the carriage and the optimal temperature of the medicine, the difference between the temperature data of each temperature sensor at each moment in the target temperature control time period and the optimal temperature of the medicine, analyze the overshoot situation of the temperature control process in the target sample time period, and combine the length of the target temperature control time period to obtain the temperature control preference degree of the target sample time period. Subsequently, the correction coefficient of the target sample time period can be accurately calculated and analyzed based on the temperature control preference degree, improving the final effect of the temperature control inside the carriage.

[0111] Preferably, in an embodiment of the present invention, the method for obtaining the temperature control preference degree of the target sample time period specifically includes:

[0112] First, take the average of the temperature data at all times within the target sample time period for the exterior of the carriage as the overall exterior temperature value of the target sample time period. Take the difference between the overall exterior temperature value of the target sample time period and the optimal temperature for the medicine as the temperature difference value for the target sample time period. The larger the temperature difference value, the greater the difference between the temperature outside the carriage and the optimal temperature for the medicine within the target sample time period. The temperature difference values for each sample time period can be obtained through the same method described above.

[0113] It should be noted that the optimal temperature for the medicine is a known value, which is related to the specific medicine in the pharmaceutical cold chain transportation. There are differences in the optimal temperatures for different medicines.

[0114] Based on the calculation formula for the overshoot degree, obtain the overshoot degree of the target sample time period. The calculation formula for the overshoot degree is:

[0115]

[0116] Among them, B represents the overshoot degree of the target sample time period; E i represents the overshoot factor of the i-th temperature sensor in the target sample time period; I represents the number of temperature sensors; μ represents the temperature difference value of the target sample time period, and in the actual scenario, μ≠0; D represents the optimal temperature for the medicine; a (i,t) represents the temperature data of the i-th temperature sensor at the t-th moment within the target temperature control time period; S represents the target temperature control time period; ∈ represents the belonging symbol; max() represents the maximum value function.

[0117] Among them, the overshoot factor E i The larger it is, the greater the overshoot phenomenon of the temperature in a certain area inside the carriage monitored by the temperature sensor within the target sample time period. Then, combining the overshoot factors E of all temperature sensors i , obtain the overshoot degree B of the temperature control within the target sample time period.

[0118] The overshoot degrees of each sample time period can be obtained through the same method described above.

[0119] Since the temperature control durations in different sample time periods are different, when the control duration is shorter, the impact on the medicine inside the carriage is smaller. Therefore, the overshoot degree of the target sample time period and the length of the target temperature control time period can be comprehensively considered and negatively correlated for normalization processing to obtain the temperature control preference degree of the target sample time period.

[0120] In the embodiments of the present invention, the combination of the two can be achieved by calculating the sum value or product value of the overshoot degree of the target sample time period and the length of the target temperature control time period, and no limitation is made here.

[0121] In an embodiment of the present invention, negative correlation normalization processing can be implemented in the form of a negative exponential function with the natural constant e as the base or a function of 1 - norm(), which is not limited herein. Here, norm() represents a normalization function. In an embodiment of the present invention, the normalization processing can specifically be, for example, min - max normalization processing. Moreover, the normalization in subsequent steps can all adopt min - max normalization processing. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of values, which will not be elaborated herein.

[0122] As an example, in an embodiment of the present invention, the expression of the temperature control preference degree of the target sample time period can specifically be, for example:

[0123] φ = 1 - norm(B×H)

[0124] where φ represents the temperature control preference degree of the target sample time period; B represents the overshoot degree of the target sample time period; H represents the length of the target temperature control time period; and norm() represents a normalization function.

[0125] It should be noted that the length of the target temperature control time period can be represented by the number of moments included in the target temperature control time period, or by calculating the difference between the end moment and the start moment of the target temperature control time period.

[0126] By the same method as above, the temperature control preference degree of each sample time period can be obtained.

[0127] Since the traditional PID parameter setting cannot meet the temperature control in the pharmaceutical cold chain transportation process, it is necessary to correct and adjust the PID controller parameters to achieve precise control of the temperature in the carriage. Considering that the external environmental influence situations such as the temperature outside the carriage and the opening duration of the carriage door are different in different sample time periods, there will be significant differences in the regulation process. Therefore, it is necessary to analyze the similarity of the influence of these external environments in different sample time periods, and then perform subsequent regulation. Therefore, the correction coefficient of the target sample time period can be obtained according to the difference in length between the target sample time period and the target temperature control time period, the difference between the overall level of the temperature data at all moments in the target sample time period outside the carriage and the optimal temperature of the medicine, and the difference in temperature control preference degree between the target sample time period and other sample time periods except the target sample time period. Subsequently, based on the correction coefficient, the parameters of the PID controller can be adjusted to achieve precise control of the temperature in the carriage.

[0128] Preferably, in an embodiment of the present invention, the method for obtaining the correction coefficient of the target sample time period specifically includes:

[0129] First, the difference between the length of each sample time period and the length of the temperature control time period of each sample time period is used as the opening duration of the carriage door for each sample time period. Similarly, the length of the sample time period can be represented by the number of moments included in the sample time period, or by calculating the difference between the end moment and the start moment of the sample time period.

[0130] Since the differences in the external environment between the target sample time period and other sample time periods are mainly manifested in the differences in the opening duration of the carriage door and the temperature difference value, the relative reference value between each other sample time period and the target sample time period can be obtained according to the differences in the opening duration of the carriage door, the temperature difference value, and the temperature control preference degree between the target sample time period and each other sample time period. Subsequently, based on the relative reference value, the reference sample time period of the target sample time period can be screened out, and the correction coefficient of the target sample time period can be further calculated.

[0131] Preferably, in an embodiment of the present invention, the method for obtaining the relative reference value between each other sample time period and the target sample time period specifically includes:

[0132] Based on the calculation formula of the relative reference value, the relative reference value between each other sample time period and the target sample time period is obtained. The calculation formula of the relative reference value is:

[0133]

[0134] Among them, represents the relative reference value between the j-th other sample time period except the target sample time period and the target sample time period; φ j represents the temperature control preference degree of the j-th other sample time period except the target sample time period; φ represents the temperature control preference degree of the target sample time period; F j represents the environmental difference degree between the j-th other sample time period except the target sample time period and the target sample time period; L j represents the opening duration of the carriage door of the j-th other sample time period except the target sample time period; L represents the opening duration of the carriage door of the target sample time period; μ j represents the temperature difference value of the j-th other sample time period except the target sample time period; μ represents the temperature difference value of the target sample time period; norm() represents the normalization function; ε represents a preset adjustment parameter used to prevent the denominator from being 0, and the value range of ε is [0.001, 0.01]. In an embodiment of the present invention, ε is set to 0.01. The specific value of ε can also be set by the implementer according to the specific implementation scenario and is not limited herein.

[0135] Then, use the other sample time periods corresponding to the preset second largest relative reference values as the reference sample time periods of the target sample time period. Here, the preset second quantity is set to 20, and the specific value of the preset second quantity can also be set by the implementer according to the specific implementation scenario and is not limited here.

[0136] Furthermore, based on the relative reference value between each reference sample time period and the target sample time period, the difference in overshoot degree between each reference sample time period and the target sample time period, and the difference in the length of the temperature control time period, obtain the correction coefficient of the target sample time period.

[0137] Preferably, in an embodiment of the present invention, the method for obtaining the correction coefficient of the target sample time period further includes:

[0138] Based on the calculation formula of the correction coefficient, obtain the correction coefficient of the target sample time period. The calculation formula of the correction coefficient is:

[0139]

[0140] where ψ represents the correction coefficient of the target sample time period; represents the relative reference value between the nth reference sample time period and the target sample time period; B n represents the overshoot degree of the nth reference sample time period; B represents the overshoot degree of the target sample time period, and in the actual scenario B≠0; H n represents the length of the temperature control time period of the nth reference sample time period; H represents the length of the temperature control time period of the target sample time period; N represents the number of reference sample time periods of the target sample time period.

[0141] where is used to reflect the reference value of the nth reference sample time period relative to the target sample time period and is used as a weight here. When B n is relatively large and H n is relatively small, is greater than the value 1, so as to increase the parameters that need to be adjusted subsequently. When B n is relatively small and H n is relatively large, is less than the value 1, so as to reduce the parameters that need to be adjusted subsequently.

[0142] The correction coefficient of each sample time period can be obtained by the same method as above.

[0143] Step S4: Based on the correction coefficient of each sample time period, adjust the PID controller, and use the adjusted PID controller to control the temperature.

[0144] Due to the fact that traditional PID parameter setting methods, such as the Ziegler-Nichols algorithm, cannot adapt to different environmental conditions, resulting in a poor control effect on the temperature inside the carriage. Therefore, the PID controller can be further adjusted based on the correction coefficient of each sample period, and the adjusted PID controller is used to control the temperature, thereby improving the control effect of the temperature inside the carriage during the pharmaceutical cold chain transportation process.

[0145] Preferably, in an embodiment of the present invention, the method for controlling the temperature specifically includes:

[0146] Take the last sample period as the current sample period, and take the other sample periods except the current sample period as historical sample periods.

[0147] Based on the calculation method of the environmental difference degree between the j-th other sample period except the target sample period and the target sample period, calculate the environmental difference parameters between the current sample period and each historical sample period.

[0148] As an example, in an embodiment of the present invention, the expression of the environmental difference parameter between the current sample period and each historical sample period can be specifically, for example:

[0149]

[0150] Among them, F′ m represents the environmental difference parameter between the m-th historical sample period and the current sample period; L′ m represents the opening duration of the carriage door in the m-th historical sample period; L′ represents the opening duration of the carriage door in the current sample period; μ′ m represents the temperature difference value in the m-th historical sample period; μ′ represents the temperature difference value in the current sample period.

[0151] Take the correction coefficient of the historical sample period corresponding to the minimum value of the environmental difference parameter as the critical gain adjustment coefficient of the PID controller;

[0152] Obtain the critical gain and critical period of the PID control system, and take the product value of the critical gain adjustment coefficient and the critical gain as the adjusted critical gain. Among them, the method for obtaining the critical gain and critical period of the PID control system is a well-known technical means for those skilled in the art and will not be elaborated here.

[0153] Input the adjusted critical gain and critical period into the Ziegler-Nichols algorithm to obtain the adjusted proportional coefficient, adjusted integral coefficient, and adjusted differential coefficient. Among them, the Ziegler-Nichols algorithm is a well-known technical means for those skilled in the art and will not be elaborated here.

[0154] Furthermore, by using a PID controller that adjusts the proportional coefficient, integral coefficient, and derivative coefficient, the temperature inside the carriage is controlled, so that the overshoot of the regulated temperature is not too large, while the temperature regulation speed is increased as much as possible, and the influence of the external environment of the carriage on the medicine is reduced.

[0155] An embodiment of the present invention provides a constant temperature control system applied to the process of pharmaceutical cold chain transportation. The system includes a memory, a processor, and a computer program, where the memory is used to store the corresponding computer program, the processor is used to run the corresponding computer program, and when the computer program runs in the processor, it can implement the method described in steps S1 to S4.

[0156] It should be noted that the above sequence of embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0157] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key points of each embodiment are the differences from other embodiments.

Claims

1. A constant temperature control method applied to the cold chain transportation process of medicines, characterized in that: The method comprises: Obtain the temperature data of each temperature sensor in the carriage at each moment during the pharmaceutical cold chain transportation process, the distance between each temperature sensor and the carriage door, and simultaneously obtain the temperature data outside the carriage at each moment; The temperature sensor closest to the door of the carriage is used as a reference sensor, and the degree of temperature change at each moment is obtained according to the correlation of the temperature data at each moment between each temperature sensor and the reference sensor, and the change of the temperature data at each moment of each temperature sensor; a plurality of sample time periods are obtained according to the degree of temperature change at each moment; any one of the sample time periods is used as a target sample time period, and the temperature control time period of the target sample time period is obtained according to the distribution of the temperature data of all the temperature sensors at the same moment in the target sample time period; The temperature control time period of the target sample time period is taken as the target temperature control time period, and the temperature control preference degree of the target sample time period is obtained according to the difference between the overall level of temperature data outside the vehicle compartment at all times within the target sample time period and the optimal temperature of the medicine, the difference between the temperature data of each temperature sensor at each time of the target temperature control time period and the optimal temperature of the medicine, and the length of the target temperature control time period; the correction coefficient of the target sample time period is obtained according to the difference between the length of the target sample time period and the target temperature control time period, the difference between the overall level of temperature data outside the vehicle compartment at all times within the target sample time period and the optimal temperature of the medicine, and the difference between the temperature control preference degree between the target sample time period and other sample time periods except the target sample time period; The PID controller is adjusted based on the correction coefficient of each sample time period, and the temperature is controlled using the adjusted PID controller.

2. A constant temperature control method for cold chain transportation of medicines according to claim 1, characterized in that: The obtaining of the temperature variation degree at each moment comprises: Any temperature sensor is used as the target temperature sensor, and the first temperature sequence of the reference sensor with respect to the delay variable is obtained. The first temperature sequence is: Obtain a second temperature sequence of the target temperature sensor with respect to the delay variable, wherein the second temperature sequence is Among them, a i represents the temperature data of the reference sensor at the i-th moment, t end represents the sequence number of the last moment; Δt represents the delay variable, 0≤Δt≤(d―d′)×ω, and Δt is an integer, where d represents the distance between the target temperature sensor and the compartment door; d′ represents the distance between the reference sensor and the compartment door; ω represents the preset maximum delay value; Using the Pearson correlation coefficient between the first temperature sequence and the second temperature sequence as the data change correlation between the reference sensor and the target sensor with respect to the time delay variable, and using the time delay variable corresponding to the maximum value of the data change correlation as the temperature change lag time of the target temperature sensor; Taking the absolute value of the difference between the temperature data of the target temperature sensor at each moment and the next adjacent moment as the temperature change of the target temperature sensor at each moment; Based on the calculation formula of the temperature change degree, the temperature change degree at each moment is obtained, and the calculation formula of the temperature change degree is: Among them, A k Indicates the degree of temperature change at the kth moment; t end Indicates the serial number of the last moment; T max Indicates the maximum value of the temperature change hysteresis time of all temperature sensors; T i Indicates the temperature change lag time of the i-th temperature sensor; Indicates that the i-th temperature sensor is at the k+T i The temperature change at each moment; I represents the number of temperature sensors.

3. A constant temperature control method for cold chain transportation of medicines according to claim 1, characterized in that: The obtaining of multiple sample time periods comprises: Taking any moment as the target moment, taking the first number of moments closest to the target moment as the reference moments of the target moment, if the temperature change degree at the target moment is greater than the temperature change degrees at all reference moments, taking the target moment as the door opening moment, traversing all moments, and extracting all the door opening moments; Extract multiple normal temperature moments from all moments, wherein the temperature data of all temperature sensors at the same normal temperature moment are within the normal temperature range, take any one of the compartment door opening moments as the target opening moment, and take the normal temperature moment after the target opening moment and closest to the target opening moment as the temperature recovery moment of the target opening moment; The time period between the target start-up time and the temperature recovery time at the target start-up time is taken as a sample time period.

4. A constant temperature control method for cold chain transportation of medicines according to claim 1, characterized in that: The temperature control time period for obtaining the target sample time period includes: The standard deviation of the temperature data of all temperature sensors at the same time in the target sample time period is used as the temperature dispersion at each time in the target sample time period; In the target sample time period, the time corresponding to the maximum value of the temperature dispersion is used as the closing time of the carriage door in the target sample time period; The time period between the closing moment of the compartment door in the target sample time period and the last moment of the target sample time period is used as the temperature control time period of the target sample time period.

5. The constant temperature control method for cold chain transportation of medicines according to claim 1, characterized in that: The temperature control optimization degree of obtaining the target sample time period includes: The average value of the temperature data outside the vehicle compartment at all times during the target sample period is used as the overall temperature value outside the vehicle during the target sample period, and the difference between the overall temperature value outside the vehicle during the target sample period and the optimal temperature of the medicine is used as the temperature difference value during the target sample period; Based on the calculation formula of the overshoot degree, the overshoot degree of the target sample time period is obtained, and the calculation formula of the overshoot degree is: Where B represents the overshoot degree of the target sample time period; E i represents the overshoot factor of the ith temperature sensor in the target sample time period; I represents the number of temperature sensors; μ represents the temperature difference value in the target sample time period; D represents the optimal temperature of the medicine; a (i,t) represents the temperature data of the ith temperature sensor at the tth moment within the target temperature control time period; S represents the target temperature control time period; ∈ represents the belonging symbol; max() represents the maximum value function; The overshoot degree of the target sample time period and the length of the target temperature control time period are integrated and negatively correlated normalized to obtain the temperature control optimization degree of the target sample time period.

6. A constant temperature control method for cold chain transportation of medicines according to claim 5, characterized in that: The correction coefficient for obtaining the target sample time period includes: The difference between the length of each sample time period and the length of the temperature control time period of each sample time period is used as the door opening time of each sample time period; According to the difference in the door opening time, the difference in the temperature difference value, and the difference in the temperature control preference degree between the target sample time period and each other sample time period, a relative reference value between each other sample time period and the target sample time period is obtained; Using other sample time periods corresponding to the preset second number of largest relative reference values ​​as reference sample time periods for the target sample time period; The correction coefficient of the target sample time period is obtained according to the relative reference value between each reference sample time period and the target sample time period, the difference in the overshoot degree between each reference sample time period and the target sample time period, and the difference in the length of the temperature control time period.

7. A constant temperature control method for cold chain transportation of medicines according to claim 6, characterized in that: The obtaining of the relative reference value between each other sample time period and the target sample time period comprises: Based on the calculation formula of relative reference value, the relative reference value between each other sample time period and the target sample time period is obtained. The calculation formula of the relative reference value is: in, represents the relative reference value between the jth sample time period other than the target sample time period and the target sample time period; φ j represents the preferred degree of temperature control in the jth sample time period other than the target sample time period; φ represents the preferred degree of temperature control in the target sample time period; F j represents the environmental difference between the jth sample time period other than the target sample time period and the target sample time period; L j represents the door opening time of the jth sample time period other than the target sample time period; L represents the door opening time of the target sample time period; μ j represents the temperature difference value of the jth sample time period except the target sample time period; μ represents the temperature difference value of the target sample time period; norm() represents the normalization function; ε represents the preset adjustment parameter, and its value range is [0.001, 0.01].

8. A constant temperature control method for pharmaceutical cold chain transportation according to claim 6, characterized in that: The correction coefficient for obtaining the target sample time period includes: Based on the calculation formula of the correction coefficient, the correction coefficient of the target sample time period is obtained, and the calculation formula of the correction coefficient is: Among them, ψ represents the correction coefficient of the target sample time period; Indicates the relative reference value between the nth reference sample period and the target sample period; B n represents the overshoot degree of the nth reference sample time period; B represents the overshoot degree of the target sample time period; H n represents the length of the temperature control period of the nth reference sample period; H represents the length of the temperature control period of the target sample period; and N represents the number of reference sample periods of the target sample period.

9. A constant temperature control method for cold chain transportation of medicines according to claim 7, characterized in that: The method of adjusting the PID controller based on the correction coefficient of each sample time period and controlling the temperature using the adjusted PID controller includes: The last sample period is taken as the current sample period, and the other sample periods except the current sample period are taken as the historical sample periods; Calculate the environmental difference parameter between the current sample time period and each historical sample time period based on the calculation method of the environmental difference between the j-th sample time period other than the target sample time period and the target sample time period; The correction coefficient of the historical sample time period corresponding to the minimum value of the environmental difference parameter is used as the critical gain adjustment coefficient of the PID controller; Acquire the critical gain and critical period of the PID control system, and use the product value of the critical gain adjustment coefficient and the critical gain as the adjusted critical gain; Inputting the adjusted critical gain and critical period into a Ziegler-Nichols algorithm to obtain an adjusted proportional coefficient, an adjusted integral coefficient, and an adjusted differential coefficient; The temperature in the vehicle cabin is controlled by using a PID controller that adjusts the proportional coefficient, the integral coefficient, and the differential coefficient.

10. A constant temperature control system applied to a pharmaceutical cold chain transportation process, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

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