Constant temperature control method and system applied to medicine cold chain transportation process

Abstract

The invention relates to the field of constant temperature control, in particular to a constant temperature control method and system applied to a medicine cold chain transportation process. The method comprises the following steps: firstly, acquiring temperature data of each temperature sensor in a carriage at each moment in a medicine cold chain transportation process, acquiring temperature data outside the carriage at each moment, and extracting a plurality of sample time periods according to change characteristics of the temperature data of the temperature sensors at each moment; further extracting a temperature control time period in each sample time period, and analyzing the difference between the temperature data of the outside of the carriage in the sample time period and the optimal temperature of the medicine, the difference between the temperature data of each temperature sensor at each moment of the temperature control time period and the optimal temperature of the medicine, and the length of the temperature control time period; and a correction coefficient of each sample time period is obtained, the PID controller is adjusted, and the temperature is controlled by using the adjusted PID controller. The effect of temperature control in the carriage in the medicine cold chain transportation process can be improved.

Description

Technical Field

[0001] The present invention relates to the field of constant temperature control, and in particular to a constant temperature control method and system applied to a 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 growing demand for biopharmaceuticals, vaccines and other temperature-sensitive drugs, the requirements for cold chain transportation are becoming more and more stringent. In the process of drug transportation, especially for drugs such as biologics and vaccines that require strict temperature control, maintaining a constant temperature in 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 the related art, a PID control system is usually used to control the temperature inside the carriage during the cold chain transportation of medicines. However, temperature fluctuations are inevitable during the cold chain transportation of medicines, especially during operations such as opening and closing carriage doors and loading and unloading medicines. This often leads to a relatively obvious temperature gradient in the carriage. When the PID parameter is 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 serious temperature adjustment overshoot. When the PID parameter is set too small, the temperature adjustment speed inside the carriage will be too slow, making it impossible to quickly alleviate the uneven temperature inside the carriage, resulting in the inability of existing methods to effectively control the temperature inside the carriage during the cold chain transportation of medicines. Summary of the invention

[0004] In order to solve the technical problem that the existing method cannot effectively control the temperature in the compartment during the cold chain transportation of medicines, the purpose of the present invention is to provide a constant temperature control method and system applied to the cold chain transportation of medicines. The technical scheme adopted is as follows:

[0005] The present invention proposes a constant temperature control method applied to the cold chain transportation process of medicines, the method comprising:

[0006] 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;

[0007] 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;

[0008] 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;

[0009] 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.

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

[0011] Any temperature sensor is used as the target temperature sensor to obtain the first temperature sequence of the reference sensor with respect to the delay variable. 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;

[0012] 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;

[0013] The absolute value of the difference between the temperature data of the target temperature sensor at each moment and the next adjacent moment is used as the temperature change of the target temperature sensor at each moment;

[0014] 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:

[0015]

[0016] 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.

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

[0018] 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;

[0019] 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;

[0020] 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.

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

[0022] 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;

[0023] 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;

[0024] 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.

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

[0026] 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;

[0027] 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:

[0028]

[0029] 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;

[0030] 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.

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

[0032] 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;

[0033] 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;

[0034] 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;

[0035] 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.

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

[0037] 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:

[0038]

[0039] 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].

[0040] Furthermore, the correction coefficient for obtaining the target sample time period includes:

[0041] 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:

[0042]

[0043] 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 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; and N represents the number of reference sample periods of the target sample period.

[0044] Further, the step 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:

[0045] 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;

[0046] 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;

[0047] 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;

[0048] 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;

[0049] 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;

[0050] 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.

[0051] The present invention also proposes a constant temperature control system applied to the cold chain transportation process of medicines. 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, it implements any step of a constant temperature control method applied to the cold chain transportation process of medicines.

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

[0053] The present invention collects temperature data from multiple positions in a constant temperature compartment, combines the temperature change data from multiple historical compartment door opening processes, performs segmented analysis and optimization adjustment, dynamically improves PID control parameters, and constructs a critical gain correction mechanism based on the similarity of historical samples by analyzing the time it takes for the temperature to return to a normal level after the compartment is closed, the degree of overshoot in the temperature control process, and the difference in environmental impacts, thereby realizing adaptive optimization of PID parameters. The present invention can significantly improve the temperature control speed while minimizing the overshoot phenomenon in the temperature control process, thereby reducing the interference of the external environment of the compartment on the temperature of the medicine, and improving the temperature control accuracy and stability in the cold chain transportation of medicines, thereby 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 drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 A flow chart of a constant temperature control method applied to a pharmaceutical cold chain transportation process provided by one embodiment of the present invention;

[0056] Figure 2 A schematic diagram of a constant temperature vehicle interior device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the constant temperature control method and system for the cold chain transportation process of medicines proposed in accordance with the present invention, in combination with the accompanying drawings and preferred embodiments, and its specific implementation, structure, characteristics and effects are described as follows. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0058] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0059] The following is a detailed description of a specific scheme of a constant temperature control method and system for cold chain transportation of medicines provided by the present invention in conjunction with the accompanying drawings.

[0060] See also Figure 1, which shows a flow chart of a constant temperature control method applied to a pharmaceutical cold chain transportation process provided by an embodiment of the present invention, the method comprising:

[0061] Step S1: Obtain the temperature data of each temperature sensor in the carriage at each moment during the cold chain transportation of medicines, 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 are as follows:

[0063] (1) Temperature sensor:

[0064] Model: PT100 RTD sensor, this temperature sensor has high accuracy and is suitable for cold chain transportation environment;

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

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

[0067] Temperature sensors should be installed at multiple locations within the vehicle, including near the door, in the center of the vehicle, and in medicine storage areas.

[0068] (2) Compressor:

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

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

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

[0072] (3) Heater:

[0073] Adopt electric film heater;

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

[0075] Installation location: The heater should be installed in a cooler area of ​​the vehicle, such as near the door or the edge of the vehicle, to compensate for heat loss due to door opening and closing.

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

[0077] ssDC fans are installed in the carriage;

[0078] The fan power ranges from 5W to 20W, ensuring that air circulates in the cabin to avoid excessive temperature gradients;

[0079] Installation location: The fan should be installed in an area of ​​the vehicle that is far away from the temperature control source to ensure air circulation without dead corners.

[0080] See also Figure 2 , which shows a schematic diagram of a constant temperature vehicle interior device provided by an embodiment of the present invention.

[0081] The embodiment of the present invention first uses various temperature sensors installed inside the carriage to collect temperature data at each moment during the cold chain transportation of medicines, and at the same time records the distance between each temperature sensor inside the carriage and the carriage door, wherein 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, the embodiment of the present invention also needs to install a temperature sensor outside the car, and use the temperature sensor outside the car to collect temperature data outside the car at every moment.

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

[0084] Step S2: Take the temperature sensor closest to the car door as the reference sensor, and obtain the degree of temperature change at each moment based on the correlation of temperature data at each moment between each temperature sensor and the reference sensor, and the change of temperature data at each moment of each temperature sensor; obtain multiple sample time periods based on the degree of temperature change at each moment; take any sample time period as the target sample time period, and obtain the temperature control time period of the target sample time period based on the distribution of temperature data of all temperature sensors at the same moment within the target sample time period.

[0085] During the cold chain transportation of medicines, the carriage door may be opened and closed many times, and the temperature data collected by multiple temperature sensors is continuous and uninterrupted. Therefore, when the 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 it takes for the temperature in different areas to reach normal, it is first necessary to segment the cold chain transportation process of medicines in time based on the temperature data of each temperature sensor. When the carriage door is opened during the cold chain transportation of medicines, the temperature data of the temperature sensor close to the carriage door changes first and the change is more obvious. As the temperature propagates, the temperature data collected by multiple temperature sensors inside the carriage changes. The data will also change, that is, when the temperature data of the temperature sensor far away from the car door changes, there will be a certain time delay relative to the temperature sensor close to the car door. Therefore, the embodiment of the present invention first uses the temperature sensor closest to the car door 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, analyzes the time delay when the temperature changes at each temperature sensor compared to the temperature changes at the reference sensor, and combines the change characteristics of the temperature data collected by each temperature sensor to obtain the degree of temperature change at each moment. Subsequently, based on the degree of temperature change, the opening time of the car door during the cold chain transportation of medicines can be accurately analyzed.

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

[0087] First, any temperature sensor is used as the target temperature sensor to obtain the first temperature sequence of the reference sensor with respect to the delay variable. The first temperature sequence is Get the second temperature sequence of the target temperature sensor with respect to the delay variable. 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 serial number of the last moment; Δt represents the delay variable, 0≤Δt≤(d―d′)×ω, and Δt is an integer, wherein d represents the distance between the target temperature sensor and the car door; d′ represents the distance between the reference sensor and the car door; ω represents the preset maximum delay value. In one embodiment of the present invention, ω is set to 20 seconds. The specific value of ω can also be set by the implementer according to the specific implementation scenario, which is not limited here.

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

[0089] As an example, in one embodiment of the present invention, the expression of the temperature change hysteresis time of the target temperature sensor may be specifically, for example, as follows:

[0090] T=argmax[ρ(A′(Δt),B′(Δt))]

[0091] Wherein, T represents the lag time of the temperature change 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 correlation of the data change between the reference sensor and the target sensor with respect to the time delay variable; argmax[] represents the function of the independent variable corresponding to the maximum function value.

[0092] The temperature change hysteresis time of each temperature sensor can be obtained by the same method as above. It should be noted that when the reference sensor is selected as the target temperature sensor, the temperature change hysteresis time of the target temperature sensor is directly set to a value of 0.

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

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

[0095]

[0096] Among them, A k Indicates the degree of temperature change at the kth moment; t end Indicates the serial number of the last moment; Tmax 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.

[0097] Among them, when calculating the temperature change degree A at the kth moment k In the process of , the temperature change lag time of each temperature sensor is added to eliminate the influence of time lag caused by temperature propagation, which is convenient for extracting the opening time of the compartment door in the subsequent step, and is divided into 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 car door is opened, the temperature data of each temperature sensor changes most dramatically after experiencing the corresponding temperature change lag time. Therefore, the opening time of the car door can be identified according to the degree of temperature change at each moment, and multiple sample time periods can be obtained. A sample time period can be considered as the time period from the opening of the car door to the closing of the car door and then to the completion of the temperature control system's completion of the internal temperature control of the car. Subsequently, the temperature data of the temperature sensor in each sample time period can be combined to accurately obtain the parameters of the PID control system, thereby effectively controlling the temperature in the car.

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

[0100] Take any moment as the target moment, and take the preset first number of moments closest 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 locally larger, it means that the temperature data change of each temperature sensor after the corresponding temperature change lag time from the target moment is the most drastic, which further means that the target moment is more likely to be the opening moment of the car door. Therefore, if the temperature change degree at the target moment is greater than the temperature change degree of all reference moments, the target moment is taken as the opening moment of the car door, and all moments are traversed to extract all the opening moments of the car door. 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] Multiple normal temperature moments are extracted from all moments, wherein the temperature data of all temperature sensors at the same normal temperature moment are within the normal temperature range, wherein the normal temperature range during the cold chain transportation of medicines is a known range, and different medicines require different normal temperature ranges. During the cold chain transportation of medicines, the carriage door will undergo multiple opening and closing operations, and each opening and closing will trigger the temperature control system to control and regulate the temperature inside the carriage, so that the temperature returns to the normal temperature range, and then any carriage door opening moment is used as the target opening moment, and the normal temperature moment after the target opening moment and closest to the target opening moment is used 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 temperature of each area inside the carriage reaches the normal temperature range after the carriage door is opened and closed and controlled by the temperature control system. The temperature recovery moment of each carriage door opening moment can be obtained by the same method as above.

[0102] Furthermore, the time period between the target start-up time and the temperature recovery time of the target start-up time can be taken as a sample time period, and multiple sample time periods can be obtained by the same method as above.

[0103] When the car door is open, the temperature control process will be affected by the temperature outside the car. After the car door is opened, the stability of its internal temperature will gradually decrease. When the car door is closed, as the on-board compressor or heater works, its internal temperature will gradually return to normal. Therefore, the embodiment of the present invention first analyzes any sample time period, takes any sample time period as the target sample time period, and then identifies the closing time of the car door within the target sample time period based on the distribution of temperature data of all temperature sensors at the same time within the target sample time period, and obtains the temperature control time period of the target sample time period. Subsequently, based on the length of the temperature control time period, the PID control system parameters can be adjusted more accurately, thereby effectively controlling the temperature in the car.

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

[0105] First, 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.

[0106] After the car door is closed, as the temperature is adjusted, the temperature inside the car will gradually stabilize. When the car door is closed, temperature control has not been performed yet. The consistency of the temperature data of each temperature sensor at this time is worse and the degree of discreteness is higher. Therefore, within the target sample time period, the moment corresponding to the maximum value of the temperature discreteness can be used as the closing time of the car door in the target sample time period.

[0107] Then, the time period between the closing moment of the carriage door of 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 period of each sample time period can be obtained by the same method as above.

[0109] Step S3: Take the temperature control time period of the target sample time period as the target temperature control time period, and obtain the temperature control preference of the target sample time period according to the difference between the overall level of temperature data outside the vehicle at all times within the target sample time period and the optimal temperature of medicine, the difference between the temperature data of each temperature sensor at each time during the target temperature control time period and the optimal temperature of 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 temperature data outside the vehicle at all times within the target sample time period and the optimal temperature of medicine, and the difference in temperature control preference between the target sample time period and other sample time periods except the target sample time period.

[0110] There is a temperature control time period in each sample time period. Since the temperature control uses consistent PID parameters, this method will cause a large number of samples to have a long control time or a large overshoot in certain environments, which will eventually affect the stability of the medicine. When a temperature overshoot occurs in a certain area, the temperature after the overshoot will show the opposite of the situation before the control. For example, when the initial temperature outside the constant temperature compartment is greater than the optimal temperature of the medicine, due to the fixed PID parameters, the temperature adjustment of some areas during the adjustment process will be too large and lower than the optimal temperature. Therefore, the embodiment of the present invention first uses the temperature control time period of the target sample time period as the target temperature control time period, and then analyzes the overshoot of the temperature control process in the target sample time period based on the difference between the overall level of the temperature data outside the compartment at all times in the target sample time period and the optimal temperature of the medicine, and the difference between the temperature data of each temperature sensor at each time in the target temperature control time period and the optimal temperature of the medicine. In combination with the length of the target temperature control time period, the temperature control optimization degree of the target sample time period is obtained. Subsequently, the correction coefficient of the target sample time period can be accurately calculated and analyzed based on the temperature control optimization degree, thereby improving the final effect of temperature control in the compartment.

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

[0112] First, the average value of the temperature data outside the car at all times during the target sample time period is taken as the overall temperature value outside the car during the target sample time period, and the difference between the overall temperature value outside the car during the target sample time period and the optimal medical temperature is taken as the temperature difference value of the target sample time period. The larger the temperature difference value, the greater the difference between the temperature outside the car during the target sample time period and the optimal medical temperature. The temperature difference value of each sample time period can be obtained by the same method as above.

[0113] It should be noted that the optimal temperature of medicines is a known value, which is related to the specific medicines in the cold chain transportation of medicines. The optimal temperature of medicines varies for different medicines.

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

[0115]

[0116] Where 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, and μ≠0 in the actual scenario; D represents the optimal temperature of the medicine; a (i,t) It 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.

[0117] Among them, the overshoot factor E i The larger the value, the greater the overshoot phenomenon. i , and obtain the overshoot degree B of temperature control within the target sample time period.

[0118] The overshoot degree of each sample time period can be obtained by the same method as above.

[0119] Since the temperature control duration in different sample time periods is different, the shorter the control time is, the smaller the impact on the drugs inside the car. Therefore, the overshoot degree of the target sample time period and the length of the target temperature control time period can be combined and negatively correlated to obtain the temperature control optimization degree of the target sample time period.

[0120] In the embodiment of the present invention, the overshoot degree of the target sample time period and the length of the target temperature control time period may be calculated to integrate the two, which is not limited here.

[0121] In an embodiment of the present invention, a negative exponential function with a natural constant e as the base or a function form of 1-norm() can be used to implement normalization processing of negative correlation, which is not limited here, wherein norm() represents a normalization function. In one embodiment of the present invention, the normalization processing can be specifically, for example, maximum and minimum value normalization processing, and the normalization in subsequent steps can adopt maximum and minimum value normalization processing. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of numerical values, which will not be described in detail.

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

[0123] φ=1―norm(B×H)

[0124] Among them, 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; norm() represents the 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 initial moment of the target temperature control time period.

[0126] The temperature control optimization degree of each sample time period can be obtained by the same method as above.

[0127] Since traditional PID parameter settings cannot meet the temperature control requirements of the pharmaceutical cold chain transportation process, it is necessary to correct and adjust the PID controller parameters to achieve precise control of the temperature inside the car. Taking into account the different external environmental influences such as the temperature outside the car and the length of time the car door is open in different sample time periods, the regulation process will be quite different. Therefore, it is necessary to analyze the similarities of these external environmental influences on different sample time periods, and then perform subsequent regulation. Therefore, the correction coefficient of the target sample time period can be obtained based on the difference in length between the target sample time period and the target temperature control time period, the difference between the overall level of temperature data outside the car at all times within the target sample time period and the optimal temperature of the medicine, and the difference in temperature control preference between the target sample time period and other sample time periods except the target sample time period. The parameters of the PID controller can be adjusted based on the correction coefficient to achieve precise control of the temperature inside the car.

[0128] Preferably, in one 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 taken as the opening time of the car door of each sample time period. Similarly, the length of the sample time period can be expressed by the number of moments included in the sample time period, or by calculating the difference between the end moment and the initial 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 reflected in the different opening time of the car door and the different temperature difference values, the relative reference value between each other sample time period and the target sample time period can be obtained based on the difference in the opening time of the car door, the difference in the temperature difference value, and the difference in the degree of temperature control preference between the target sample time period and each other sample time period. Subsequently, the relative reference value can be used to screen out the reference sample time period of the target sample time period, and the correction coefficient of the target sample time period can be further calculated.

[0131] Preferably, in one 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 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 relative reference value is:

[0133]

[0134] 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 other than 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, which is used to prevent the denominator from being 0, and the value range of ε is [0.001, 0.01]. In one 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, which is not limited here.

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

[0136] Furthermore, 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 overshoot degree between each reference sample time period and the target sample time period, and the difference in length of the temperature control time period.

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

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

[0139]

[0140] 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 Indicates the overshoot degree of the nth reference sample time period; B indicates the overshoot degree of the target sample time period. In actual scenarios, B≠0; 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.

[0141] in, It is used to reflect the reference value of the nth reference sample time period relative to the target sample time period. It is used as a weight here. n Relatively large and H n Relatively small, is greater than 1, thus increasing the parameters that need to be adjusted later. n Relatively small and H n When it is relatively large, Less than 1, thus reducing the parameters that need to be adjusted later.

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

[0143] Step S4: adjusting the PID controller based on the correction coefficient of each sample time period, and controlling the temperature using the adjusted PID controller.

[0144] Since traditional PID parameter setting methods, such as the Ziegler-Nichols algorithm, cannot adapt to different environmental conditions, resulting in poor control of the temperature in the car compartment, the PID controller can be further adjusted based on the correction coefficient of each sample time period, and the temperature can be controlled using the adjusted PID controller, thereby improving the effect of temperature control in the car compartment during pharmaceutical cold chain transportation.

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

[0146] 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.

[0147] 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 environmental difference parameter between the current sample time period and each historical sample time period is calculated.

[0148] As an example, in one embodiment of the present invention, the expression of the environment difference parameter between the current sample time period and each historical sample time period may be specifically, for example, as follows:

[0149]

[0150] Among them, F′ m represents the environmental difference parameter between the mth historical sample period and the current sample period; L′ m represents the length of time the door is open in the mth historical sample period; L′ represents the length of time the door is open in the current sample period; μ′ m represents the temperature difference value of the mth historical sample time period; μ′ represents the temperature difference value of the current sample time period.

[0151] 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;

[0152] The critical gain and critical period of the PID control system are obtained, and the product value of the critical gain adjustment coefficient and the critical gain is used as the adjusted critical gain. The method for obtaining the critical gain and critical period of the PID control system is a technical means well known to those skilled in the art and will not be elaborated here.

[0153] The adjusted critical gain and critical period are input into the Ziegler-Nichols algorithm to obtain the adjusted proportional coefficient, the adjusted integral coefficient and the adjusted differential coefficient. The Ziegler-Nichols algorithm is a technical means well known to those skilled in the art and will not be described in detail here.

[0154] Then, by using a PID controller that adjusts the proportional coefficient, the integral coefficient and the differential coefficient, the temperature in the car is controlled so that the overshoot of the temperature after regulation will not be too large, while the speed of temperature regulation is increased as much as possible, reducing the impact of the external environment of the car on medicine.

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

[0156] It should be noted that the sequence of the above 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 accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0157] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on 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 to obtain the first temperature sequence of the reference sensor with respect to the delay variable. 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; The absolute value of the difference between the temperature data of the target temperature sensor at each moment and the next adjacent moment is used 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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