CN-121981639-A - Digital twin-driven ice bag cold chain full-link management and control method and system

CN121981639ACN 121981639 ACN121981639 ACN 121981639ACN-121981639-A

Abstract

The invention relates to the technical field of cold chain transportation management and control, in particular to a digital twin-driven ice bag cold chain full-link management and control method and system, which comprises the steps of constructing a virtual model by comprehensively integrating parameters of ice bags, packaging and transportation equipment, visually presenting the states of all parts of an ice bag cold chain system, and providing a solid foundation for management and control by observing potential problems in advance; the method has the advantages of ensuring timely mastering of state changes by collecting data in real time and utilizing blockchain storage, ensuring the authenticity and non-falsifiability of the data, enhancing the management and control reliability, realizing accurate regulation and control of transportation equipment by taking a minimized dynamic quality entropy as a target to construct a model and comprehensively generating real-time regulation and control instructions by multiple factors, improving the operation efficiency, reducing the energy consumption and the cost, rapidly formulating a scheme for coping with temperature control risks by searching similar historical scenes and dynamically adjusting strategies, fully utilizing historical experience, and enhancing the risk coping capability.

Inventors

ZHENG XIAONA
LI TENG
GONG ZHONGQI
ZHANG BAOJIAN
JIA YAOYAO

Assignees

杭州华冰新材料科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260409

Claims (10)

1. The digital twin-driven ice bag cold chain full-link control method is characterized by comprising the following steps of: s1, acquiring physical attribute parameters of a target ice bag, structural parameters of a packaging unit for bearing the target ice bag and initial working condition parameters of cold chain transportation equipment configured by the packaging unit; s2, acquiring ice bag state data and cold chain transportation equipment operation data in real time through a deployed sensor network, uploading the acquired data to a blockchain network for verification to form full-link trusted time sequence data, and synchronously driving a digital twin body to perform state evolution; S3, constructing an optimal control model aiming at minimizing dynamic quality entropy based on the evolved digital twin body state and full-link trusted time sequence data; And S4, when judging that the future road section has the temperature control risk, searching similar historical scenes by taking the current state of the digital twin body and preset path environment prediction information as matching conditions based on historical data in the all-link trusted time sequence data, extracting a historical regulation strategy corresponding to the similar historical scenes, and dynamically adjusting the historical regulation strategy to generate a self-adaptive cold energy maintenance map.
2. The digital twinned driven ice bag cold chain full link control method of claim 1, wherein the cold chain transport equipment comprises a transport equipment compartment, a refrigeration unit, a wind path control system, wherein the transport equipment compartment is an enclosed space loaded with cargo.
3. The digital twinning driven ice bag cold chain full link control method of claim 1, wherein S1 comprises: Establishing a three-dimensional geometric model of the target ice bag, the packaging unit and the cold chain transportation equipment in the digital twin body, and endowing each target ice bag with a unique digital identity on the corresponding three-dimensional geometric model; In a space region of a target ice bag and a packaging unit in a three-dimensional geometric model, discretizing the space region into voxel grids, wherein each voxel corresponds to one node, and constructing a cold energy field-stress cloud representing cold energy distribution inside the ice bag and a mechanical state of the packaging structure, wherein the voxel nodes in the geometric region of the ice bag are associated with cold energy values and thermally induced stress tensors, and the voxel nodes in the geometric region of the packaging unit are associated with mechanical stress tensors; Constructing an initial environment field reflecting the air flow organization and the temperature distribution in the cabin in a digital twin body by combining initial working condition parameters of cold chain transportation equipment, wherein the initial environment field is used as an external thermodynamic boundary condition of a cold energy field-stress cloud; And (3) carrying out data coupling on the cold energy field-stress cloud and the initial environment field so as to dynamically interact the ice bag state and the cabin environment.
4. The digital twinning driven ice bag cold chain full link control method of claim 1, wherein S2 comprises: Utilizing a blockchain edge gateway to add an acquisition time stamp, space position information and gateway equipment identification to the received real-time ice bag state data and cold chain transportation equipment operation data to form an original cold chain data unit with time stamp anchoring; Carrying out hash operation on the original cold chain data unit to generate a cold chain data fingerprint, and packaging the cold chain data fingerprint with other cold chain data units in adjacent time periods to generate a cold chain block to be identified; the method comprises the steps that a consensus node in a block chain network verifies a cold chain block to be identified, and verification content comprises logic continuity of a time stamp, uniqueness of a cold chain data fingerprint and validity of equipment identification; And simultaneously, storing the cold chain block body containing the original cold chain data unit in a distributed file system under the chain, and generating an index association pointing to the cold chain block body on the block chain to jointly form a complete full-link trusted time sequence data storage certificate and archiving record.
5. The digital twinning driven ice bag cold chain full link control method of claim 1, wherein S3 comprises: extracting the temperature of voxel nodes in all ice bag geometric areas in the three-dimensional cold energy field-stress cloud from the current state of the digital twin body, and calculating the variance of the voxel nodes as a cold energy attenuation uniformity factor; according to a phase transition temperature interval defined in physical attribute parameters of the ice bag, counting the number proportion of voxel nodes in the ice bag geometric area in the phase transition temperature interval in the three-dimensional cold energy field-stress cloud, and taking the voxel nodes as phase transition progress synchronization rate factors; analyzing stress tensors in the cold energy field-stress cloud, which correspond to the geometric area of the packing unit, identifying voxel nodes with maximum principal stress exceeding a preset yield strength threshold in the geometric area of the packing unit, defining the voxel nodes as key stress nodes, and calculating the risk space density of the key stress nodes as packing stress accumulation risk factors; dynamic weights are distributed for the three factors of the cooling energy attenuation uniformity factor, the phase change process synchronization rate factor and the packaging stress accumulation risk factor, and comprehensive field entropy coupling degree indexes are generated through weighted summation and normalization processing, wherein the negative value of the field entropy coupling degree indexes is the dynamic quality entropy.
6. The digital twinning driven ice bag cold chain full link management method of claim 1, wherein S4 comprises: abstracting each piece of historical scene data in the historical data into a multidimensional historical feature vector based on the historical data in the full-link trusted time sequence data, wherein the historical data comprises the historical scene data and a corresponding historical regulation strategy thereof; Generating a unique historical scene fingerprint for each historical scene data, wherein the fingerprint is a compact representation of the multidimensional historical feature vector of the fingerprint after dimension reduction and hashing, and constructing an index for quick retrieval based on all the historical scene fingerprints; setting a current query feature vector by taking the current state of the digital twin body and preset path environment prediction information as query conditions; and in the index constructed based on the historical scene fingerprints, performing approximate nearest neighbor search, and rapidly searching one or more similar historical scenes with the current query feature vector within a preset similarity threshold.
7. The digital twinning driven ice bag cold chain full link control method of claim 6, wherein S4 comprises: Extracting a history regulation strategy sequence corresponding to the retrieved similar history scene, wherein the history regulation strategy sequence comprises control parameters of cold chain transportation equipment on a history time line; Analyzing the state difference degree between the current state of the digital twin body and each similar historical scene; Based on the state difference degree, a self-adaptive interpolation algorithm is adopted to adjust a time base line and a control parameter value of a historical regulation strategy sequence to be matched with a time window corresponding to a future road section with temperature control risk, so that a candidate regulation sequence is obtained; And taking the candidate regulation and control sequence obtained after interpolation adjustment as an initial solution, inputting a preset map generation model, and generating a final self-adaptive cold energy maintenance map by integrating the weight of each similar historical scene and the constraint of the current state of the digital twin.
8. The method of claim 2, wherein the adaptive cold energy maintenance map generated in S4 comprises a control parameter sequence configured as a space-time cooperative control signal, the signal comprising: defining a curve of power output of a compressor of the refrigeration unit changing along with time; Defining the combination of the opening state, wind direction angle and wind speed of each air outlet of the air path control system; zone temperature set point trajectory in the cargo compartment defining a target temperature profile for different temperature zones within the cargo compartment.
9. The method for controlling a full link of a digital twin-driven ice bag cold chain according to claim 8, wherein the refrigerating unit and the wind path control system of the cold chain transportation equipment are multi-mode adaptive temperature control systems, and the method is characterized by receiving and analyzing a real-time regulation instruction set or an adaptive cold energy maintenance map, and executing at least one of the following control modes: providing refrigeration intensity at different bilges or different heights of the same bilge according to a real-time regulation instruction set; the pulse air supply mode is to control the air path to intermittently supply air according to the real-time regulation instruction set; And in the vortex guiding mode, the opening, closing and angles of a plurality of air doors are coordinated according to a real-time regulation instruction set, so that controllable air vortex is formed in the cabin.
10. A digital twin-driven ice bag cold chain full link control system, which is applied to the digital twin-driven ice bag cold chain full link control method as claimed in any one of claims 1 to 9, and comprises the following steps: The twin body construction module is used for acquiring physical attribute parameters of the target ice bag, structural parameters of a packaging unit for bearing the target ice bag and initial working condition parameters of cold chain transportation equipment configured by the packaging unit; the data driving evolution module is used for collecting ice bag state data and cold chain transportation equipment operation data in real time through a deployed sensor network, uploading the collected data to a blockchain network for verification, forming all-link trusted time sequence data, and synchronously driving a digital twin body to carry out state evolution; The optimization instruction generation module is used for constructing an optimization control model aiming at minimizing dynamic quality entropy based on the evolved digital twin body state and the full-link trusted time sequence data; The self-adaptive map generation module is used for searching similar historical scenes by taking the current state of the digital twin and preset path environment prediction information as matching conditions based on historical data in the all-link trusted time sequence data when judging that the future road section has temperature control risks, extracting a historical regulation strategy corresponding to the similar historical scenes, and dynamically adjusting the historical regulation strategy to generate a self-adaptive cold energy maintenance map.

Description

Digital twin-driven ice bag cold chain full-link management and control method and system Technical Field The invention relates to the technical field of cold chain transportation management and control, in particular to a digital twin-driven ice bag cold chain full-link management and control method and system. Background At present, a refrigeration unit, an air path control system and a distributed temperature sensor are commonly configured in cold chain transportation equipment, return air temperature PID feedback is adopted to realize maintenance of the cabin environment, and an ice bag is used as a passive cold storage element to release cold only by means of physical characteristics of a phase change material. However, the phase change process of the ice bag has nonlinearity and time lag, the internal cold energy spatial distribution, the phase change process group synchronism and the packaging stress state induced by temperature gradient cannot be perceived by the existing monitoring means, when a plurality of batches of ice bag goods with different initial states are simultaneously carried in the cabin, the refrigeration system cannot identify local cold energy difference, a global homogenization regulation and control strategy is still adopted, so that the ice bag is uneven in cold release, concentrated in stress and low in cold energy utilization rate, meanwhile, the prior art is in a post alarm mode, the prediction capability of the residual cold energy situation of the ice bag and the future environmental risk is lacked, and the prospective intervention of equipment cannot be implemented before the temperature control risk occurs. Therefore, the invention provides a digital twin-driven ice bag cold chain full-link control method and system. Disclosure of Invention The invention aims to solve the problems in the background technology, and provides a digital twin-driven ice bag cold chain full-link control method and a system. In order to achieve the above purpose, the present invention adopts the following technical scheme: the first aspect of the invention provides a digital twin-driven ice bag cold chain full-link control method, which comprises the following steps: s1, acquiring physical attribute parameters of a target ice bag, structural parameters of a packaging unit for bearing the target ice bag and initial working condition parameters of cold chain transportation equipment configured by the physical attribute parameters, wherein the cold chain transportation equipment comprises a transportation equipment cabin, a refrigerating unit and an air path control system; s2, acquiring ice bag state data and cold chain transportation equipment operation data in real time through a deployed sensor network, uploading the acquired data to a blockchain network for verification to form full-link trusted time sequence data, and synchronously driving a digital twin body to perform state evolution; S3, constructing an optimal control model aiming at minimizing dynamic quality entropy based on the evolved digital twin body state and full-link trusted time sequence data; And S4, when judging that the future road section has the temperature control risk, searching similar historical scenes by taking the current state of the digital twin body and preset path environment prediction information as matching conditions based on historical data in the all-link trusted time sequence data, extracting a historical regulation strategy corresponding to the similar historical scenes, and dynamically adjusting the historical regulation strategy to generate a self-adaptive cold energy maintenance map. Further, the cold chain transportation equipment comprises a transportation equipment cabin, a refrigerating unit and an air path control system, wherein the transportation equipment cabin is an enclosed space for loading goods. Further, the step S1 includes: Establishing a three-dimensional geometric model of the target ice bag, the packaging unit and the cold chain transportation equipment in the digital twin body, and endowing each target ice bag with a unique digital identity on the corresponding three-dimensional geometric model; In a space region of a target ice bag and a packaging unit in a three-dimensional geometric model, discretizing the space region into voxel grids, wherein each voxel corresponds to one node, and constructing a cold energy field-stress cloud representing cold energy distribution inside the ice bag and a mechanical state of the packaging structure, wherein the voxel nodes in the geometric region of the ice bag are associated with cold energy values and thermally induced stress tensors, and the voxel nodes in the geometric region of the packaging unit are associated with mechanical stress tensors; Constructing an initial environment field reflecting the air flow organization and the temperature distribution in the cabin in a digital twin body by combining initial working condition parameters of c