Adaptive cold chain thermal energy management device and control method
By installing retractable insulated curtains and dual-mode air curtain modules on cold chain containers, combined with an intelligent sensing and control system, low energy consumption, high sealing performance, and intelligent adaptability of cold chain containers during loading and unloading processes are achieved. This solves the problems of high energy consumption and poor sealing performance in existing technologies, and improves the efficiency and safety of cold chain transportation.
CN122143607AActive Publication Date: 2026-06-05SHANGHAI MARITIME UNIVERSITY
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHANGHAI MARITIME UNIVERSITY
- Filing Date
- 2026-05-09
- Publication Date
- 2026-06-05
Smart Images

Figure CN122143607A_ABST
Abstract
The present application relates to the technical field of cold chain logistics, and provides a self-adaptive cold chain thermal energy management device and a control method, which comprises: a retractable thermal curtain module installed at the opening of the door, used to expand to close the opening during non-entry and exit period; a dual-mode air curtain module installed above the opening of the door, used to start to form a dynamic air flow barrier when the thermal curtain is opened; and an intelligent sensing and control module, comprising a sensor group for real-time monitoring of the working state and a main control unit. The main control unit receives real-time data collected by the sensor group, predicts the working busy degree in the future time window based on the processed data, and generates a control instruction according to the prediction result to drive the retractable thermal curtain module and the dual-mode air curtain module to act cooperatively. The present application realizes the cooperation of physical isolation and air flow isolation, effectively reduces the cold and heat exchange through intelligent prediction and decision, reduces the energy consumption, and improves the working efficiency.
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