Evidence map›Paper›PMID 39955322›Full record

ArticleScientific reports2025

Adaptive variable channel heat dissipation control of ground control station under various work modes.

Dexin Wang, Jiali Tao, Jin Lei, Xinyan Qin, Yanqi Wang, Jie Song, Tianming Feng, Yujie Zeng

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Dexin WangCollege of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China.
Jiali TaoCollege of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China.
Jin LeiCollege of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China. jinlei@shzu.edu.cn.
Xinyan QinCollege of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China.
Yanqi WangCollege of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China.
Jie SongCollege of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China.
Tianming FengCollege of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China.
Yujie ZengCollege of Mechanical and Electrical Engineering, Shihezi University, Shihezi, 832003, China.

Funding

National Outstanding Youth Science Fund Project of National Natural Science Foundation of China 62063030National Outstanding Youth Science Fund Project of National Natural Science Foundation of China 62163032
6 · The paper itself

Abstract

To address the challenges posed by varying heat generation modules in Ground Control Stations (GCS) during various work modes, a cooling system has been developed. This research introduces an Adaptive Variable Channel Control (AVCC) cooling approach using the Deep Reinforcement Learning Soft Actor-Critic (SAC) algorithm. The primary contributions of this paper include: (1) the design of a distributed cooling module featuring multiple cooling fans, which enables a variable channel cooling structure; (2) the development of a multi-module temperature control platform that simulates the heat generation conditions of each module under six work modes, providing a training environment for the cooling control algorithm; (3) the formulation of a model-free control method based on the SAC algorithm, AVCC, to optimize the cooling efficiency and endurance of the GCS. Finally, the effectiveness of the AVCC method was evaluated under maximum load conditions, contrasting it with a rule-based policy. The experimental results indicate that the AVCC method is able to cool the modules B (voltage stabilizer), Q (battery), E (charger), G (data transmission), D (voltage stabilizer), C (picture transmission), H (computer), and F (voltage stabilizer) from 78.9 °C, 58.5 °C, 88.3 °C, 88.3 °C, 79.2 °C, 88.9 °C, 77.5 °C, and 78.8 °C, respectively, to 50 °C in 280 s, improving the cooling efficiency by 40.4% and decreasing the energy consumption by 42.2% compared to the rule-based approach. The proposed distributed cooling module and AVCC method improve cooling efficiency and reduce energy consumption in the GCS. This study provides a valuable reference for the control and design of cooling systems in electronic equipment cabinets, especially those with similar shapes, sizes, cooling methods, number of heat sources and environmental conditions.

Indexed as

AVCC cooling controlDeep reinforcement learningGround control station

Identifiers

PMID39955322
PMCPMC11830006

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.