ADRC Thermal Control Using ESO for Datacenter Hot Spots
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Solution Overview
Problem
The rapid growth of datacenters and increased computing infrastructure density have made it challenging to provide effective cooling, leading to higher cooling costs and thermal management issues, such as thermal throttling of processors and storage drives.
Innovation Solution
A system employing active disturbance rejection thermal control (ADRC) using extended state observers (ESO) to generate control signals for cooling elements based on temperature measurements and estimated disturbances, allowing for efficient thermal management across multiple thermal zones in servers and datacenters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing infrastructure density is increased to drive datacenter growth, then productivity and data processing capability are improved, but thermal management difficulty and cooling costs increase
Solution Approach 1:
The datacenter is divided into multiple thermal zones, each monitored and controlled independently by ADRC controllers. This segmentation allows precise local thermal management while maintaining overall system productivity, resolving the contradiction between high density computing and thermal management complexity.
Solution Approach 2:
ADRC controllers continuously receive temperature measurements from thermal zones and use extended state observers to estimate disturbances and generate real-time control signals for cooling elements. This feedback mechanism enables dynamic thermal adaptation to high-density computing loads without proportionally increasing cooling costs.
2Reliability
If conventional cooling control methods are used in high-density datacenters, then device operation is maintained, but thermal throttling occurs and cooling efficiency decreases
Solution Approach 1:
The extended state observer in the ADRC controller estimates thermal disturbances and predicts temperature trends before they cause throttling. By taking preliminary cooling action based on predicted disturbances, the system maintains device operation reliability while avoiding excessive cooling that would reduce overall efficiency.
Solution Approach 2:
The ADRC controller dynamically adjusts cooling parameters based on real-time temperature measurements and estimated disturbances. This adaptive parameter change allows the system to maintain optimal cooling efficiency across varying computational loads while preventing thermal throttling, resolving the contradiction between reliability and productivity.
Data Source
AI summary
A system and method for active disturbance rejection based thermal control is configured to receive, at a first active disturbance rejection thermal control (ADRC) controller, a first temperature measurement from a first thermal zone. The ADRC controller generates a first output control signal for controlling a first cooling element, wherein the first output control signal is generated according a first estimated temperature and a first estimated disturbance calculated by a first extended state observer (ESO) of the first ADRC controller.