Datacenter Liquid Cooling Control Using Thermal Power Estimation
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Solution Overview
Problem
Existing datacenter liquid cooling systems face challenges in accurately estimating power consumption and optimizing the control of dry cooler fan and pump operations to enhance cooling efficiency.
Innovation Solution
A liquid cooling method and arrangement that includes a dry cooling unit, liquid distribution circuits, temperature sensors, volume sensors, and a control module to estimate power consumption and control fan and pump speeds based on measured parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If liquid cooling blocks are positioned in direct thermal contact with heat-generating components, then cooling effectiveness is improved, but system complexity increases
Solution Approach 1:
The system divides the cooling function into separate modular components: liquid cooling blocks attached to individual rack units, distributed pumps in each rack, and centralized dry cooler units. This segmentation allows each component to be optimized independently while maintaining overall cooling effectiveness.
Solution Approach 2:
The system transitions from direct liquid-to-liquid heat exchange to an indirect air-to-liquid heat exchange mechanism by introducing dry cooler units with finned heat exchangers exposed to ambient air, adding a spatial dimension for heat dissipation.
2Temperature
If cooling loop components operate at high capacity, then cooling performance is improved, but energy consumption increases
Solution Approach 1:
The system implements dynamic control of pump and fan operations based on real-time thermal conditions and power consumption estimates. Pumps adjust their flow rates and fans adjust their speeds to match the actual cooling demand, avoiding continuous high-capacity operation.
Solution Approach 2:
Temperature sensors continuously monitor cooling liquid temperature and rack unit thermal conditions, feeding this data back to the control system which adjusts pump and fan operations accordingly. This closed-loop feedback ensures optimal performance while minimizing energy consumption.
3Use of energy by moving object
If power consumption is estimated and used to control cooling operations, then energy efficiency is improved, but measurement and control complexity increases
Solution Approach 1:
The control system performs multiple functions through a single integrated platform: estimating power consumption from temperature and flow data, determining cooling demands, controlling pump speeds, adjusting fan operations, and monitoring system status. This universal control approach reduces overall system complexity despite the multiple functions performed.
Solution Approach 2:
The system uses its own operational data (temperature measurements, flow rates) to automatically estimate power consumption and adjust its cooling operations without external intervention. The cooling system essentially self-regulates based on its measured performance parameters.
4Measurement precision
If multiple temperature sensors and flow meters are deployed, then measurement accuracy is improved, but system cost and complexity increase
Solution Approach 1:
Temperature sensors are strategically positioned at specific locations where they provide maximum measurement value: in the cooling liquid supply line and at rack units with highest power consumption. This localized sensing approach achieves adequate measurement accuracy without deploying sensors throughout the entire system.
Solution Approach 2:
The control system uses temperature and flow measurements for multiple purposes: calculating power consumption, determining cooling demands, monitoring system health, and optimizing pump/fan operations. This multi-use of measurement data reduces the need for additional specialized sensors and instruments.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution effectively estimates power consumption and optimizes the operation of dry cooler fans and pumps, leading to improved cooling efficiency and reduced energy consumption in datacenter environments.
Implementation Method 1
the received cooling liquid absorbs the generated heat
Implementation Method 2
the heated liquid is circulated, via the cooling loop arrangement, back to cooling liquid source for re-cooling
Implementation Method 3
a dry cooling unit to supply a cooling liquid to the rack-mounted processing assemblies and receive a heated liquid from the rack-mounted processing assemblies, the dry cooling unit comprising a fan assembly and a heat exchanger unit
Implementation Method 4
the dry cooling unit comprising a fan assembly and a heat exchanger unit
Data Source
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AI summary
A liquid cooling method and system for estimating power consumption of cooling rack-mounted processing assemblies and controlling corresponding fan and pump speeds, is presented. The presented method and system provide for the estimation of the power consumption of the rack-mounted data processing assemblies by calculating a thermal load based on measured cooling liquid temperatures, heated liquid temperatures, ambient dry cooler temperatures, and cooling liquid volume and controlling the fan speed based on the estimated power consumption. The presented method and system also provide for controlling the pump speed based on measured flow rates and corresponding empirically derived pump head pressure values H.