Physics-Based Cooling Actuator Optimization
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Solution Overview
Problem
The increasing power consumption in enterprise servers and data centers, particularly due to cooling equipment, poses significant operational costs and environmental impact, as fans and other cooling systems consume substantial amounts of energy.
Innovation Solution
A system and method that utilize physics-based models to optimize the settings of resource actuators, such as fans, to minimize energy consumption while meeting the resource demands of entities like blade servers, by formulating a constraint optimization problem that determines the optimal power consumption levels of resource actuators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If cooling equipment power is increased to meet thermal demands, then cooling capacity is improved, but power consumption increases
Solution Approach 1:
The patent implements dynamic control of cooling equipment by continuously monitoring thermal conditions and adjusting fan speeds accordingly. The system transitions from static full-speed operation to dynamic variable-speed control, allowing fans to operate at optimal speeds based on real-time thermal demands, thus reducing power consumption while maintaining adequate cooling capacity.
Solution Approach 2:
The system changes the operational parameters of cooling equipment by adjusting fan speeds across a continuous range rather than operating at fixed speeds. This parameter adjustment is based on thermal models and real-time conditions, enabling the system to optimize the balance between cooling capacity and power consumption by selecting appropriate fan speed parameters.
2Temperature
If fan speed is increased to meet cooling demand, then cooling performance is improved, but noise increases
Solution Approach 1:
The system dynamically adjusts fan speeds based on actual cooling requirements rather than operating at constant high speeds. By matching fan speed to real-time thermal conditions, the system minimizes noise generation while maintaining adequate cooling performance, as fans only operate at higher speeds when thermally necessary.
Solution Approach 2:
The patent utilizes parameter changes by varying fan speed settings according to thermal models and environmental conditions. This allows the system to select optimal fan speed parameters that achieve required cooling performance with minimal noise, avoiding unnecessary high-speed operation that would generate excessive noise.
3Temperature
If more cooling equipment is deployed to handle thermal loads, then cooling capacity is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal thermal management approach where a single integrated system performs multiple functions: thermal modeling, condition monitoring, optimization calculation, and actuator control. This multi-functional system replaces the need for separate complex control mechanisms for each cooling device, simplifying overall system architecture while maintaining adequate cooling capacity.
Solution Approach 2:
The cooling system incorporates self-service capabilities through automated thermal modeling and optimization. The system autonomously monitors conditions, calculates optimal settings using thermal models, and adjusts cooling equipment without requiring complex external control systems or manual intervention, thereby reducing overall system complexity.
Data Source
AI summary
In a method for supplying a resource to an entity from a resource actuator, a plurality of physics-based models pertaining to the resource actuator and the entity are developed, a condition detected at the entity is received, feedback control on a resource demand of the entity employed based upon the detected condition, feed forward control on the resource demand of the entity is employed based upon the detected condition and the plurality of physics-based models, a constraint optimization problem having an objective function and at least one constraint using the plurality of physics-based models is formulated, a solution to the constraint optimization problem is determined, in which the solution provides the actuator setting, and the resource actuator is set to the actuator setting to supply the entity with the resource from the resource actuator.