Contextual Cooling Switching Between Ionic Blower and Fan
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Solution Overview
Problem
Existing cooling systems in information handling systems, such as cooling fans, generate noise and inefficiencies due to reactive temperature-based control methods, failing to accommodate anticipated contexts and workload variations.
Innovation Solution
An ion emitter/collector blower cooling system combined with a cooling fan, controlled by a contextual cooling device switching system using supervised binary or multi-level classification algorithms, adjusts airflow based on user context and workload predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If a traditional cooling fan is used to cool the information handling system, then heat dissipation is achieved, but noise is generated and the system reacts only to detected temperature increases rather than anticipating operational contexts
Solution Approach 1:
The patent replaces the traditional mechanical cooling fan with an ion emitter/collector blower system that uses electrostatic forces to move air. The ion emitter creates ions that are attracted to the ion collector, generating a silent airflow that eliminates the noise associated with mechanical fan blades while maintaining effective heat dissipation from the information handling system.
Solution Approach 2:
The patent implements a machine learning model that analyzes operational context and workload patterns to predict future cooling requirements. This allows the cooling system to activate the ion emitter/collector blower in advance of actual temperature increases, transitioning from reactive cooling based on detected temperature to predictive cooling based on anticipated operational contexts.
2Productivity
If a traditional cooling fan operates at high speed to meet anticipated cooling needs, then cooling performance is improved, but noise levels increase
Solution Approach 1:
The patent replaces the mechanical cooling fan with an ion emitter/collector blower system that uses electrostatic forces to move air. The ion emitter creates ions that are attracted to the ion collector, generating a silent airflow that eliminates the noise associated with mechanical fan blades while maintaining effective heat dissipation from the information handling system.
3Object-affected harmful factors
If a contextual cooling system uses machine learning to predictively adjust cooling operation, then noise is minimized and cooling is optimized, but system complexity increases
Solution Approach 1:
The patent implements a machine learning model that autonomously analyzes operational context, workload patterns, and cooling requirements to make real-time decisions about cooling system operation. The system self-adjusts the ion emitter/collector blower operation based on predicted cooling needs, eliminating the need for manual intervention or complex external control systems while optimizing both noise reduction and cooling performance.
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 system effectively manages cooling needs while minimizing noise and optimizing airflow, balancing ambient noise reduction and cooling efficiency.
Implementation Method 1
an ion emitter/collector blower cooling system... the ion emitter/collector blower creates silent or near-silent airflow
Data Source
AI summary
An information handling system includes a hardware processor, memory device, power system, and an ion emitter/collector blower cooling system with an ion emitter/collector blower, having an ion emitter and an ion collector, and a cooling fan, where an ionic driving circuit operatively couples high voltage to the ion emitter to create charged ions that generate an airflow along a voltage field to the ion collector. The information handling system further includes a hardware embedded controller to execute code instructions of a contextual cooling system switching system, the contextual cooling device switching system operating the ion emitter/collector blower and cooling fan based on plurality of contextual inputs including characterizing workload values under which the information handling system is being operated by the user that are input into a trained machine learning algorithm to generate instructions when to activate ion emitter/collector blower and cooling fan.


