Systems and methods for controlling a fan array
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Solution Overview
Problem
Existing fan array control systems struggle to optimize fan operation efficiently, often relying on nominal characteristics rather than real-world conditions, and fail to adapt to historical facility and environmental factors.
Innovation Solution
A control system and method that dynamically adjust the number of enabled fans and their operating speeds based on real-time efficiency measurements and historical data, using evaluation fans to determine optimal fan array configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fan array control systems rely on nominal characteristics, then device complexity is reduced, but operational efficiency deteriorates due to inability to adapt to real-world conditions
Solution Approach 1:
The system implements feedback by continuously measuring actual airflow and power consumption of fans, then using this real-world data to evaluate and adjust fan array configurations. This closed-loop approach allows the system to adapt to changing conditions while maintaining optimized performance, resolving the contradiction between simple control and high efficiency.
Solution Approach 2:
The control system performs self-optimization by automatically evaluating different fan configurations based on measured performance data and selecting the most efficient configuration without external intervention. This self-service capability enables the system to maintain high operational efficiency while keeping the control architecture relatively simple.
2Productivity
If the number of enabled fans is increased, then airflow output is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts the number of enabled fans and their individual speeds based on real-time measurements of airflow requirements and power consumption. Rather than operating fans at fixed speeds or configurations, the system continuously optimizes the fan array state to achieve the desired airflow with minimum energy expenditure, resolving the trade-off between productivity and energy use.
Solution Approach 2:
The system changes operational parameters (fan speeds, number of enabled fans) based on measured performance data to optimize the balance between airflow output and power consumption. By adjusting these parameters dynamically rather than maintaining fixed settings, the system achieves high productivity while minimizing energy consumption.
3Productivity
If real-time efficiency measurements are implemented for all fans, then operational efficiency is improved, but device complexity and measurement requirements increase
Solution Approach 1:
The system uses a limited number of evaluation fans as proxies to represent the performance characteristics of the entire fan array. By measuring only these representative fans and using their data to evaluate configurations, the system achieves operational optimization without the complexity of installing sensors on every single fan, thus resolving the contradiction between measurement accuracy and system complexity.
4Productivity
If evaluation fans are used to determine optimal configurations, then productivity is improved through optimized fan selection, but device complexity increases due to additional control logic
Solution Approach 1:
The system segments the fan array by designating specific fans as evaluation fans that represent different positions or characteristics within the array. This segmentation allows the control logic to focus on evaluating a manageable subset of fans rather than managing all fans individually, thereby achieving optimization while keeping control complexity tractable through structured division of the problem.
Data Source
AI summary
Control systems and methods for controlling an array of fans include generating an airflow corresponding to an operational setpoint, selecting a first evaluation fan and a second evaluation fan from among N enabled fans in the array, determining efficiencies of the evaluation fans based on input power, and determining fan speeds of a fan array configuration with N+1 enabled fans and a fan array configuration with N−1 enabled fans. The control systems and methods further include selecting and implementing one of the N−1 configuration, the N+1 configuration, and the original fan array configuration based on efficiencies of the first and second evaluation fans.