A condition based energy smart air circulation system
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
HVAC systems face challenges in balancing operating costs with maintenance costs while maintaining indoor air quality, as high-efficiency filters increase energy consumption and require frequent replacement, leading to increased labor and material costs.
Innovation Solution
A method and system that predict and balance the operational and maintenance costs of air circulation systems by monitoring differential pressure, particulate matter concentration, and airflow, recommending filter maintenance and fresh air input schedules to optimize energy use and extend filter life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If high capacity filtration system is used to maintain air quality, then indoor air quality is improved, but pressure drop across filters increases and energy consumption increases
Solution Approach 1:
The system performs preliminary action by predicting future filter conditions and scheduling maintenance before critical pressure drops occur. The optimization algorithm forecasts when filter replacement will occur and schedules it in advance to minimize energy consumption while maintaining air quality standards.
Solution Approach 2:
The system dynamically adjusts the filtration strategy based on real-time pressure drop measurements and predictive modeling. The optimization algorithm continuously adapts the filter replacement schedule and system operation parameters to balance air quality requirements with energy consumption, rather than using fixed schedules.
2Reliability
If high capacity filtration system is used to maintain air quality, then indoor air quality is improved, but filter replacement frequency increases and maintenance costs increase
Solution Approach 1:
The system schedules filter maintenance in advance based on predicted filter life and actual usage conditions. By performing preliminary assessment of filter status and forecasting replacement timing, the system optimizes maintenance scheduling to minimize disruption while ensuring air quality standards are met.
Solution Approach 2:
The system autonomously monitors filter pressure drop, predicts remaining filter life, and self-schedules maintenance activities without requiring manual intervention. The optimization algorithm automatically determines the optimal replacement timing based on actual operating conditions, reducing the need for scheduled maintenance checks.
3Reliability
If filter replacement is scheduled frequently to maintain air quality, then indoor air quality is improved, but labor costs and material costs increase
Solution Approach 1:
The system performs preliminary prediction of filter performance degradation and schedules replacements only when necessary to maintain air quality standards. This advance planning allows optimization of replacement timing to minimize impact on operational efficiency while ensuring quality requirements are met.
Solution Approach 2:
The optimization algorithm dynamically adjusts maintenance parameters including replacement frequency and timing based on actual filter performance data, operating conditions, and predicted degradation rates. This allows customization of maintenance schedules to match actual needs rather than following fixed conservative intervals.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method for improving the effectiveness of a building air circulation system having motorized blower and a contamination filter. The method including predicting a cost of operation of the system over an operational duration based on at least electricity consumption of the motor (115), and an operational cost to operate the filter (148), predicting a cost of maintenance of the system over the operational duration based on at least one of, a condition of the filter (148), a cost of a filter (148), a cost of labor to clean or replace the filter (148), and an effectiveness of the filter (148) over the operational duration, and balancing the cost of operation of the circulation system versus the cost of maintenance of the circulation system over the duration to recommend at least one of a filter use/bypass schedule, a filter maintenance schedule, and a fresh air input schedule satisfying an operation objective and an operational constraint.