HVAC Controller Dynamic Activation for Energy-Response Balance
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Solution Overview
Problem
Intelligent controllers face challenges in balancing conflicting control goals and constraints, particularly in dynamically adjusting environmental parameters like temperature in smart-home environments, where energy efficiency and response time often conflict.
Innovation Solution
The implementation of intelligent controllers that continuously monitor progress towards control goals, dynamically adjusting control strategies using sensor data and user inputs to achieve a balance between energy efficiency and response time, by selecting appropriate systems to activate and adjusting auto-component-activation levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the controller activates systems more aggressively to achieve setpoint changes quickly, then response time is improved, but energy usage increases
Solution Approach 1:
The controller dynamically adjusts the activation level of HVAC components based on real-time conditions. The auto-component-activation feature allows the controller to respond adaptively to changing environmental parameters and user preferences, optimizing the balance between response time and energy consumption rather than using fixed aggressive activation strategies
Solution Approach 2:
The controller modifies operational parameters such as component activation levels, cycling rates, and setpoint adjustments based on monitored conditions. By changing these parameters dynamically, the system can achieve faster response when needed while conserving energy during stable conditions, directly addressing the contradiction between response time and energy usage
2Use of energy by moving object
If the controller prioritizes energy efficiency by reducing system activation, then energy usage is reduced, but response time to achieve setpoint changes increases
Solution Approach 1:
The controller performs preliminary assessments of system conditions and user preferences before activating components. By evaluating the urgency of setpoint changes, environmental conditions, and energy considerations in advance, the controller can make informed decisions about activation levels, preventing both excessive energy use and unnecessary delays in response
3Loss of time
If the controller uses multiple systems simultaneously to achieve setpoint changes faster, then response time is improved, but device complexity increases
Solution Approach 1:
The controller dynamically determines which systems to activate based on current conditions rather than using fixed multi-system activation rules. The auto-component-activation feature allows the controller to selectively engage systems as needed, managing complexity through adaptive decision-making rather than predetermined complex coordination protocols
Data Source
AI summary
The current application is directed to intelligent controllers that continuously, periodically, or intermittently monitor progress towards one or more control goals under one or more constraints in order to achieve control that satisfies potentially conflicting goals. An intelligent controller may alter aspects of control, dynamically, while the control is being carried out, in order to ensure that goals are obtained and a balance is achieved between potentially conflicting goals. The intelligent controller uses various types of information to determine an initial control strategy as well as to dynamically adjust the control strategy as the control is being carried out.