HVAC Comfort-Map Control Using Qualitative User Feedback
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Solution Overview
Problem
Smart thermostats often have complex interfaces that users find difficult to interact with, leading to underutilization of their capabilities, with users either leaving them unchanged or overriding them, resulting in suboptimal energy efficiency and comfort.
Innovation Solution
An interior comfort HVAC user-feedback control system that transforms qualitative user comfort feedback into a multi-variable data representation, known as a comfort map, to adaptively control heating, ventilating, and air conditioning systems, allowing for dynamic temperature adjustments without requiring numeric temperature input from users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If smart thermostats use complex interfaces to provide advanced control capabilities, then system functionality is improved, but user ease of operation deteriorates
Solution Approach 1:
The thermostat system automatically performs comfort characterization and temperature sequence generation without requiring user interaction. The system serves itself by collecting ambient data, processing user feedback indirectly through comfort events, and autonomously optimizing HVAC control sequences, eliminating the need for complex user interfaces while maintaining advanced functionality
Solution Approach 2:
The system implements feedback through comfort events where users simply indicate comfort levels (comfortable, warm, cool) rather than manipulating complex controls. This simplified feedback mechanism is processed by the system to automatically adjust temperature sequences, resolving the contradiction between advanced functionality and ease of operation
2Ease of operation
If the thermostat requires minimal user interaction, then ease of operation is improved, but measurement precision of user comfort preferences deteriorates
Solution Approach 1:
The system performs preliminary comfort characterization during an initial comfort period before full operation begins. This preliminary action establishes baseline comfort preferences without requiring extensive user input during normal operation, allowing the system to achieve accurate comfort modeling with minimal ongoing user interaction
Solution Approach 2:
The comfort map and temperature sequences are dynamically adjusted based on incoming comfort events and environmental conditions. The system evolves its understanding of user preferences over time, refining measurement precision while maintaining minimal interaction requirements through adaptive learning
3Loss of information
If the system displays temperature setpoints to users, then information transparency is improved, but device complexity increases
Solution Approach 1:
The system extracts and displays only essential comfort information (comfortable, warm, cool indicators) rather than detailed temperature setpoints and complex system parameters. This extraction approach maintains information transparency regarding user comfort while eliminating unnecessary interface complexity
Solution Approach 2:
Instead of displaying temperature values and asking users to adjust them, the system inverts the approach by having users describe their comfort state and automatically translating this into appropriate temperature control sequences. This inversion eliminates complex temperature displays while maintaining full information transparency about comfort status
Data Source
AI summary
The INTERIOR COMFORT HVAC USER-FEEDBACK CONTROL SYSTEM AND APPARATUS transforms qualitative feedback received from a user/occupant into a “comfort map,” or modifications thereto, a comfort map being defined at least in part by one or more comfort event windows. The comfort map data is used to determine a temperature setpoint sequence that avoids regions of the map corresponding to known and/or predicted regions of user discomfort.