HVAC Control Using Body Fat Ratio for Personalized Thermal Comfort
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Solution Overview
Problem
Existing HVAC control systems require constant user monitoring and do not effectively account for individual variations in body shape, leading to discomfort and increased energy consumption due to under- or overheating/cooling.
Innovation Solution
A control unit that uses a user interface to input user-specific parameters, including body fat ratio and clothing rate, in conjunction with sensor data to calculate a thermal sensation quantity and output control variables to HVAC systems, optimizing room temperature for thermal comfort with minimal user cooperation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If constant user monitoring with metabolic amount measurement devices is implemented, then thermal comfort control is improved, but user cooperation requirements and device complexity increase
Solution Approach 1:
The invention extracts the essential parameter (body fat ratio) from the complex metabolic amount measurement system. Instead of requiring continuous monitoring of all metabolic parameters through complex devices, the system only requires a single body fat ratio measurement, significantly simplifying the device while maintaining thermal comfort control reliability
Solution Approach 2:
The body fat ratio is measured in advance and stored for subsequent thermal comfort calculations. This preliminary measurement eliminates the need for continuous real-time monitoring during HVAC operation, reducing both device complexity and user burden while maintaining accurate thermal comfort control
2Ease of operation
If standardized metabolic amount adjustments based on weight, height and age are used, then ease of operation is improved, but thermal comfort accuracy deteriorates for users with non-standard body shapes
Solution Approach 1:
The invention replaces the standardized parameters (weight, height, age) with a more discriminating parameter (body fat ratio) that better captures individual thermal characteristics. This parameter change enables accurate thermal comfort prediction for users with diverse body compositions, including those with non-standard body shapes, while maintaining ease of operation through simple input requirements
3Device complexity
If HVAC systems operate without personalized parameters, then device complexity is reduced, but thermal comfort and energy efficiency deteriorate due to under- or overheating/cooling
Solution Approach 1:
The body fat ratio is measured and stored in advance, enabling the HVAC system to operate with personalized parameters without requiring complex real-time adjustments. This preliminary personalization allows the system to maintain optimal temperature settings that prevent energy-wasting overcooling or overheating while keeping device complexity low
Solution Approach 2:
By incorporating the body fat ratio parameter into the thermal comfort calculation, the system achieves personalized temperature control with minimal additional complexity. This single parameter enables the HVAC system to adapt to individual user characteristics, preventing energy loss from inappropriate temperature settings
Data Source
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AI summary
The invention relates to a method for controlling a heating- or cooling- and/or ventilation- and/or air-conditioning (HVAC)-apparatus, a corresponding control unit and possible uses of the control unit. The method for controlling the HVAC-apparatus is based on a control loop. The control loop starts off with calculating a quantity indicative of a thermal sensation of a user from at least one user-specific parameter and data from at least one sensor. Afterwards a deviation of this quantity from a value indicative of a target thermal sensation is computed. In the end the control loop outputs a control variable correlating with this deviation to the heating- or cooling- and/or ventilation- and/or air-conditioning-apparatus. During this cycle the control loop utilizes at least a body fat ratio of a user as the at least one user-specific parameter and a room air temperature as data from the at least one sensor.