Predictive temperature management system controller
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Solution Overview
Problem
Conventional temperature management systems for buildings, such as heating and air conditioning, often fail to achieve energy efficiency and occupant comfort due to lack of forward planning and ignorance of thermal response, leading to fluctuating room temperatures and unnecessary energy usage.
Innovation Solution
A controller that uses a data processor to calculate energy supply based on predicted room temperatures, cost of energy, and tolerance of temperature deviations from set points, optimizing energy use while maintaining comfort by considering thermal characteristics and external factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional thermostat control with hysteresis is used to turn heat source on and off, then the control system is simple to operate, but the room temperature fluctuates significantly and energy efficiency is poor
Solution Approach 1:
The system performs preliminary heating or cooling actions before the scheduled set point temperature period begins. The controller calculates the thermal response time of the house and initiates heating/cooling in advance so that the room temperature reaches the set point at the beginning of the scheduled period, eliminating temperature fluctuations and discomfort for occupants.
2Loss of energy
If set point temperature is raised for a short period, then energy savings can be achieved, but the room temperature increases gradually and may not reach the set point by the end of the period
Solution Approach 1:
The controller calculates the required lead time based on the house's thermal response characteristics and initiates heating or cooling before the set point temperature period begins. This ensures that the room temperature reaches the desired set point at the start of the period, maintaining both energy efficiency and precise temperature control.
3Loss of energy
If predictive temperature management is used to optimize energy efficiency, then energy consumption is reduced, but the system complexity increases
Solution Approach 1:
The system automatically determines the thermal response characteristics of the house by monitoring temperature changes in response to heating or cooling cycles. This self-learning capability eliminates the need for manual input of building parameters, reducing system complexity while enabling predictive control and energy optimization.
4Manufacturing precision
If thermal response prediction is implemented to achieve forward planning, then temperature control accuracy is improved, but the computational requirements increase
Solution Approach 1:
The system determines the thermal response time parameter by monitoring actual temperature changes in the house and adjusting this parameter dynamically. This approach simplifies the predictive model to use a single key parameter rather than complex multi-parameter models, reducing computational requirements while maintaining accurate temperature prediction and control.
Data Source
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AI summary
A controller for a temperature management system for heating and/or cooling a room in accordance with a schedule of set point temperatures over a control period as a data processor arrangement (10). A signal indicative of the current temperature of the room is received at a temperature input (9) for receiving a signal indicative of the current temperature in the room and a control output (18) for supplying control signals to the system. The controller has at least one electronic memory for storing said schedule of set point temperatures, a relationship, based on known heating or cooling characteristics of the room, between the energy supplied to the system in a portion of the control period and the predicted temperature of the room during that portion and subsequent portions of the control period. The electronic memory also stores a first parameter value representative of the cost of supplying said energy and a second parameter value representative of a predetermined acceptability of variations of the actual or predicted temperature of the room from the set point schedule, wherein the processor arrangement (10) is operable to calculate, for each said portion, the energy to be supplied to the system in order for a plurality of parameter values to satisfy a predetermined criterion, said plurality of parameter values comprising said first parameter value and said second parameter value.