Multi-Zone Vapor Compression Control to Eliminate Limit Cycling
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Solution Overview
Problem
Multi-zone vapor compression systems face inefficiencies due to persistent variations in zone temperatures and heat exchanger temperatures caused by switching heat exchangers ON and OFF, leading to reduced occupant comfort and energy inefficiency, and existing controllers often sacrifice performance to enforce safety constraints reactively.
Innovation Solution
A model predictive controller (MPC) is used to smoothly control the thermal capacity of heat exchangers by enforcing linear relationships between thermal capacities and temperatures, eliminating limit cycling and allowing for predictive control without the need for additional actuators or direct measurement of thermal load disturbances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If heat exchangers are switched ON and OFF to control zone temperature, then the zone temperature can be regulated, but persistent variations in zone temperatures and heat exchanger temperatures occur which reduce occupant comfort and energy efficiency
Solution Approach 1:
The patent applies periodic action through duty cycling control where heat exchangers are switched ON and OFF in periodic cycles to modulate cooling capacity. The controller alternates between ON and OFF states based on the difference between actual and desired zone temperatures, creating a periodic control pattern that regulates temperature while managing the inherent oscillations through systematic timing and sequencing of multiple heat exchangers.
2Temperature
If heat exchangers are switched ON and OFF to control zone temperature, then the zone temperature can be regulated, but persistent variations in zone temperatures and heat exchanger temperatures occur which reduce energy efficiency
Solution Approach 1:
The patent applies periodic action through duty cycling control where heat exchangers are switched ON and OFF in periodic cycles to modulate cooling capacity. The controller alternates between ON and OFF states based on the difference between actual and desired zone temperatures, creating a periodic control pattern that regulates temperature while managing the inherent oscillations through systematic timing and sequencing of multiple heat exchangers.
Solution Approach 2:
The patent applies dynamics by transitioning from static ON/OFF control to a dynamic duty cycling strategy that adapts the switching pattern based on system state. The controller dynamically adjusts the timing and duration of ON/OFF cycles for different heat exchangers, creating a time-varying control approach that responds to changing thermal conditions and optimizes energy efficiency while maintaining comfort.
3Reliability
If reactive constraint management is used to enforce safety constraints, then equipment safety is maintained, but the controller is detuned away from constraint values which sacrifices system performance
Solution Approach 1:
The patent applies preliminary action through predictive constraint management where the controller anticipates potential constraint violations before they occur. By using predictive models to forecast future system states and identifying potential violations in advance, the controller can take preventive action to adjust control inputs, thereby maintaining safety constraints while avoiding the performance degradation associated with reactive detuning.
Solution Approach 2:
The patent applies feedback through a closed-loop predictive control system that continuously monitors system state, compares actual performance against constraints, and adjusts control actions based on predicted future behavior. The feedback mechanism uses predictive models to anticipate constraint violations and modifies control inputs proactively, creating a feedback-driven approach that maintains both safety and performance by continuously adapting to system conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach ensures accurate and efficient control of multi-zone vapor compression systems, enhancing performance and occupant comfort while maintaining equipment safety by predicting and adjusting thermal capacity smoothly, thus reducing energy consumption and maintaining safety constraints.
Implementation Method 1
A model predictive controller (MPC) is used to smoothly control the thermal capacity of heat exchangers by enforcing linear relationships between thermal capacities and temperatures
Implementation Method 2
Vapor compression systems (VCS) move thermal energy between a low temperature environment and a high temperature environment in order to perform cooling or heating operations
Data Source
AI summary
A multi-zone vapor compression system (MZ-VCS) includes a compressor connected to a set of heat exchangers controlling environments in a set of zones. A supervisory controller includes a processor configured for optimizing a cost function subject to constraints on an operation of the MZ-VCS to produce a set of values of the thermal capacity requested for the set of heat exchangers to achieve setpoint temperatures in the corresponding zones. The supervisory controller is a model predictive controller for determining the set of control inputs using a model of the MZ-VCS including a linear relationship between the thermal capacity of each heat exchanger and the temperature in a corresponding zone controlled by the heat exchanger. A set of capacity controllers, wherein there is one capacity controller for each heat exchanger, such that each capacity controller is configured for controlling the corresponding heat exchanger to achieve the requested thermal capacity.