Control of a refrigeration circuit
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing refrigeration circuit control methods do not effectively optimize operating efficiency based on performance requirements, leading to suboptimal energy usage and performance.
Innovation Solution
A controller configured to monitor prevailing conditions and use a simulation module for iterative optimization to determine a limit setting for control variables, such as compressor speed, to maximize operating efficiency, while a dynamic control module adjusts settings to target performance thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If traditional control methods targeting thermodynamic parameters are used, then temperature control is achieved, but operating efficiency is not optimized
Solution Approach 1:
The system performs preliminary determination of optimal control variable limits through iterative optimization based on objective functions before actual operation. The simulation module pre-calculates optimal operating ranges considering efficiency requirements, so that during runtime, the control system only needs to operate within these pre-determined optimal boundaries rather than performing complex real-time optimization
Solution Approach 2:
A simulation module acts as an intermediary between the physical refrigeration circuit and the control system. It creates a virtual model that evaluates objective functions and determines optimal control limits without directly controlling the physical system, thereby decoupling the complexity of efficiency optimization from the actual control operation
2Productivity
If control variable limits are expanded to improve performance response, then performance thresholds are met, but operating efficiency decreases
Solution Approach 1:
The system dynamically adjusts control variable limits by changing operational parameters based on prevailing conditions. The simulation module evaluates objective functions with varying parameters to determine optimal limits that balance performance requirements with energy efficiency, adapting to different operating scenarios rather than using fixed limits
Solution Approach 2:
The control system transitions from static control limits to dynamic limits that adapt to changing operating conditions. The simulation module continuously evaluates the model with current prevailing conditions to update optimal control variable limits, making the system responsive to performance requirements while maintaining efficiency
3Use of energy by stationary object
If iterative optimization is performed in real-time, then efficiency is maximized, but computational complexity and response time increase
Solution Approach 1:
Optimal control variable limits are determined in advance through iterative optimization based on the objective function and system model. This preliminary calculation establishes efficiency-optimized boundaries before actual operation, eliminating the need for continuous real-time iterative optimization during runtime
Solution Approach 2:
The system performs full iterative optimization only when necessary to update control limits based on changing prevailing conditions. Between updates, the system operates within established limits without continuous optimization computation, performing partial optimization actions only when triggered by significant condition changes
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
There is disclosed a controller 100 for a refrigeration circuit 10, configured to monitor a set of prevailing conditions 50 relating to the refrigeration circuit including a space temperature of a temperature-controlled space associated with the refrigeration circuit. The controller 100 has a simulation module 102 configured to determine a limit setting 152 of a control variable for the refrigeration circuit by an iterative optimisation procedure based on a model 110 corresponding to the refrigeration circuit. The objective function for the optimisation relates to an operating efficiency. The controller further comprises a dynamic control module 160 configured to: adjust an operating setting of the control variable within an operating range to target a performance threshold for a monitored performance parameter, based on monitoring of the performance parameter during operation of the refrigeration circuit; and apply the limit setting received from the simulation module as a limit to the operating range.