System for estimating capacity and method for estimating capacity of a cooling system
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Solution Overview
Problem
Transport refrigeration units face challenges in optimizing cooling efficiency due to varying cooling needs of different goods and trip durations, as existing systems lack precise methods for determining the appropriate temperature setpoints without knowing the cooling load.
Innovation Solution
A system and method for estimating cooling capacity by averaging computed capacity over a duty cycle associated with the effective state of a valve, using sensors for temperature, pressure, and mass flow rate measurements, and incorporating a subcooling function based on outside air temperature and valve position, with optional calibration for known valve positions and temperatures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cooling capacity is increased to meet varying cooling needs of different goods, then cooling effectiveness is improved, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts cooling capacity by computing and averaging capacity over a duty cycle associated with valve effective state, allowing the refrigeration unit to adapt to varying cooling needs of different goods and trip durations rather than operating at fixed capacity
Solution Approach 2:
The system changes operating parameters by incorporating subcooling function based on outside air temperature and valve position, and by calibrating average computed cooling capacity to optimize the balance between cooling effectiveness and energy consumption
2Use of energy by moving object
If temperature setpoints are adjusted to optimize efficiency, then energy consumption is reduced, but cooling reliability deteriorates
Solution Approach 1:
The system uses feedback by measuring temperature, pressure, and mass flow rate to compute cooling capacity in real-time, then uses this information to adjust setpoints and optimize efficiency while maintaining cooling reliability through continuous monitoring and adjustment
Solution Approach 2:
The system performs preliminary calibration of average computed cooling capacity to establish accurate baseline performance characteristics before operation, enabling more precise control and reducing the risk of unreliable cooling when setpoints are adjusted
3Measurement precision
If real-time capacity estimation is implemented, then system control precision is improved, but device complexity increases
Solution Approach 1:
The controller performs multiple functions including measuring temperature, pressure, and mass flow rate; computing cooling capacity; averaging over duty cycle; implementing subcooling function; and calibrating capacity. This multi-functionality reduces the need for separate dedicated devices for each function, thereby limiting the increase in device complexity while achieving real-time capacity estimation
Data Source
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AI summary
Provided is a system and a method for estimating capacity. The system includes one or more sensors, a compressor coupled to one or more sensors, and a controller. The controller is configured to receive one or more parameters of a cooling system, receive system state information and one or more measurements from the cooling system (306, 308), and compute a cooling capacity (304) based at least in part on the one or more parameters, one or more measurements and system state information. The system is also configured to estimate cooling capacity based on one or more computed capacity over a period of time (310), and provide the estimated capacity of the cooling system to a device in real-time.