Transport Refrigeration Unit Control Using Cargo Load Detection
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Solution Overview
Problem
Current refrigeration systems in transport containers face issues with temperature overshooting and inefficient regulation due to manual settings, leading to excessive energy consumption and false alarms from safety devices triggered by intermediate flammability refrigerants.
Innovation Solution
A system and method that uses sensors, such as LiDAR, to determine the cargo load and refrigerant concentration, adjusting temperature regulation parameters and security modes dynamically to optimize energy efficiency and minimize disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the refrigeration system operates at full capacity with manual temperature settings, then the temperature control simplicity is maintained, but temperature overshooting and poor regulation occur
Solution Approach 1:
The system dynamically adjusts refrigeration capacity based on real-time cargo load detection. The control system modifies operating parameters (compressor speed, fan speed, valve positions) according to the detected cargo volume, transitioning from static full-capacity operation to dynamic adaptive operation that maintains temperature precision without overshooting
Solution Approach 2:
The system implements feedback control by continuously monitoring cargo load via sensors (LiDAR, cameras, weight sensors) and adjusting refrigeration output accordingly. This closed-loop control prevents temperature overshooting by matching cooling capacity to actual cargo requirements, improving temperature regulation precision while maintaining ease of operation through automated adjustment
2Measurement precision
If safety devices use low flammability limit thresholds for A2L or A3 refrigerants, then refrigerant leak detection sensitivity is improved, but excessive vehicle halts occur due to false triggers
Solution Approach 1:
The system dynamically adjusts the flammability limit threshold parameter based on detected cargo load. When cargo volume is high (increasing potential fuel load), the threshold is lowered for sensitive detection. When cargo volume is low, the threshold is raised to prevent false triggers, thus maintaining detection sensitivity while ensuring vehicle operational continuity
Solution Approach 2:
The safety device transitions from static threshold operation to dynamic threshold adjustment based on real-time cargo load conditions. This adaptive approach allows the system to maintain high detection sensitivity when needed while avoiding excessive false alarms that would disrupt vehicle operation, balancing safety and productivity
3Device complexity
If the refrigeration system operates with fixed manual settings, then the system complexity is reduced, but energy consumption increases due to unnecessary full-capacity operation
Solution Approach 1:
The refrigeration system performs self-adjustment by automatically detecting cargo load and modifying its own operating parameters without external intervention. The control system autonomously optimizes energy consumption by matching cooling capacity to cargo requirements, reducing unnecessary energy use while maintaining acceptable control complexity through automated decision-making
Solution Approach 2:
The system dynamically changes operating parameters (temperature setpoints, compressor capacity, fan speed) based on detected cargo load. This adaptive parameter adjustment reduces energy consumption by avoiding full-capacity operation when cargo volume is low, while the automated nature of the adjustment keeps the control system relatively simple
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
The system provides real-time adjustment of refrigeration settings based on cargo load and refrigerant levels, enhancing temperature control and reducing unnecessary shutdowns, thus optimizing energy use and safety.
Implementation Method 1
the distance is determined based on a time of flight measurement of a signal transmitted from the at least one sensor towards the one or more objects associated with the cargo load
Data Source
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AI summary
Embodiments of the invention describe systems and methods (500) for controlling operation of a Transport Refrigeration Unit, TRU, (114) of a vehicle (102), the vehicle (102) comprising a container (104) configured to store cargo. The method (500) comprises receiving (502) first input information from at least one sensor positioned inside the container. Further, the method (500) comprises determining (504) a current amount of cargo load in the container based on the received first input information from the at least one sensor. Furthermore, the method (500) comprises controlling (508) operation of the TRU by setting one or more temperature regulation parameters for the container based on the determined current amount of cargo load in the container. Further, the operation of the TRU is controlled by triggering a specific type of security mode, among a plurality of modes, in response to detecting a type of refrigerant leak in the vehicle.