Method and system for setting cooling parameters from a peer transport vehicle
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Solution Overview
Problem
Cargo transport vehicles often consume more energy than necessary due to non-optimized cooling parameters, leading to increased costs and environmental impact, as existing systems fail to account for specific goods and vehicle conditions.
Innovation Solution
A method and system that utilize a server to receive data from transport vehicles, retrieve historical data from similar peer vehicles, identify those with minimal energy and fuel consumption, and adjust cooling parameters to match, optimizing energy use based on peer vehicle settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional integrated systems monitor environmental parameters, then cargo quality and safety are maintained, but energy consumption increases due to non-optimized cooling parameters
Solution Approach 1:
The system copies cooling parameters from peer transport vehicles that have demonstrated optimal energy efficiency. The server retrieves cooling parameters from multiple peer vehicles, identifies the optimal set, and applies it to the current vehicle, thereby achieving energy efficiency without compromising cargo quality
Solution Approach 2:
The system dynamically changes cooling parameters (temperature, humidity, ventilation) based on retrieved data from peer vehicles and current vehicle conditions. This allows optimization of energy consumption while maintaining cargo safety through adaptive parameter adjustment
2Use of energy by moving object
If cooling parameters are set for specific goods and vehicle conditions, then energy efficiency improves, but system complexity increases
Solution Approach 1:
A server acts as an intermediary between transport vehicles, collecting and analyzing cooling parameter data from multiple sources. This intermediary handles the complexity of data processing and optimization algorithms, keeping the individual vehicle systems relatively simple while achieving sophisticated energy optimization
Solution Approach 2:
The system uses a universal approach by collecting cooling parameters from multiple peer vehicles and applying the optimal configuration across different vehicles. This multi-functional system handles various cargo types and vehicle conditions through a standardized data collection and optimization process
Data Source
AI summary
A method for setting cooling parameters for a refrigerated transport vehicle includes receiving, from the transport vehicle, first information including energy consumption and performance parameters associated with the transport vehicle, and second information including vehicle type information and transit information associated with the transport vehicle. The method further includes retrieving historical data associated with peer transport vehicles similar to the transport vehicle based on the second information and identifying a peer transport vehicle for which energy and fuel consumption is minimum based on the second information and the retrieved historical data. Upon determining that the energy consumption and the performance parameters of the transport vehicle are greater than the energy consumption and the performance parameters of the identified peer transport vehicle, the method further includes controlling setting of the cooling parameters of the transport vehicle based on the cooling parameters of the identified peer transport vehicle.