Cloud-Based Fuel Quality Recording and Station Selection
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Solution Overview
Problem
Existing systems for motor vehicles lack a comprehensive and real-time solution for making informed fuel purchasing decisions based on fuel quality and research octane number (RON) information, which are crucial for efficient engine operation and compliance with fuel standards.
Innovation Solution
A cloud-based subscription service utilizing a vehicle's ECU and telematics device to collect, process, and share fuel information, including RON and fuel quality data, with remote devices to provide subscribers with current and accurate information for selecting suitable fuel stations and ensuring fuel meets requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If fuel quality information is collected and shared in real-time through a cloud-based system, then the availability and accuracy of fuel information for decision-making is improved, but the system complexity and infrastructure requirements increase
Solution Approach 1:
A cloud-based server acts as an intermediary between fuel stations and user devices. The server receives fuel quality data from multiple fuel stations, processes and stores it centrally, then distributes relevant information to users based on their location and vehicle requirements. This intermediary approach enables real-time information sharing without requiring direct peer-to-peer communication between all system components, thus reducing overall system complexity while improving information availability.
Solution Approach 2:
The cloud-based server performs multiple functions: collecting data from various fuel stations, storing fuel quality information, processing location data, generating recommendations, and communicating with multiple user devices simultaneously. This multi-functional approach consolidates what would otherwise require separate systems into a single platform, reducing infrastructure complexity while enhancing information availability.
2Measurement precision
If the ECU calculates fuel quality parameters like RON and shares them remotely, then the precision of fuel quality measurement is improved, but the loss of time for data transmission and processing increases
Solution Approach 1:
The ECU calculates fuel quality parameters such as RON continuously and stores them locally before remote transmission. When a user needs fuel quality information, the pre-calculated data is already available in the system, ready for immediate retrieval and transmission. This preliminary calculation and storage approach eliminates the need for real-time computation during data requests, significantly reducing time loss while maintaining high measurement precision.
Solution Approach 2:
The system establishes a feedback loop where fuel quality data is continuously collected, transmitted to the cloud server, processed, and then used to generate recommendations that are sent back to users. This continuous feedback mechanism ensures that precision measurements are systematically captured and utilized, while the automated feedback process minimizes manual intervention time and streamlines data flow.
3Reliability
If comprehensive fuel information is provided to help users make informed refueling decisions, then the reliability of refueling decisions is improved, but the quantity of data to be transmitted and processed increases
Solution Approach 1:
The cloud-based server filters and personalizes fuel quality information based on each user's specific needs, such as vehicle type, fuel requirements, and location. Instead of transmitting all available fuel data universally, the system provides tailored recommendations with only the relevant fuel quality parameters for each user's situation. This localized information approach maintains high decision reliability by providing customized, relevant data while significantly reducing overall data transmission volume.
Solution Approach 2:
The system extracts and transmits only the essential fuel quality parameters needed for informed decision-making, such as RON values and key quality metrics, rather than transmitting complete raw datasets. By extracting only the critical information required for refueling decisions, the system maintains decision reliability while minimizing data transmission and processing requirements.
Data Source
AI summary
A system and method for selecting a fueling station for vehicle refueling, including receiving fuel information from a remote device corresponding to one or more fueling stations near a vehicle; upon the vehicle travelling to a selected one of the one or more fueling stations, setting a flag to a value based upon a fuel grade of fuel used to refuel the vehicle at the selected one of the one or more fueling stations; and capturing location information for at least one of the vehicle and the selected one of the one or more fueling stations. Subsequent to refueling at the selected one of the one or more fueling stations, the method further includes determining fuel information of the fuel used to refuel the vehicle; and sending the flag, the fuel information of the fuel used to refuel the vehicle, and the captured location information to the remote device.