Onboard Fuel Consumption Analysis for Vehicle Trip Planning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems for evaluating fuel consumption in vehicles are inaccurate and time-consuming due to errors in data correlation and communication interruptions, requiring large datasets for reliable results, which delays the assessment of fuel-saving technologies.
Innovation Solution
A system comprising a vehicle control module, an operating information module, and a fuel analysis module, which are onboard the vehicle to autonomously determine fuel consumption by collecting and processing operating information in real-time, reducing reliance on off-board processing and minimizing errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If off-board processing is used to evaluate fuel consumption, then data can be collected from multiple sources, but the processing time increases significantly and accuracy decreases due to data correlation errors
Solution Approach 1:
The system divides the fuel consumption evaluation process into distinct segments: onboard data collection by individual locomotives, autonomous onboard processing of fuel consumption data, and selective off-board verification. Each locomotive independently processes its own data, eliminating the need for complex centralized data correlation and significantly reducing processing time while maintaining accuracy.
Solution Approach 2:
Each locomotive is equipped with autonomous capabilities to collect, process, and evaluate its own fuel consumption data onboard. This self-service approach eliminates reliance on external processing systems, allowing immediate evaluation of fuel-saving technologies without waiting for centralized data aggregation and correlation, thereby reducing time loss while maintaining measurement precision.
2Reliability
If large datasets are collected to ensure reliable results, then measurement confidence increases, but the time required to accumulate sufficient data increases
Solution Approach 1:
The system performs preliminary data processing and validation onboard each locomotive as data is collected, rather than waiting to accumulate large datasets before any processing occurs. This preliminary action ensures data quality from the start, allowing reliable results to be achieved with smaller, progressively analyzed datasets, thereby reducing the time required to reach statistically significant conclusions.
3Loss of information
If multiple data sources are integrated for comprehensive analysis, then data completeness improves, but correlation errors increase due to timestamp mismatches
Solution Approach 1:
The system extracts and processes only the essential fuel consumption data elements onboard each locomotive, removing the need to integrate and correlate data from multiple external sources. By taking out only the necessary information (fuel consumption metrics, operational parameters) and processing it autonomously, the system maintains data completeness for fuel analysis while eliminating correlation errors that would arise from timestamp mismatches between different data sources.
Data Source
AI summary
A system includes a vehicle control module, an operating information module, and a fuel analysis module. The vehicle control module is configured to obtain a trip plan for the vehicle. The operating information module is configured to be disposed on-board the vehicle and to autonomously obtain operating information describing one or more of tractive events or braking events performed during the trip. The fuel analysis module is configured to be disposed on-board the vehicle, to receive the operating information from the operating information module, and to autonomously determine a fuel consumption for at least a portion of the trip using the operating information received from the operating information module.