Rail Vehicle Trip Optimizer for Fuel Efficiency
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Solution Overview
Problem
Operators of diesel-powered systems, such as trains and marine vessels, face challenges in optimizing fuel efficiency and emissions due to varying train configurations, loading conditions, and environmental factors, leading to suboptimal performance and increased fuel consumption.
Innovation Solution
A method and system for determining a mission plan that optimizes fuel efficiency and emissions by using a trip optimizer system, which integrates data from various sources, including locomotive and train characteristics, track conditions, and real-time monitoring, to compute optimal speed and power settings, allowing for continuous power adjustments and dynamic re-planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operators use extensive experience and knowledge to determine operating speeds and forces, then safe operation and compliance with prescribed operating parameters is improved, but the complexity of operation and difficulty in optimizing fuel consumption and emissions increases
Solution Approach 1:
The patent replaces the operator's mechanical decision-making process with an automated control system that uses sensors, processors, and algorithms to determine optimal operating parameters. The system automatically calculates fuel-efficient speeds and power settings based on real-time data from sensors monitoring train conditions, track characteristics, and environmental factors, eliminating the need for operator experience while achieving optimization.
Solution Approach 2:
The control system performs self-optimization by continuously monitoring its own performance and automatically adjusting operating parameters. The system uses feedback from sensors about actual train performance, fuel consumption, and emissions to refine its control algorithms, enabling the system to improve its own operation without external intervention.
2Ease of operation
If operators call for the same notch settings to simplify operation, then ease of operation is improved, but fuel consumption and emissions output vary significantly and cannot be minimized
Solution Approach 1:
The system transitions from static, fixed notch settings to dynamic, continuously adjusting power settings. The control system monitors real-time conditions including train speed, load, track gradient, and environmental factors to dynamically optimize power delivery at every moment, enabling continuous fuel efficiency optimization rather than relying on predetermined discrete settings.
Solution Approach 2:
The system optimizes fuel consumption by continuously adjusting operating parameters such as speed, power settings, and acceleration rates. The control algorithms modify these parameters in real-time based on the specific mission profile, train configuration, and environmental conditions, achieving optimal fuel efficiency for each individual trip rather than using standardized settings.
3Ease of operation
If a mission plan is established with fixed parameters to simplify planning, then ease of operation is improved, but the ability to adapt to varying train configurations, loading, and environmental conditions is reduced
Solution Approach 1:
The system performs preliminary optimization by pre-calculating optimal mission profiles based on anticipated conditions. The control system uses historical data, track characteristics, and environmental forecasts to pre-determine optimal operating parameters for different segments of the mission, enabling the system to adapt to varying conditions without requiring complex real-time calculations during execution.
Solution Approach 2:
The system incorporates continuous feedback loops that monitor actual train performance, fuel consumption, and environmental conditions. This feedback is used to adjust the mission plan in real-time, allowing the system to adapt to varying train configurations, loading conditions, and environmental factors while maintaining operational simplicity through automated adjustments.
Data Source
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AI summary
Various methods are disclosed for controlling a rail vehicle or other powered system based on an optimized mission plan. One embodiment relates to method for determining a mission plan for a powered system when a desired parameter of the mission plan is unobtainable and/or exceeds a predefined limit. The method comprises identifying a desired parameter prior to creating a mission plan, wherein the desired parameter may be unobtainable and/or in violation of a predefined limit, and notifying an operator of the powered system and/or a remote monitoring facility of the desired parameter.