Rail Vehicle Speed Control Using Real-Time Environmental Data
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Solution Overview
Problem
Current rail vehicle speed control systems generate braking curves based on worst-case environmental scenarios, leading to unnecessary braking and fuel consumption, especially when conditions are better than assumed, and slow orders may be outdated, causing trains to travel slower than necessary.
Innovation Solution
A system that receives environmental data to assess and adjust tractive effort control parameters, allowing for dynamic generation or selection of braking curves and speed profiles based on real-time conditions, enabling the rail vehicle to maintain optimal speeds and reduce fuel consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If braking curves are generated based on worst-case environmental scenarios, then safety is improved, but fuel consumption increases and trip duration is extended
Solution Approach 1:
The system dynamically adjusts braking curves based on real-time environmental conditions (wind speed, temperature, track status) rather than using static worst-case scenarios. The control module continuously receives environmental data and modifies braking parameters accordingly, making the braking system adaptive to current conditions while maintaining safety margins.
Solution Approach 2:
The system changes key parameters of the braking curves (braking distance, deceleration rate, initiation point) based on environmental parameter assessments. When conditions are better than worst-case scenarios, the system adjusts these parameters to reduce braking duration and intensity, thereby reducing fuel consumption while preserving adequate safety margins.
2Reliability
If braking curves are generated based on worst-case environmental scenarios, then safety is improved, but trip duration is extended
Solution Approach 1:
The system dynamically adjusts braking curves based on real-time environmental conditions (wind speed, temperature, track status) rather than using static worst-case scenarios. The control module continuously receives environmental data and modifies braking parameters accordingly, making the braking system adaptive to current conditions while maintaining safety margins.
Solution Approach 2:
The system changes key parameters of the braking curves (braking distance, deceleration rate, initiation point) based on environmental parameter assessments. When conditions are better than worst-case scenarios, the system adjusts these parameters to reduce braking duration and intensity, thereby reducing trip duration while preserving adequate safety margins.
3Reliability
If slow orders are issued based on environmental conditions, then safety is improved, but fuel consumption increases when conditions change
Solution Approach 1:
The system continuously monitors environmental conditions and provides feedback to the control module, which adjusts speed profiles and braking curves in real-time. This feedback loop allows the system to cancel or modify slow orders when environmental conditions improve, preventing unnecessary speed reductions and associated fuel consumption increases while maintaining safety when conditions warrant restrictions.
Data Source
AI summary
A system, method and device for controlling a rail vehicle consist configured to traverse a rail system is provided. In one embodiment, the system may include a second module configured to receive environmental data from a first module having one or more sensors, wherein the environmental data is indicative of one or more environmental conditions for a portion of the rail system; wherein the second module is further configured to conduct an assessment of the environmental data in relation to a first control parameter; the second module is further configured to communicate one or more control signals of one of the first control parameter or a different, second control parameter based on the assessment; each of the first and second control parameters relates to controlling tractive effort of the rail vehicle consist over the portion of the rail system; and the second module is further configured to communicate the one or more control signals to a third module for control of the rail vehicle consist.