Railway Network Train Parameter Optimization

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Solution Overview

Problem

Current train operation systems face challenges in optimizing fuel efficiency, emissions efficiency, and time of arrival for multiple trains operating over intersecting railroad networks, as they lack the ability to combine local train knowledge with global network knowledge in real-time, leading to variations in locomotive power and train dynamics.

Innovation Solution

A system and method that link train parameters such as fuel efficiency and load with network knowledge to adjust operating conditions dynamically, using a network optimizer and on-board trip optimizer to calculate and compare optimized parameters with current ones, and adjust train operations accordingly across intersecting tracks.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If train operators use the same notch setting based on previous operations, then operation simplicity is maintained, but fuel consumption varies significantly and cannot be minimized

Engineering Contradiction:

Improveoperating simplicityVSAvoidfuel consumption

Core Design Contradiction:

Ease of operationVSUse of energy by moving object

Solution Approach 1:

The system dynamically adjusts the notch setting based on real-time train parameters (weight, length, locomotive characteristics) and environmental conditions (track grade, weather, traffic) rather than using a fixed operator-determined setting. This dynamic optimization minimizes fuel consumption while maintaining operational simplicity through automated control.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback loops that continuously monitor actual fuel consumption, train performance, and network conditions, then adjust the optimal notch setting accordingly. This closed-loop control enables the system to learn from past operations and adapt to changing conditions, resolving the contradiction between operational simplicity and fuel efficiency.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If locomotives are provided based on available power and run history, then flexibility in power selection is achieved, but a large variation of locomotive power exists for individual trains

Engineering Contradiction:

Improvelocomotive selection flexibilityVSAvoidlocomotive power variation

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system changes the parameters used for locomotive selection from broad categories (available power, run history) to specific optimized parameters (exact power needed for the train's weight, track conditions, weather, and schedule requirements). This parameter refinement reduces power variation while maintaining flexibility in selecting from available locomotives.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If train operators determine operating speeds based on experience and terrain knowledge, then compliance with speed restrictions is achieved, but fuel efficiency cannot be optimized for each trip

Engineering Contradiction:

Improvespeed restriction complianceVSAvoidfuel efficiency

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system introduces an intermediary optimization layer between the operator and the locomotive control. This intermediary automatically calculates the optimal speed profile that satisfies all speed restrictions while minimizing fuel consumption, based on train parameters and environmental conditions, without requiring operator expertise in fuel optimization.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Productivity

If local train knowledge is combined with global network knowledge, then optimized system performance can be achieved, but system complexity increases

Engineering Contradiction:

Improvesystem performance optimizationVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system segments the optimization problem into local train-level optimization (fuel efficiency, speed profiling) and global network-level optimization (scheduling, routing, coordination). This segmentation allows each level to operate independently with its own knowledge base, reducing overall system complexity while achieving integrated optimization through standardized interfaces.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS8630757B2System and method for optimizing parameters of multiple rail vehicles operating over multiple intersecting railroad networks

Publication Date: 2014.01.14 TRANSPORTATION IP HOLDINGS LLC

AI summary

In a railway network a method for linking at least one of train parameters, fuel efficiency emission efficiency, and load with network knowledge so that adjustments for network efficiency may be made as time progresses while a train is performing a mission. The method includes dividing the train mission into multiple sections with common intersection points, and calculating train operating parameters based on other trains in a railway network to determine optimized parameters over a certain section. The method further includes comparing optimized parameters to current operating parameters, and altering current operating parameters of the train to coincide with optimized parameters for at least one of the current track section and a pending track section.