Train Trip Optimization Using Signal Data
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Solution Overview
Problem
Train operators face challenges in optimizing fuel consumption and emissions while adhering to schedule constraints due to numerous variables affecting locomotive performance, including railcar composition, weather, and track conditions, without extensive experience or real-time data.
Innovation Solution
A system and method that determine travel parameters of railway vehicles and other vehicles on the network, using a processor to create a trip plan with a speed trajectory responsive to track occupation and operational criteria, optimizing fuel use and emissions by adjusting tractive and braking efforts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If an operator manually controls the locomotive based on experience, then safe operation and schedule compliance are achieved, but fuel consumption cannot be optimized due to multiple variable factors
Solution Approach 1:
A trip optimization system acts as an intermediary between the operator and the locomotive control systems. The system receives multiple input variables (railcar composition, weather, track conditions, signal information), processes them through algorithms, and generates optimized tractive and braking effort recommendations that the operator can follow to achieve fuel optimization without manually managing all variables
Solution Approach 2:
The patent replaces manual operator judgment and experience-based control with an automated computerized optimization system that uses algorithms to calculate optimal operating parameters. This substitution enables precise fuel optimization by processing multiple variables simultaneously that would be difficult for a human operator to weigh and balance in real-time
2Use of energy by moving object
If the operator adjusts tractive and braking efforts to optimize fuel consumption, then energy efficiency improves, but it becomes difficult to account for multiple variables such as railcar composition, weather, and track conditions
Solution Approach 1:
The trip optimization system serves multiple functions simultaneously: it collects data from various sources (track circuits, signals, weather stations), processes multiple variable types (railcar weight, track grade, weather conditions), performs optimization calculations, and provides guidance to the operator. This multi-functional integration allows the system to handle the complexity of multiple operating factors through a single unified platform
Solution Approach 2:
The optimization system acts as an intermediary that absorbs and processes the complexity of multiple variables. Instead of requiring the operator to directly manage each variable (railcar composition, weather, track conditions), the system intermediates by collecting, integrating, and processing all these factors into unified optimization recommendations
3Use of energy by moving object
If real-time optimization is implemented using signal information and travel parameters, then fuel savings of around 7.6% are achieved, but the system complexity and data processing requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-collecting and storing signal information, track data, and operational parameters before the actual trip optimization is needed. Travel parameters and signal states are gathered in advance, allowing the optimization algorithms to process this pre-prepared data efficiently during the trip without requiring complex real-time computation under operational stress
Data Source
AI summary
A system is provided for operating a railway network including a first railway vehicle during a trip along track segments. The system includes a first element for determining travel parameters of the first railway vehicle, a second element for determining travel parameters of a second railway vehicle relative to the track segments to be traversed by the first vehicle during the trip, a processor for receiving information from the first and the second elements and for determining a relationship between occupation of a track segment by the second vehicle and later occupation of the same track segment by the first vehicle and an algorithm embodied within the processor having access to the information to create a trip plan that determines a speed trajectory for the first vehicle. The speed trajectory is responsive to the relationship and further in accordance with one or more operational criteria for the first vehicle.