Locomotive Consist Control for Real-Time Fuel-Efficient Isolation

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Solution Overview

Problem

Existing energy-management systems for trains do not effectively deploy locomotives in real-time based on predicted operating parameters, leading to inefficiencies in fuel consumption and operational performance when actual conditions deviate from planned routes.

Innovation Solution

An energy-management system that utilizes machine-learning algorithms to predict optimal locomotive deployment configurations in real-time by comparing benefits of different locomotive activation scenarios based on current operating parameters and route characteristics, allowing for dynamic adjustment of locomotive activation and deactivation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If traditional equal power distribution across all locomotives is used, then operational simplicity is maintained, but fuel efficiency deteriorates when selective deployment could optimize performance

Engineering Contradiction:

Improvefuel efficiencyVSAvoidcontrol system complexity

Core Design Contradiction:

Use of energy by moving objectVSDevice complexity

Solution Approach 1:

The system dynamically adjusts the deployment configuration of locomotives in the consist based on real-time operating conditions and predictive analytics. The energy management system continuously evaluates whether to deploy all addressable locomotives or only a subset, changing the operational state from static equal-power distribution to dynamic selective deployment, thereby optimizing fuel efficiency without requiring complex manual control adjustments

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The energy management system automatically determines optimal locomotive deployment configurations without requiring manual intervention from the train engineer. The system self-manages the complexity of evaluating operating conditions, predicting performance metrics, and selecting deployment strategies, thereby improving fuel efficiency while keeping the control interface simple for the operator

Inventive Principle:

Principle #25Self-service

2Use of energy by moving object

If plan-based energy management systems are used, then fuel efficiency is improved for predetermined routes, but adaptability deteriorates when actual conditions deviate from the plan

Engineering Contradiction:

Improvefuel efficiencyVSAvoidroute deviation adaptability

Core Design Contradiction:

Use of energy by moving objectVSAdaptability or versatility

Solution Approach 1:

The system continuously monitors actual operating conditions and compares them with the predetermined trip plan, using this feedback to dynamically adjust locomotive deployment strategies. When actual conditions deviate from the plan, the system receives feedback about the deviation and automatically modifies its deployment decisions, thereby maintaining fuel efficiency while adapting to unexpected route changes, terrain variations, or operational conditions

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The energy management system transitions from static plan-based control to dynamic adaptive control by continuously evaluating current operating conditions against the trip plan and adjusting locomotive deployment in real-time. This dynamic approach allows the system to maintain the fuel efficiency benefits of plan-based management while gaining the adaptability to handle route deviations and unexpected conditions

Inventive Principle:

Principle #15Dynamics

3Power

If all locomotives are deployed throughout the mission, then power availability is maximized, but fuel consumption increases

Engineering Contradiction:

Improvepower availabilityVSAvoidfuel consumption

Core Design Contradiction:

PowerVSLoss of energy

Solution Approach 1:

The system applies partial action by deploying only the necessary subset of locomotives required to meet the power demands of upcoming route sections, rather than deploying all locomotives throughout the entire mission. The energy management system predicts future power requirements based on route characteristics and operating conditions, activating only enough locomotives to satisfy anticipated demands, thereby reducing fuel consumption while maintaining adequate power availability

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system performs preliminary evaluation of upcoming route sections and power requirements before making deployment decisions. By predicting future operating conditions and power needs in advance, the system can proactively adjust locomotive deployment to match anticipated demands, ensuring power availability is maximized only when and where needed, thereby reducing unnecessary fuel consumption during low-demand sections

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12552425B2Systems and methods for deploying locomotives within a consist

Publication Date: 2026.02.17 PROGRESS RAIL LOCOMOTIVE INC

AI summary

An energy-management system of a train performs real-time assessment of operating parameters of the train and characteristics of a route using machine-learning algorithms. A consist management module within the energy-management system evaluates predictions of future performance by the train when different numbers of locomotives within a consist are inactive. Calculating and comparing operating benefits obtained from the predictions with respect to an upcoming distance, the consist management module identifies a number of locomotives to place in an isolation mode to provide efficient operation of the train. The number identified is provided to a driving strategy module for consideration in maneuvering the train over the upcoming distance.