Rail Vehicle Speed Profile Optimization for Lower Energy Use
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing solutions to reduce energy consumption in rail vehicles, such as replacing components with lower energy requirements, are costly and provide only small reductions, failing to significantly impact overall energy consumption.
Innovation Solution
A rail vehicle optimization system that generates optimized speed profiles and configuration parameter sets based on real-time data from sensors, kinematics, track, and component conditions to minimize energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If components are replaced with new components having lower energy consumption requirements, then energy consumption is reduced, but research and development costs and acquisition costs increase significantly
Solution Approach 1:
The patent changes operational parameters (speed profiles, configuration parameters) of existing components rather than replacing components themselves. The optimization system dynamically adjusts these parameters to minimize energy consumption while avoiding the high costs of developing new components.
Solution Approach 2:
The patent creates a virtual model (digital twin) of the rail vehicle that replicates its behavior and energy consumption characteristics. This virtual copy is used for optimization simulations, allowing energy reduction strategies to be tested and implemented without physical component replacement.
2Use of energy by moving object
If components are replaced with new components having lower energy consumption requirements, then energy consumption is reduced, but acquisition costs increase significantly
Solution Approach 1:
The patent achieves energy reduction by optimizing operational parameters of existing components through an optimization system, avoiding the need to acquire new expensive components while still achieving significant energy consumption reduction.
Solution Approach 2:
The virtual model allows the system to simulate and optimize energy consumption without requiring physical acquisition of new components, thereby avoiding acquisition costs entirely.
3Ease of manufacture
If existing components are used without optimization, then research and development costs are minimized, but energy consumption remains high
Solution Approach 1:
The optimization system continuously monitors actual energy consumption and component behavior, comparing it with simulated optimal behavior from the virtual model. This feedback loop enables real-time adjustments to speed profiles and configuration parameters to minimize energy consumption of existing components.
Solution Approach 2:
The virtual model is pre-trained with historical data and component characteristics before actual operation. This preliminary preparation allows the optimization system to provide immediate energy-saving guidance without requiring real-time complex calculations or component modifications.
4Use of energy by moving object
If a detailed optimization system is implemented to minimize energy consumption, then energy efficiency is improved, but system complexity increases
Solution Approach 1:
The patent creates a simplified virtual copy (digital twin) of the rail vehicle that captures essential energy consumption characteristics without replicating every physical detail. This virtual model enables optimization while keeping the system manageable in complexity.
Solution Approach 2:
The optimization system is divided into modular components: virtual model creation, training module, optimization algorithm, and control interface. This segmentation allows each module to be developed and optimized independently, reducing overall system complexity.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A rail vehicle (10) including a plurality of components (14) and an optimization system (20) coupled to the components (14) and configured to receive input data and, based on the received input data, generate a plurality of candidate speed profiles and select, among the candidate speed profiles, an optimized speed profile for driving the rail vehicle (10), the optimized speed profile minimizing the energy consumption of the rail vehicle (10). The input data comprise: kinematics data (D1) determined in real-time and indicative of real-time kinematics information of the rail vehicle (10); track data (D2) indicative of a path to be travelled by the rail vehicle (10); constraint data (D4) indicative of constraints for the functioning of the rail vehicle (10); and component condition data (D3) comprising operating parameters determined in real-time and indicative of the real-time functioning of the components (14).