Timetable Optimization for Electric Rail Energy Savings
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Solution Overview
Problem
The transportation industry faces challenges in reducing energy consumption in electric transportation systems, as conventional solutions like fly-wheels and super batteries are costly and inefficient, and existing timetables do not account for energy optimization.
Innovation Solution
A system and method that utilize a controller to synchronize braking and acceleration intervals of electric vehicles by shifting acceleration intervals in time relative to braking intervals, based on an energy model, to reduce energy consumption without additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional hardware solutions like fly-wheels or super batteries are used to reduce energy consumption, then energy conservation is improved, but system cost and complexity increase
Solution Approach 1:
The patent replaces mechanical energy storage hardware (fly-wheels, super batteries) with a software-based timetable optimization system. The controller synchronizes braking and acceleration intervals through computational algorithms, eliminating the need for additional mechanical energy storage devices while achieving energy conservation through regenerative braking optimization
Solution Approach 2:
The patent changes the timing parameters of vehicle operations by shifting acceleration intervals relative to braking intervals. This parameter optimization allows better synchronization of energy generation and consumption, reducing overall energy loss without requiring hardware modifications
2Loss of energy
If conventional hardware solutions like fly-wheels or super batteries are used to reduce energy consumption, then energy conservation is improved, but maintenance cost increases
Solution Approach 1:
The patent replaces mechanical energy storage hardware (fly-wheels, super batteries) with a software-based timetable optimization system. The controller synchronizes braking and acceleration intervals through computational algorithms, eliminating the need for additional mechanical energy storage devices while achieving energy conservation through regenerative braking optimization
Solution Approach 2:
The system uses existing vehicle infrastructure and regenerative braking capability to achieve energy conservation. By optimizing the timing of acceleration intervals to coincide with braking intervals of other vehicles, the system enables self-service energy recovery without requiring external maintenance-intensive hardware
3Ease of operation
If existing timetables are used without energy optimization, then operational simplicity is maintained, but energy consumption increases
Solution Approach 1:
The controller receives information about braking intervals from vehicles and uses this feedback to optimize acceleration intervals. The system continuously monitors and adjusts timetable parameters to synchronize energy generation and consumption, improving energy efficiency while maintaining operational simplicity through automated control
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively minimizes energy consumption by optimizing the use of regenerative energy, reducing the need for costly hardware solutions and improving the efficiency of energy transfer between vehicles, resulting in significant energy savings.
Implementation Method 1
The method includes generating an energy model using the controller, where the energy model is associated with the timetable and relates to how regenerative energy is transferred throughout the electric transportation line
Data Source
AI summary
Systems and methods for synchronizing two or more vehicles operating on an electric transportation line to optimize energy consumption. A controller is provided having a computer memory component storing a set of computer-executable instructions, a list of braking intervals, and a list of acceleration intervals for the vehicles. The controller also has a processing component configured to execute the set of computer-executable instructions to operate on the list of braking intervals and the list of acceleration intervals to minimize an energy consumption of the electric transportation line over a determined period of time by shifting acceleration intervals to synchronize with braking intervals. A dedicated heuristic greedy algorithm and an energy model are implemented in the controller as part of the computer-executable instructions to achieve the improved energy consumption.


