Rail Vehicle Driving Strategy With Horizon-Based Power Scheduling
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Solution Overview
Problem
Existing methods for optimizing the driving strategy of rail vehicles with energy storage and generation devices are inefficient due to high calculation effort and failure to account for external influences, leading to suboptimal fuel cell performance and battery aging.
Innovation Solution
A method that divides a route into sections or 'horizons' to determine a constant energy output rate for the energy generation device, maintaining the energy storage device's state of charge within an optimal range, balancing fuel cell efficiency and battery longevity through simulation and measurement, while adjusting for unforeseeable factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative calculation methods are used to determine optimal power distribution between fuel cell and battery, then the optimization accuracy is improved, but the computational effort increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-defining discrete operating points for the fuel cell and battery based on their respective optimal operating ranges before the actual optimization calculation. This pre-structuring of the solution space allows the iterative algorithm to converge faster while maintaining accuracy, as it searches within predetermined boundaries rather than exploring the entire continuous parameter space.
Solution Approach 2:
The patent transforms the continuous power distribution optimization problem into a discrete parameter selection problem by defining specific operating points (e.g., 30%, 60%, 90% of maximum power) for both fuel cell and battery. This parameter discretization reduces the computational complexity of the iterative optimization while preserving the essential trade-offs between different operating strategies.
2Use of energy by moving object
If the fuel cell operates at constant power level to maximize efficiency, then the fuel cell efficiency is improved, but the battery state of charge range becomes restricted
Solution Approach 1:
The patent applies dynamics by making the power distribution between fuel cell and battery adaptive rather than static. The system dynamically adjusts the fuel cell operating point and battery power level based on real-time conditions (vehicle power demand, battery state of charge, environmental factors) while keeping the fuel cell within its optimal efficiency range. This allows the battery SOC to vary within acceptable bounds without forcing the fuel cell out of its optimal operating window.
Solution Approach 2:
The patent implements feedback control where the actual battery state of charge and fuel cell operating point are continuously monitored and used to adjust the power distribution strategy. When battery SOC approaches the boundaries of the acceptable range, the system provides feedback to modify the fuel cell power level or charge/discharge rate, ensuring both fuel cell efficiency and battery adaptability are maintained.
3Duration of action of stationary object
If the battery operates within a narrow state of charge range to extend lifespan, then the battery lifespan is improved, but the flexibility in power distribution is reduced
Solution Approach 1:
The patent applies preliminary action by pre-establishing the optimal state of charge range for the battery based on its technical specifications and operational requirements. This predefined SOC window (e.g., 20%-80% or 30%-70%) is used as a constraint in the power distribution optimization, ensuring the battery operates within lifespan-extending boundaries while the system explores all feasible power distribution options within these bounds.
Solution Approach 2:
The patent transforms the power distribution problem into a constrained optimization where the battery SOC is treated as a parameter with defined bounds. The optimization algorithm adjusts other parameters (fuel cell power level, timing of charge/discharge events) to maintain battery SOC within the optimal range, thereby preserving battery lifespan while achieving near-optimal overall system efficiency.
Data Source
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AI summary
A method, in particular a computer-implemented method, for optimizing the driving strategy of a rail vehicle with an energy generation device and an energy storage device comprises the following steps: Dividing a route to be traveled into at least one, in particular several, track segments, combining the at least one track segment into at least one horizon, determining an energy requirement of the at least one horizon, determining a substantially constant energy output rate of the energy generation device of the rail vehicle for the horizon, at which the state of charge of the energy storage device for the horizon lies within an optimal range.