Operation through Traction Force Allocation
Energy losses in the operation of rail vehicles are a significant problem with both ecological and economic impacts. Reducing these losses is of great importance to improve energy efficiency and achieve the goals of the Federal Climate Protection Act (Bundesklimaschutzgesetz) by 2045. Hardware-based solutions are often associatedwith high costs and poor scalability. Software-based approaches offer a promising alternative to reduce energy losses without the need for expensive hardware upgrades.
This thesis presents a software-based method for reducing energy losses in the drivetrain of rail vehicles. The method is based on non-uniform traction force allocation on the driving axles to achieve optimal operating conditions for given velocity and total traction force. The challenge lies in the temperature dependencies of the loss functions and temperature changes caused by the chosen traction force allocation. The choice of traction force allocation at a given time thus has implications for the loss functions of all subsequent points in time.
The optimization of traction force allocations over a time series for a drive cycle represents the core of this work. Various optimization strategies based on sequential decision problem optimization are investigated to minimize energy losses for arbitrary drive cycles. The results of the strategies are compared with each other, as well as with methods, currently applied in the field. The comparison is made based on energy saving potential and computational effort. It is shown, that proposed methods can achieve improved energy savings compared to in-the-field methods under successful real-time computation, which, scaled to railway operations, offer significant ecological and economic benefits.
Room: 04.137, Martensstr. 3, Erlangen
Zoom-Meeting:
https://fau.zoom-x.de/j/68350702053?pwd=UkF3aXY0QUdjeSsyR0tyRWtLQ0hYUT09
Meeting-ID: 683 5070 2053
Kenncode: 647333