Postdoctoral position in “Energy and Power Peak Control, enabled by Automatic Train Operation” in Zürich

100%, Zurich, fixed-term

Despite the excellent quality of railway systems in Switzerland, railway systems needs to increase their performances, to match the ambitious targets from policy and environmental goals. Punctuality, travel time, and energy efficiency should be kept at the same level, or even increased, to remain attractive, under increasing constraints. Pervasive automation, under the ideas of Automated Train Operations, has the potential to reach those goals

This project, funded by the Swiss national research fund, is to use pervasive sensing and controlling train trajectories as an enabler of more efficient power distribution at the level of networks, by reducing peaks. Currently, power peak computations are usually done together with (static) timetable planning; no stochastic conditions of delay or deviation from planned conditions is considered. On the vehicle side (traction equipment) special functions are implemented to help stabilize the electrical infrastructure regarding peak power. However, these functions have a negative influence on the tractive effort, and hence on the quality of the speed profile to be tracked by the ATO.

We aim to establish a computational framework able to assess the potential of ATO in realistic conditions, within the aim of energy and power peaks. This includes modelling, simulating and/or optimizing the following layers:

1. Traffic Management System (TMS) for monitoring and scheduling of train operations
2. The ATO Wayside which provides data interface to the train
3. The ATO on-board which interprets data from the wayside and operates the train accordingly
4. The traction equipment which provides tractive / braking force as determined by the ATO-on-board
5. The train protection system

All these components are running in a computationally efficient co-simulation environment coupled according to suitable interfaces, able to deal with high density railway networks operated using ATO.
The ultimate goal is to quantify the performance of the emergent behaviour of the two networks, i.e. transport (train movements) and power distribution (electricity peaks), based on the interaction of the decentralized control units onboard the vehicles. Within this framework, we investigate scenarios for peak power shaving, and identify systematic design procedures to ensure a system-wide optimum. A part of the results is envisaged to be implemented in pilot operations with industrial partners.

Moreover, this topic spans know how on mathematical optimization, ICT, computer science, process management, which currently practical implementation of control techniques, as well as interaction of multiple modules in complex systems. We envisage for tackling those challenges a new approach simulating current peak requirements, understanding requirements and effect of the individual parameters and component, and optimizing for a reduced peak power at the level of a single train or at multiple trains. The specific position is envisaged to result in control techniques which are close to implementation, which exploit the existing body of knowledge in energy efficient train control. This research will be as a cooperation of two research groups, Institute of Electric Power Systems at University of Applied Sciences and Arts Northwest Switzerland (FHNW, in Windisch AG) and transport system at ETH Zürich, and with planned involvement of multiple industrial partners. Moreover, this project is one in a large array of project showcasing potential of automation in mobility and energy systems. We expect regular interaction with research groups at universities, and railway companies in Switzerland and elsewhere, with and at relevant research groups at international level.

You ideally have a Doctoral Degree in transport sciences, management/ decision sciences, econometrics, statistics, computer science, energy modelling, or related fields. Your research track is consistent and shows a track record, or clear potential, for application of modelling simulation and control of energy in transport systems.

You are highly motivated, self-driven, with a clear research vision and academic ambition, you have excellent communication and writing skills (fluent spoken and written English is mandatory). Moreover, the following skills are expected of a promising candidate:

• Ability to program independently complex software
• Ability to model and consider complex systems described by modular approach; to critically review the gaps between industrial needs and academic potential
• Basic knowledge of mathematical optimization (MILP, IP, LP), and/or control sciences, in particular control techniques based on Model Predictive Control
• Basic understanding of railway vehicle control
• Team working and communication skills, also in German. Knowledge of German or similar languages is a plus; willingness to learn basic German within a short time horizon
• Know how of industrial process and ability/experience to collaborate with industrial partners
  

You enjoy working in an interactive international environment with doctoral students, post-docs and senior scientists, referring continuously to practical problems and solutions. This position will be available as of spring 2021 or upon agreement; the planned duration of the initial contract is one year, to be extended based on successful performance, for up to 2 years more. The workplace and collaboration with FHNW will determine a shared amount of time spent at both institutions, with one of the two schools taking the (formal) lead.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.