Internship / Master Thesis (State of Health Estimation via Digital Twin for Smart Batteries in Bus fleets)
Electrification Suite & Test Lab
17 December 2019
Open until filled
Project Title: State of Health Estimation via Digital Twin for Smart Batteries in Bus fleets
About TUMCREATE TUMCREATE is a research platform for the improvement of Singapore's public transportation, including the deployment of electric and autonomous mobility. Researchers from Technical University Munich and Nanyang Technological University join forces and are funded by Singapore’s National Research Foundation as part of the Campus for Research Excellence and Technological Enterprise (CREATE).
In TUMCREATE, over 100 scientists, researchers and engineers work together, led by Professors from the Technical University of Munich and Nanyang Technological University. The Mission of TUMCREATE is to seek the ultimate public transport system for the people of Singapore. Our innovative road transport solutions will provide high comfort and a positive travel experience, best protection of the environment and maximum benefit to the society and the economy.
TUMCREATE is a research company working on improving Singapore’s public transport system and making it more sustainable by electrifying it. Research area ESTL (Electrification Suite & Test Lab) is working on the electrification of public transport and its integration into the power system.
Innovative and electric public transportation solutions require reliable and highly efficient energy storage systems to overcome the drawbacks they are facing. These systems are facing immense challenges due to high charging currents and operation conditions. It is therefore crucial to investigate the behaviour of such battery packs under charging conditions as they may arise in electric busses.
This thesis has the focus of investigating the aging and therefore the State of Health (SoH) of Smart Cells in applications in bus fleets.
Fig 1: Smart Cell development platform
Objective and Tasks
The successful applicant is required to work independently on the following tasks:
Charge/Discharge Cycles: Investigation and implementation of different bus charge/discharge cycles into the existing cyber-physical co-simulation framework.
Cell Aging: Analysis of the recently implemented cell aging model and assessment of its viability.
Digital Twin: Implementation of a remote server-based mirror image of the smart battery pack (digital twin) to shift the computational load from the battery management system to high performance cloud computing to increase the prediction accuracy of the charge/discharge behaviour of the bus system.
Hardware & Embedded software: Transfer and evaluate the findings of the analysis to the physical smart cell demonstrator platform.
What we expect from you
Experience in programming in Python and C.
Embedded programming knowledge is highly desirable.
Excellent interpersonal skills and communication skills in both written and spoken English.
The ability to work with people from different backgrounds and cultures.
What we offer you
Exposure to the state of art research topics
An international and multidisciplinary working environment
Enquiries and How to Apply
Please send your complete application including cover letter, CV, university transcripts and degree certificates to firstname.lastname@example.org.