This 2-year research project (1.10.2019-30.9.2021) is carried out in collaboration by Turku University of Applied Sciences (TUAS) and LUT University (LUT) in Finland.
At TUAS, there are 3 distinct research groups participating in this project, namely:
- Smart Machines (SM) focusing in this project on developing high-fidelity simulation models and digital twins for EV systems, and applying these results for optimal control of electric powertrains.
- New Energy (NE) focusing in this project on developing high-power charging technology and heavy-duty battery systems for non-road mobile system (NRMS) applications.
- ICT Research Group (ICT) focusing in this project on experimental testing, characterization of battery cells and development of the battery management system (BMS), also addressing cyber-security issues.
At LUT University, there are 2 research groups participating in this project, namely:
- Electrical engineering (EE) focusing in this project on the analysis integrated components, developing modeling and control methods for the entire power train and the SoH of a battery.
- Mechanical engineering (ME) focusing in this project on structural modelling of the battery module, mechanical design and connection of battery cells into rail, and virtual model simulations.
The research project consists of two work packages, “Battery systems for heavy-duty applications” (WP1) and “Powertrains and battery system integration” (WP2).
The main goal of WP1 is the specification, design, development, commissioning and testing a battery system concept for Non-Road Mobile Machinery (NRMM) applications. As an application, the battery system is specifically implemented into the TUAS eRallycross race car. The battery system design is facilitated by physical simulations, with support from experimental validation studies and testing. The design process and the end results provide new engineering methods for heavy-duty battery system design and analysis.
The main goal of WP2 is model-based optimization of battery-driven NRMM applications, covering optimal operation and lifetime maximization, and also digital twins as they are operated online alongside the physical devices. To reach this goal, extensive development work is done on reduced-order models that can be used for simulating the entire powertrain (and beyond) while trading some physical model accuracy (as in WP1) to speed of simulation and ease of use. Through application of mathematical optimal control methods and simulation, new engineering knowledge and design utilities are sought, covering the entire powertrain.
Dissemination of the project results is achieved through technical meetings, technical reports, test result reports, scientific publications and, finally, an innovation seminar workshop event organized towards the end of the research project.
Funding from Business Finland is gratefully acknowledged.
For further information, please contact the respective project managers Eero Immonen (firstname.lastname@example.org) and Olli Pyrhönen (email@example.com).