International projects
Material, Operating strategy and REliability optimisation for LIFEtime improvements in heavy duty trucks
Researchers (1)
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
23468 |
PhD Tomaž Katrašnik |
Energy engineering |
Head |
2021 - 2024 |
671 |
Organisations (1)
Abstract
MORELife addressed the call FCH-01-2-2020: Durability-Lifetime of stacks in heavy duty trucks. The project aims at the improvement of materials and operating strategies in order to enhance the durability and reliability for the specific needs of fuel cells in heavy duty truck application.The consortium is led by AVL List GmbH (AT) and furthermore consists of:•Mebius d.o.o. (SI),•Nedstack fuel cell technology BV (NFCT, NL), •University of Ljubljana (UL, SI),•Technical University Eindhoven (TUE, NL),•Technical University of Munich (TUM, DE) and •EKPO Fuel Cell Technologies (EKPO, DE)In MORELife, we will identify degradation issues based on real life application data provided by NFCT and EKPO. With these identified, both highly specific accelerated stress tests for the shortened test duration for lifetime verification as well as advanced degradation models will be developed by the UL and the TUM. Thereby, the needed improvements on the material and operation strategy level will be defined. The models will be based on existing and proven ones and will be used as a tool to predict material lifetimes based on material characteristics and AST persistence. These results will then be picked up by Mebius, a Slovenian SME producing MEAs based on novel catalysts (international patent). These innovations will be supported by TUE, contributing their expertise in porous materials with a focus on the correct selection of GDLs. Improved materials will be evaluated on different levels by the TUM, TUE, NFCT and ECPO. Starting on a single cell level, the aim is to test minimum in a short stack under degradation accelerating conditions as well as in application relevant environment. AVL will use the combined inputs to optimise and validate the operating conditions based on the improved materials. The results will be fed back into the models to validate the improvements compared to state-of-the-art materials and prove a predicted lifetime of 30.000 h.
