Electrical and thermal conceptual modelling of the propulsive battery for hybrid-electric regional aircraft

Electrical and thermal conceptual modelling of the propulsive battery for hybrid-electric regional aircraft

Imre Gellai, Austrian Institute of Technology

Air transport is one of the fastest-growing sources of greenhouse gas emissions, therefore hybrid electric propulsion is likely to play a more prominent role for regional aircraft with 40+ passengers to reduce its climate impact. The present study focuses on modelling the operating behaviour of the battery system for a future hybrid-electric regional aircraft using an advanced, high energy-dense lithium battery electrochemistry based on available measurement data. The battery operating behaviour is modelled with coupled equivalent electric circuit (EEC) and lumped thermal (LT) models. These empirical models are suited for cell-to-system modelling as they achieve good accuracy while keeping simulation time low. This paper aims at presenting a practical solution to modelling, parametrisation and simulation of the large propulsive battery for a hybrid-electric aircraft based using upcoming energy dense Li-metal battery electrochemistry. The coupled EEC- LT battery models were implemented in Dymola/Modelica using components from the AIT ElectricEnergyStorages (EES) library. Publicly available test data of an SES Li-metal prototype battery cell was used to parameterize the cell electrical and thermal cell models, iteratively extracting them from the measurements and optimising through comparisons with virtual measurements. The implementation, parameterization methodology, and validation of the 1D EEC and pseudo-3D LT battery model are discussed. The model can reproduce at system level the electrical and thermal operating behaviour of a large aeronautical propulsive battery under the relevant operating and environmental conditions. However, the battery concept as well as the underlying models need to be further refined to provide electrical and thermal behaviour at sub-pack and module level.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101006771 ORCHESTRA.