An optimal battery sizing algorithm for future aircraft systems studies
Résumé
The path to climate-friendly aviation is a difficult way that needs to be traveled fast. A considerable and immediate drop of fossil fuels consumption is necessary to respect the Paris Agreement. Hybrid-electric and full-electric aircraft are part of the solution but developing a reliable and profitable hybrid-electric regional aircraft is a complex task. The European research project FUTPRINT50 aims at developing methods and tools to help to achieve this goal. The battery system is one of the key elements of aircraft electric architectures as it stores energy for propulsion and auxiliary systems. Among other challenges, optimal sizing (including mass, electric performances and aging) and safety are the two most difficult aspects to overcome. Herein, we propose a battery sizing algorithm, integrated to a plane level optimization tool (SUAVE), which, for a given power profile, optimizes battery systems sizing including all above cited parameters.
The sizing algorithm is based on a three steps strategy:
1.Optimal battery sizing for a given power profile:
Optimal series/parallel configuration that includes battery aging and nominal thermal management. At this step the total battery mass is estimated with a scalar coefficient. This is the standard approach for mass evaluation. It gives high uncertainty.
2.Optimal battery sizing including thermal runaway non propagation
We assure that in case of a thermal runaway of a cell, there is no propagation inside the battery pack. Two parameters are taken into account: cell-to-cell distance and thermal insulation material. Total battery mass is then refined a first time.
3.Optimal battery sizing including battery casing sizing. Based on actual experimental data, an analytical model of the battery casing helps to determine the optimal casing thickness. Besides Finite Element Analysis models based on a CAD battery casing under pressure, contributes to supports the analytical model through several safety module tests, including thermal runway of a cell inside the casing. A refined battery mass evaluation is then possible.
The reduced battery cell model is built up using several simulations of an electric equivalent circuit model of a cell (fixed chemistry, format and specifications) parametrized by testing. This model is then used to run an optimal battery sizing, finally taking into account performance targets (mass, volume, voltage, power), aging and safety.