Abstract

There is a growing interest in the sustainability of the aviation industry sector over the past years due to the environmental issues associated with traditional aviation engines. Electric and hybrid aircrafts are considered promising technologies for reducing fuel consumption and enhancing system efficiency [1]. However, electrical energy storage systems require a higher capacity-to-weight ratio than today’s Li-ion batteries to fulfil the high demands in this area. Safety restrictions imposed by liquid electrolytes motivate the development of next-generation chemistries, such as oxide-based all-solid-state batteries (ASSB) for aviation, which have non-flammable electrolytes [2]. This option is investigated in the context of the IMOTHEP European project that aims at identifying promising hybrid aircraft configurations and studying the associated technology. However, the major drawbacks of oxide-based solid electrolytes are weak contact between electrode and electrolyte interface, low mechanical flexibility, and high density, which limit their use for high gravimetric energy density applications. To mitigate the aforementioned concerns, the solid polymer composite electrolytes approach could be applied, where oxides are mixed with polymer electrolytes [3].Designing an optimum cell without ion transport limitations using experimental investigations is time- as well as resource-intensive due to the large number of iterations in production and evaluation required to achieve a well-performing design. Physics-based modelling is able to create a platform that can directly assess the impact of cell structure on battery performance and provide knowledge concerning limiting processes within the cell. Therefore, we here present the first study that combines a pseudo-two-dimensional model for the model-assisted evaluation of Li-ASSB with various hybrid electrolytes and single-ion conductor electrolytes with an evolutionary algorithm to identify optimum cell designs to reach a higher gravimetric energy density (see Fig. 1-a). To this end, we first compared the performance of several hybrid electrolytes with their experimental properties, to identify which electrolyte performs well with present technology and which has the potential to become an attractive alternative in the future.Our findings reveal that based on available ASSB technology, single ion-conducting electrolytes cannot achieve a higher gravimetric energy density than hybrid electrolytes at low current rates due to their high density, as shown in Fig. 1-b. ASSB based on 12.7 vol% of garnet Li6.4La3Zr1.4Ta0.6O12 (LLZTO) is the best option based on present manufacturing constraints. Furthermore, our study revealed that hybrid electrolytes based on 10 wt% of Li1.3Al0.3Ti1.7(PO4)3 (LATP) could be promising for future aircraft if researchers succeed to decrease its electrolyte thickness and chemical stability in contact with lithium metal anode. Further, sensitivity analyses enabled us to identify that the cathode thickness and volume fraction of cathode materials are critical parameters for the cell design of ASSB. Therefore, we applied a global optimisation to enhance gravimetric energy density by changing these two electrode design parameters. After optimisation, gravimetric and volumetric energy densities of 618 Wh kg-1 and 1251 Wh L-1 for 0.1C discharge are achieved, respectively, indicating that the cell with the optimal electrode design could meet the mission demand in the aviation industry with a gravimetric energy density of 500 Wh kg-1 and volumetric energy density of 1000 Wh L-1.In conclusion, the findings of this study show that our physics-based modelling in conjunction with an optimisation algorithm predicts the optimal composition of ASSB for a given constraint and thus supports the time- and cost-effective development of batteries that fulfil mission requirements, e.g. in the aviation sector.This work is conducted in the frame of the project IMOTHEP (Investigation and Maturation of Technologies for Hybrid Electric Propulsion), which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 875006 IMOTHEP.

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