Development of an Engineered Simulation Environment for eVTOL Battery Pack Optimization

Advanced air mobility (AAM) is a broad concept that allows consumers to access on-demand air mobility, cargo and package delivery, healthcare applications, and emergency services via a multimodal transportation network that is integrated and connected. Newly developed electric Vertical Takeoff and Landing vehicles (eVTOL) are the best candidates to serve the AAM market demand. Several well-known aircraft manufacturers, including Airbus, Boeing, and Bell, as well as new startups, have begun developing flying prototypes of electric Vertical Takeoff and Landing vehicles (eVTOL) all over the world. The realization of the aviation dream depends on public perception of its safety, similar to how people currently view flying on a commercial airplane. That is the Federal Aviation Administration’s (FAA) responsibility to ensure that this new generation of air taxis maintains the high level of safety that characterizes modern aviation. Batteries, the energy sources, are the backbone of eVTOLs. With the rise of electric vehicles (EV), the last decade has seen remarkable advancements in battery technology, particularly in Li-ion batteries (LiBs). However, when compared to EVs, eVTOLs have distinct operating profiles and, as a result, drastically different battery requirements. Research on eVTOL batteries is still limited, only a few papers have examined eVTOL battery performance metrics [1,2] and experimental work has not been reported until recently [3]. To ensure safe and dependable operations, eVTOL battery packs must provide adequate electrical power for mission requirements while maintaining pack health and cycle life over hundreds of missions. Nevertheless, because of the magnitude of eVTOL battery pack stored energy, cost, and explosive nature of packs undergoing thermal runaway, testing the performances over time of different pack design configurations is impractical and inefficient. On the other hand, the use of a simulation model will allow many scenarios to be tested virtually prior to physical testing and manufacturing [4]. While different simulation models regarding EVs are widely present in literature [5-7], in the area of eVTOL, the research is in an embryonal phase. Generating accurate battery pack degradation models for this new technology is challenging especially due to the deficiency of experimental data to validate the models. Harrison et al [5] described the process of developing a physical model to represent the battery pack of an eVTOL vehicle from a multi-physics standpoint by integrating the battery pack's electric, thermal, and fluid physics domains to predict realistic pack performance over a flight profile. Bills et al [8] used a physics-informed battery performance model based on machine learning to break the commonly observed accuracy-computing cost trade-off. Liu et al [9] analyzed a simplified electrothermal model that explicitly considers the effects of the aircraft's operating temperature and payload in the simulation. Brenner et al [10] provided eVTOL analysis capabilities that allow for improved designs in terms of mission range, operational capabilities, and flight safety. However, it appears that there is a lack in the literature regarding physics-based electrochemical modeling of battery pack integrated into an eVTOL simulation model. The proposed study successfully used a physics-based model technique to predict the degradation of a generic eVTOL battery pack. The integration of electrochemical, electrical, and mechanical aspects of technology into a unified model was achieved with the aid of GT-SUITE software. This simulation software is extensively employed in multiple industries and provides engineers with diverse functionalities to design, analyze, optimize, and troubleshoot a broad range of systems, subsystems, and components. Initially, a comprehensive model for an eVTOL system was developed. Next, the battery pack of the eVTOL was modeled, using a Pseudo-2-Dimensional (P2D) physics-based model, and analyzed using GT-AutoLion software, which is a part of the GT-SUITE package. The focus of the investigation was to identify the degradation mechanisms that impact the energy storage system during real-world usage scenarios. Finally, a comparative analysis was performed between two different battery pack typologies to evaluate their respective performance and efficiency characteristics. The findings of this study provide valuable insights into the design and optimization of battery packs for eVTOL systems, which can aid in the development of more reliable and efficient energy storage solutions for the aerospace industry.