Credibility-Based Multidisciplinary Design Optimization of Hybrid and Fully Electric Aircraft

Aircraft designs for future electric aircraft often have large discrepancies in the underlying assumptions for highly influential design parameters. More optimistic assumptions on these parameters could result in better aircraft performance but include higher risks in the realization of the design in the defined timeline. In this work, the novel concept of design credibility is introduced to be used for quantifying the effect of assumptions on the underlying technologies on the design performance and the risks. For a range of highly important parameters, probability curves have been created that can predict a range of assumed future performance by 2035. A credibility-based multidisciplinary design optimization framework is created, which evaluates the maximum achievable mission ranges for hybrid electric aircraft under credibility constraints. The optimizations are performed using a surrogate-based global optimization routine, the efficient global optimization. With the full framework, the multiple aircraft designs are optimized under a range of credibility limits to create range-credibility Pareto curves. The results show that battery gravimetric energy density is the most dominant factor for the optimization. Motor and airframe parameters have a smaller effect on the achievable range. Their influence on the optimal design depends on the desired credibility level. For high credibilities, the motor is found to be more relevant. For low credibilities, airframe technology improvements are dominant. The shape of the underlying credibility distributions of secondary parameters has a strong effect on their relevance for the optimal configuration.