A Range Prediction Method for All-Electric Aircraft by Capacity Discretization-Based Iterative Convex Programming

The emerging all-electric aircraft (AEA), which usually uses lithium-ion batteries (LIBs) as the energy supply unit, has constant mass but variable propulsive performance. The available voltage and power of an electrified propulsion system can vary regarding battery current and capacity consumption. The dynamic features distinguish AEA from its conventional counterpart driven by fossil fuel, thus necessitating the reconsideration of performance prediction. This article proposes a capacity discretization-based method to efficiently predict the range of AEA. The core idea is to discretize AEA states on capacity consumption nodes. At each node, the maximum horizontal flight distance is determined by numerical optimization and accumulated as the range. To guarantee computational tractability, the crude nonlinear programming problem (NLP) is convexified iteratively based on the previous solution. Compared to a benchmark Breguet equation, the proposed method reflects the influence of the voltage drop feature on the AEA range and improves the prediction precision by 15.22%. Further numerical cases show that the iterative convex programming method is superior to the nonlinear programming paradigm with computational time reduced by 77.60%.