Analysis of Optimal Thrust to Mass Ratio Requirement for Maximizing Payload Mass of Lunar Landing Mission

TL;DR

The paper extends classical lunar descent optimization by adding engine mass and ISP penalties to identify a Pareto-optimal thrust configuration that maximizes payload delivery. By reformulating the problem to include multiple-engine or throttling scenarios, it uncovers a global maximum in effective payload as a function of thrust, with an acceleration-scale optimum around 3 m/s^2. Simulation results across Case 1 and Case 2 parameters illustrate the trade-offs and provide design guidance for maximizing cargo delivery while ensuring a feasible descent trajectory. The approach offers a practical framework for early-stage lander sizing and propulsion-system decisions in sustained lunar operations.

Abstract

Recent successful lunar landing missions have generated significant interest among space agencies in establishing a permanent human settlement on the Moon. Building a lunar base requires multiple and frequent landing missions to support logistics and mobility applications. In these missions, maximizing payload mass defined as the useful cargo for human settlement is crucial. The landing mass depends on several factors, with the most critical being the maximum thrust available for braking and the engine's specific impulse (ISP). Generally, increasing engine thrust for braking reduces flight duration and, consequently, gravity losses. However, higher thrust also introduces trade-offs, such as increased engine weight and lower ISP, which can negatively impact payload capacity. Therefore, optimizing the descent trajectory requires careful consideration of these parameters to achieve a global solution that maximizes payload mass. Most existing research focuses on solving optimal control problems that minimize propellant consumption for a given thrust. These problems are typically addressed through trajectory optimization, where a minimum-fuel solution is obtained. The optimized trajectory is then executed onboard using polynomial guidance. In this paper, we propose an outer-layer optimization approach based on a Pareto-optimal solution. This method iterates on the maximum available thrust for descent trajectory optimization while incorporating a loss function that accounts for engine mass and ISP losses. By applying this approach, we identify a globally optimal solution that maximizes payload mass while ensuring an optimal landing trajectory.

Figures (9)

• Figure 1: Spherical Coordinate Frame for dynamics
• Figure 2: Mass and ISp of engine as function of maximum throttling
• Figure 3: Altitude Profile
• Figure 4: Vertical Velocity Profile
• Figure 5: Downrange profile