Advancing Cost Estimation for Regenerative Space Exploration

The development of regenerative life support systems (LSS) is a critical enabler for the long-term sustainability of crewed space missions. Accurate cost estimation for such a system is essential for effective planning and development. This paper examines three established cost estimation methodologies — Equivalent System Mass (ESM), the Advanced Missions Cost Model (AMCM), and PRICE-H TruePlanning — through a comparative case study of a hypothetical lunar habitat incorporating regenerative LSS. ESM, widely used in life support system trade studies, simplifies trade-offs by converting parameters such as power, volume, and crew time into mass equivalents. However, its focus on mass constraints neglects key considerations like cost, reliability, and long-term sustainability. AMCM, a lifecycle cost model, provides comprehensive financial estimates across all mission phases but relies heavily on detailed data, which is often unavailable during early design stages. This limits its predictive accuracy for novel systems like regenerative LSS. PRICE-H TruePlanning, a parametric hardware cost model, offers flexible and detailed cost predictions based on historical data and system specifications. However, its applicability to systems with dynamic processes and biological components remains limited. This study highlights the need for a next-generation cost estimation framework that integrates lifecycle cost analysis, dynamic system interactions, and sustainability metrics while keeping uncertainty and risks measured. Such a tool would enable more accurate and actionable cost predictions, aligning with the demands of sustainable space exploration. The findings aim to guide the development of a more advanced cost estimation tool for the next generation of space systems.