Optimization of light intensity in a controlled ecological life support system based on a knowledge- and data-driven modeling approach

A Controlled Ecological Life Support System (CELSS) is necessary for the long-term manned space exploration. A primary goal of plant research for CELSS is to generate the largest amount of edible biomass possible for the least amount of electrical energy used. A key factor for implementing crop production systems will be the development of energy-efficient lighting approaches. Artificial lighting is essential in plant production in a CELSS, and energy reduction is one of the most important problems to be solved. The objective of this study is to provide a scheme of light intensity control in order to determine the most suitable light intensity in CELSS for plant cultivation, which can minimum the energy consumption and meet the demand of plant production and oxygen for the crew based on a knowledge-and data-driven modeling approach. The results indicate that the optimization method can increase 11.5% light use efficiency compared to the previous experimental set. Moreover, the biomass production increases under the optimized light intensity. This approach provides a computational basis for life-time optimization of cabin design and experimental setup of CELSS.