Speaker
Description
Optical instruments in space payload systems face challenges in maintaining minimal temperature gradients to prevent optical bench deformation, which can impair optical paths due to component sensitivity. The heat generated by payload components and processor units adds to the overall thermal load. To address this, a multi-processor system can distribute generated power, or heat, by shifting tasks among processor units. Further, other subsystems, e.g. thermoelectric coolers, are controlled by the processor units. Despite introducing heat points, the control of redundant subsystems offers design freedom for optimizing the thermal distribution on a payload platform.
By utilizing the flexibility in subsystem control, a multi-processor system can minimize temperature gradients. Model predictive control, informed by orbit temperature patterns, can enhance thermal management. The Processor Layout Utilization for Thermal Optimization (PLUTO) project is a co-funded project by the Bavarian Ministry, led by Engineering Minds Munich. It aims to develop thermally optimized layouts for payload subsystems and processor units, using intelligent control based on orbit temperature data. A demonstrator payload with three interconnected processor modules will verify the thermal model, with testing scheduled for end of 2024.
This collaborative project between the space industry and universities seeks to improve thermal management in space payload systems, enhancing the performance of optical instruments.
