Telemetry Analysis of the Advanced Stirling Radioisotope Generator Using a Steady State Modeling Approach

Abstract

Stirling-based energy conversion technology has demonstrated the potential of high efficiency and low mass power systems for future space missions. The Advanced Stirling Radioisotope Generator (ASRG) was funded by NASA as a candidate for the next generation of radioisotope thermal to electrical converters for use by future NASA missions. Significant progress was made developing the Advanced Stirling Radioisotope Generator (ASRG), a 140-watt radioisotope power system prior to its cancelation in 2013. This is proposed to continue at the NASA Glenn Research Center (GRC) under Stirling technology advancement to support future Stirling-based power system development. It is in the context of this continued Stirling development that the work presented in this paper is presented. The purpose of this study was to determine if the telemetry read back from the ASRG would have been comprehensive enough to detect faults in the system. The control of the ASRG is handled by the ASC Controller Unit (ACU). Communication with ACU is done through a Mil Std 1553 bus interface. Commands from the spacecraft are sent to the ACU over this interface along with telemetry from the ACU back to the spacecraft. In flight, the telemetry provided by the ACU would have been our only means of diagnosing problems, validating models, and determining the health and status of the ASRG. The work presented in this paper attempts to validate whether the telemetry provided by the ACU would have been adequate enough to perform these functions. In addition to the telemetry over the 1553 bus, temperature telemetry within the GHA can be collected by the spacecraft This analysis was performed using a model based approach. A model of the ASRG was generated, faults were injected into this model, and the resulting telemetry was observed. The end result was a signature in the telemetry reflecting each of the modeled faults. A follow-on analysis was looking across the signatures to see if they were unique to a given fault. Additionally, we performed sensitivity studies using our model to determine how changes to input conditions affected the output parameters sent down in the telemetry. Our results showed unique signatures for each class of faults we modeled. In some cases faults within the class were not discernible from each other.