Description
The objective of the activity is to develop, manufacture and test a power module with a new concept for Li-Ion battery management and with an advanced Electrical Power System Telemetry able to collect, store, retrieve and process large quantity of data related tothe Status of the Power System (SA, Battery, PCDU). A digital oscilloscope for the Built-In Test function and a function to analysein flight the degradation of solar arrays will be implemented in this new power module.Targeted Improvements:- Enabling automatisation of the assembly, integration and test; and in-flight anomaly investigations; and In-flight test data harvesting with a built-in test architecture.- To provide large quantity of data for Artificial Intelligence learning processDescription: One of the parameters used to trigger the satellite safe mode is the level of energy stored in the battery. However this parameter is an estimation and is typically set rather low, giving not much time to react. Monitoring the energy consumed by the different loads, and with an appropriate algorithm, could allow to immediately check if the satellite is on the path to enter the safe mode with a large time margin and thus the rundown time of the satellite would be reduced. The telemetry provided by Satellites is a reduced dataset, sub-sampled to a few hundred sample per seconds with a traditional design, which this is barely sufficient for anomaly investigations. Advanced Failure Detection Identification and Recovery (FDIR) as well as the learning phase of an AI (artificial intelligence) algorithm when applied to satellites and constellations, require a large quantity of data. Thus there is a need to increase the power moduleand battery health monitoring capabilities and sampling rate. Additionally, the inclusion of a Built-In Digital Oscilloscope would eliminate the need to have accessible test points, improving reliability and reducing the size of the boards. Also, the proposed activity will also benefit the solar array, for which it is hard to assess the degradation status while on flight. This intelligent module will implement a system to characterise the degradation in flight. In some terrestrial applications, "Built-in Test" functions are already implemented in industrial equipment. Often the equipment is so densely packed that there is no possibility to connect test probes, which means that telemetry data set includes already test data. Data need to be stored and then accessed when needed. A fast data link connection to a processor for onboard processing and/or to damp the data to mass memory must be established. For the battery health monitoring, the main development area will be the implementation of a continuous energy balance calculations considering instantaneous generated, stored and consumed power. The AI algorithm could be used to check if the balance is "sound" much earlier, thus detecting a performance drift far prior to failure. For the solar array monitoring, a sweep of the Current / Voltage curve ofthe solar array can be performed to understand the degradation status. Depending on the power system topology, several options can be used to perform the sweep while continuing with the operations in a nominal way.A power module breadboard, with battery advancedmonitoring and telemetry management block, will be designed, built and tested to demonstrate additional capabilities can be added to the power system.