| Summary: | The power requirements for future spacecraft power systems will be on the order of a few hundred kilowatts to a few megawatts. Because of these power levels, a high-voltage, high-power distribution subsystem may be utilized to transmit power from the source to the different loads. Using current state-of-the-art power conditioning electronics, complex series and parallel configurations will be required at the interface between the source and the distribution subsystem and between the distribution subsystem and the loads.
The dynamic response of such a spacecraft power system may be obtained using a general purpose program such as SPICE2. However, for large and complex spacecraft power systems, the input file will be large and complex with correspondingly large computation times. As an alternative, the spacecraft power system can be considered as an interconnection of modular components. Each component is treated as a two-port network, and a state model is written with the port voltages as the inputs. The state model of each component is solved using the state transition matrix and assuming that the port voltages are . clamped for each time step. This calculation proceeds as if all two-port networks are decoupled. After the state variables have been updated, the inputs to all components are calculated using network analysis principles. The solution procedure alternates between solving the dynamic model of all components and the network equations for the component inputs.
The modular state variable approach and SPICE2 are compared using two example systems. This comparison shows the advantages of the modular state variable approach. First, for the modular state variable approach the system is considered as an interconnection of modular components. In SPICE2, the system is treated as an interconnection of circuit elements. As a result, the system description for large and complex spacecraft power systems is much _ larger and more complex than a modular state variable description. Secondly, the modular state variable approach requires less CPU time than SPICE2. For one of the example systems presented here, the modular state variable approach uses one-twentieth of the CPU time used by SPICE2. === Ph. D.
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