International Space Station power system requirements models and simulation

International Space Station (ISS) Payload Engineering Integration (PEI) organization adopted the advanced computation and simulation technology to develop integrated electrical system models based on the test data of the various sub-units to addressing specific power system design requirements. This system model was used to assess the power system requirements for assuring: (1) Compatibility of loads with delivered power, (2) Compatibility of loads with protective devices, (3) Stability of integrated system, and (4) Fault tolerance of the EPS and other loads. PEI utilizes EMA Design Automation PSPICE software for modeling and simulating the steady-state voltage, voltage transients, reverse current, surge current, source and load impedance, large signal stability, and fault characteristics of the integrated electrical systems based on the various sub-unit test data. PSPICE provides dynamic system modeling, simulation and data analysis for large-scale system integration. Modeling is valuable at the initial design stage since it enables experimentation, exploration and development without expensive and time-consuming modifications. However, with the complexity of the system interactions among all sub-units provided by various developers and suppliers, it is difficult to model an integrated system or verify that a system model meets all the requirements of its design specifications. In addition, the changes to system requirements demand frequent redesigns and reimplementation of many systems and sub-unit components. The benefits provided by modeling from conventional test data are: (1) Relatively low cost, (2) Identification of potential system integration problems early in the program, (3) Extrapolation of test data to verify system performance to cover the entire operating envelope, (4) Provide flexibility in development system integration modeling. The modeling of an integrated system based on system and sub-unit test data enable organizations to predict and improve system performance and to conduct efficient trade studies of system architecture. This comprehensive model can then be used directly in standard downstream processes such as rapid prototyping and risk mitigation in the product life cycle. The detailed modeling from conventional data will be discussed in the presentation.