An Efficient Method for Simulating Complex Systems with Switching Behaviors Using Hybrid Bond Graphs

Accurate and efficient modeling and simulation approaches are essential for design, analysis, diagnosis, and prognosis of complex embedded systems. This paper presents an efficient simulation scheme for systems with mixed continuous and discrete behaviors. We model hybrid systems using hybrid bond graphs (HBGs), a multi-domain physics-based modeling language that incorporates local switching functions that enable the reconfiguration of energy flow paths. We exploit the inherent causal structure in HBGs to derive hybrid simulation models as reconfigurable block diagram (BD) structures. Considerable computational savings are achieved during simulation by identifying fixed causal assignments when the simulation model is derived. Fixed causal assignments reduce the number of possible computational structures across all mode changes, and this leads to an overall reduction in the complexity of the BD simulation models and in their reconfiguration procedures. This approach has been implemented as a software tool called the MOdeling and Transformation of HBGs for Simulation (MOTHS) tool suite. Simulation models of an electrical power distribution system that includes a fast switching inverter system are derived using the MOTHS tool suite, and experimental studies on this system demonstrate the effectiveness of our approach.