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To support research and analysis requirements in the development of future hybrid-electric drive systems, a flexible and efficient means of predicting the dynamic performance of large-scale multi-disciplinary systems prior to hardware trials is crucial. With the development of Distributed Heterogeneous Simulation (DHS), the technology now exists to enable this type of investigation. Previously, DHS was shown to allow the interconnection of component simulations running on a single computer or networked computers and developed using any combination of a variety of commercial-off-the-shelf software packages. The US Army is interested in using the Simplorer software product from Ansoft Corporation to model various subsystems that are incorporated with such vehicle system simulations. In this paper, the DHS technique is expanded to support the Simplorer software package; thus, allowing subsystem models developed using this tool to be interconnected to form a dynamic system simulation.

The optimal design of hybrid-electric vehicle power systems poses a challenge to the system analyst, who is presented with a host of parameters to fine-tune, along with stringent performance criteria and multiple design objectives to meet. Herein, a methodology is presented to transform such a design task into a constrained multi-objective optimization problem, which is solved using a distributed evolutionary algorithm. A power system model representative of a series hybrid-electric vehicle is considered as a paradigm to support the illustration of the proposed methodology, with particular emphasis on the power system's time-domain performance.