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The approach towards building hybrid vehicles has evolved with time and requirements. What used to be direct prototype building activity has moved towards building mathematical models before the actual prototypes are built. These models are utilized in optimizing component sizes, design and calibrate controllers and to estimate fuel economy improvements. If model results show promise, the actual prototype building activity is started. But modeling of vehicles still has a long way to go before aligning with businesses and aiding them as decision making tools on R&D investments. The reason being - the model building activity itself is prolonged and expensive. In addition to this, a lot of proprietary information such as component efficiency maps is required in order to build the model. In absence of these component level data, extensive testing becomes necessary where again vast amounts of resources have to be allocated.