Model-based software design is constantly becoming more important and thus requiring systematic model testing. Test case generation constitutes a critical activity that is cost-intensive, time-consuming and error-prone when done manually. Hence, an automation of this process is required. One automation approach is search-based testing for which the task of generating test data is transformed into an optimization problem which is solved using metaheuristic search techniques. However, only little work has been done so far applying search-based testing techniques to continuous functional models, such as SIMULINK STATEFLOW models. This paper presents the current state of my thesis developing a new approach for automatically generating continuous test data sets achieving high structural model coverage for SIMULINK models containing STATEFLOW diagrams using search-based testing. The expected contribution of this work is to demonstrate how search-based testing techniques can be applied successfully to continuous functional models and how to cope with the arising problems such as generating and optimizing continuous signals, covering structural model elements and dealing with the complexity of the models.