Safety-critical applications require complete high-coverage testing, which is not always guaranteed by model-based test generation techniques. Recently, automatic test generation by model checking has been reported to improve the efficiency of test suites over conventional test generation techniques. This study introduces our novel tool SimAutoGen, which employs the model checking technique (as a formal verification technique) to derive test vectors from Simulink models of automotive controllers according to structural coverage metrics. Model checking based on test generation is challenging for two reasons. First, the input model to the model checker requires conversion into a formal language. Second, standard tools have limited ability to generate test vectors for large-scale Simulink models because the state-space explodes with increasing model size. Our proposed SimAutoGen avoids the first problem by expressing the properties to be verified, which correspond to a structural coverage metric, in the Simulink language. To solve the state-space explosion problem, we developed a new algorithm that slices the Simulink model into hierarchical levels.