Complex systems modeling and simulation are critical in many industrial and research fields, specifically to predict, prove, verify, and understand the behavior of cyber-physical systems. The diversity of variables in a system creates complexity and a need for more efficient modeling and simulation methods. In the case of hybrid systems, the heterogeneity of the discrete and continuous parts makes these tasks more challenging, adding the necessity to manage different types of variables and trajectories separately. Qualitative reasoning offers a paradigm to study the behavior of such systems with a high level of abstraction, trading precision and specificity against generality and formalism. In some situations, this paradigm can be preferred to numerical analysis, especially in the upstream study of a system in its design phases when information and knowledge about its components are incomplete. However, the different representations and contexts of such systems create a significant obstacle to defining a general methodology for applying qualitative reasoning and modeling to every case. This article proposes a method and presents a tool prototype to unify different qualitative reasoning techniques on complex cyber-physical systems described by polynomial ordinary differential equations. Both are illustrated in case studies to highlight their benefits. It also presents some possibilities of generalization to systems that do not satisfy the criteria currently required by our approach.