Qualitative models of dynamical systems fall into non-causal or causal approaches. The non-causal approach is widely used in part because traditional physics describes phenomena by means of symmetric functional relations. It supports the idea that causality can be ignored or inferred from the model itself. Nevertheless, when people explain how things work, they use causal relations. Representing causality explicitly makes it possible to take advantage of exogenous knowledge necessary for understanding the phenomena and supporting self-explanatory simulation. The basic concepts used in both approaches, in addition to the representation formalisms and algorithms, are discussed in the light of recent works performed by teams affiliated to the MQ&D research group in France.