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Internal combustion engines are still the main source of energy for transport. This situation will not change rapidly (but it will come irrevocably), hence there is a need for their further development. Development is also a need to reconcile a series of conflicting requirements. This, in turn, implies the need for very long-lasting and expensive research. The solution is a wider use of simulation methods. Here, however, there are barriers in the form of having to simulate several processes at the same time. These processes are most often of a probabilistic nature. Thus, there is a need for a different mapping of the engine in mathematical terms. This work presents such an approach based on the use of artificial intelligence. It turns out that the engine performance can be quite accurately mapped, so the method can be used more widely. However, the engine performance cannot be mapped by a mathematical model in the form of one equation. As a result of the work, it was possible to state that each engine parameter should be simulated by one model-as a equation in specific form (different from other). If the engine is treated as a system then Consequently it can be assumed that each of the object's (engine) responses is described by a specific for this equation form but content the same influencing factors. Internal combustion engine model must be multi equational .