The research of heat generation and heat consumption in a conventional or ideal engine provides useful information about the regularities, character of the process and effectiveness of fuel combustion in any real engine that cannot be subject to experiments. This information is advantageous both in case of heat transformation effectiveness analysis and the development of means to improve already employed engine. The procedure (algorithm) of thermal processes modeling that take place in the internal combustion engines should be developed in a way that enables, according to measured pressure of working gases, to adequately reconstruct the course of heat generation, and vice versa, relying on a set course of heat generation, to veritably identify the change of gases pressure in the cylinder. Research aim – based on the principle of analogy and harmonious combination of induction and deduction to evaluate the possibility to represent in a formal way and theoretically generalize experimentally identified information about the regularities of heat generation and heat consumption processes development in Otto-cycle engines (engines of rapid internal combustion). As a rule in case of analytical identification of heat generation – heat consumption processes the index a of combustion capacity is defined in advance. The acquired information, however, demonstrates that there are more reasons to consider the value of the parameter m to be set in advance, rather than of the parameter a. The relation between values of heat emission maximal intensiveness and the time of its achievement in an empirical sense is seemingly parabolic. Theoretically, as it has been found out, it can be evidently treated as “fuzzy” hyperbolic. The fact that the engine’s idle run does not conform to the “hyperbolic” tendency manifests its considerable imperfection and does not contend against the theoretically substantiated regularity. Given, for example, that, it is possible to acknowledge that. While given, we will have to acknowledge that. Thus, if we assign in advance that we considerably limit the flexibility and preciseness of the identification algorism.
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