In recent years, the number of motor vehicles in circulation has increased in proportion to Brazil’s economic growth, resulting in an increase in emissions of toxic gases from combustion, such as nitrogen oxide, particulate matter, carbon dioxide and volatile organic compounds, among other polluting compounds. This type of pollution has its impacts potentiated in large cities, accumulating due to the configuration of streets and buildings in large urban centers, and can even penetrate indoor environments, having harmful effects on the health of residents. To minimize the emission of these gases, catalytic converters can be used in the vehicle exhausts. Catalytic converters are a promising technology used to reduce exhaust emissions from the engine. In this context, this paper presents an overview of the emission of toxic gases by heavy transport powered by diesel oil and the influence of the use of automotive catalysts in reducing the emission of toxic gases. Additionally, a proposal for monitoring the useful life of automotive catalysts is presented through an electronic sensing system, which makes it possible to determine the catalyst efficiency and the appropriate point for its reactivation or replacement.

This paper presents the results of studies on reducing the amount of vibrations in different frequency ranges generated by a combustion engine through the use of different types of engine mounts. Three different types of engine supports are experimentally and numerically analyzed, namely an elastomeric engine mount, an elastomeric engine mount with a hydraulic component and standard decoupling, and an elastomeric engine mount with a hydraulic component and a modified decoupler—with this engineering design being a novelty in the literature. Experimental tests that considered different excitation frequencies were performed for the three types of engine mounts. Experimental data for stiffness and damping were used to obtain nonlinear mathematical models of the two systems with hydraulic components through the use of an Artificial Neural Network (ANN). For the results, all of the mathematical models presented coefficients of determination, R², greater than 0.985 for both stiffness and damping, showing an excellent fit for the nonlinear experimental data. Numerical results using a quarter-car suspension model showed a large reduction in vibration amplitudes for the first vibration model when using the hydraulic systems, with values ranging between 48.58% and 66.47%, depending on the tests. The modified system presented smaller amplitudes and smoother behavior when compared to the standard hydraulic model.