Cylinder deactivation is a fuel economy improvement technology that has attracted particular attention recently. The currently produced cylinder deactivation engines utilize fixed-type cylinder deactivation in which only a fixed number of cylinders are deactivated. As fixed-type cylinder deactivation has some shortcomings, variable-type cylinder deactivation with no limit on the number of deactivated cylinders is under research. For variable-type cylinder deactivation, control is more complicated and production cost is higher than fixed-type cylinder deactivation. Therefore, it is necessary to select the cylinder deactivation control method considering both advantages and disadvantages of the two control methods. In this study, a fuel economy prediction simulation model was created using the measurement data of various vehicles with engine displacements of 1.0–5.0 L. The fuel economy improvement of fixed-type cylinder deactivation was compared with that of variable-type cylinder deactivation using the created simulation. As a result of examining the fuel economy improvement of the test vehicle in the FTP-75 driving cycle, the improvement was 2.2–10.0% for fixed-type cylinder deactivation and 2.2–12.8% for variable-type cylinder deactivation. Furthermore, the effect of the engine load on fuel economy improvement under cylinder deactivation and the effect of changes in engine control were examined via a simulation.
Because of emissions of exhaust gases, global warming is proceeding, and air pollution has increased. Thus, many countries are manufacturing eco-friendly vehicles, including electric vehicles. However, the range of electric vehicles is less than the range of internal combustion engine vehicles, so electric vehicle production is being disrupted. Thus, it is necessary to analyze the energy flow of electric vehicles. Therefore, to analyze energy flow of electric vehicles, this study suggested an energy flow structure first, then modeled the energy flow of the vehicle, dividing it into battery, inverter and motor, reduction gear and differential, and wheel parts. This study selected a test vehicle, drove in urban driving conditions and measured data. Then, this study calculated energy flow using MATLAB/SIMULINK in real time, and calculated and analyzed energy loss of each of the vehicle’s parts using the calculated data.
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