Search Results

This paper describes how use of multi-objective optimization of pulsating noise and backpressure improved an exhaust silencer for diesel drive equipment. Low frequency pulsating noise and backpressure were simultaneously predicted using one-dimensional fluid dynamics and acoustic analysis by BEM. In addition, an experiment was done to investigate the relation between high frequency noise including flow-induced noise and the dimensions of perforations in silencer pipes. Finally, a prototype of the exhaust silencer was built and examined in order to confirm the effects of these design methods mentioned. As predicted, exhaust noise was reduced without increasing backpressure.

In this study, a system to perform a parameter search of heavy-duty diesel engines is proposed. Recently, it has become essential to use design methodologies including computer simulations for diesel engines that have small amounts of NOx and SOOT while maintaining reasonable fuel economy. For this purpose, multi-objective optimization techniques should be used. Multi-objective optimization problems have several types of objectives and they should be minimized or maximized at the same time. There is often a trade-off relationship between objects and derivation of the Pareto optimum solutions that express the relationship between the objects is one of the goals in this case. The proposed system consists of a multi-objective genetic algorithm (MOGA) and phenomenological model. MOGA has strong search capability for Pareto optimum solutions. However, MOGA requires a large number of iterations.

Generally, it is well known that road noise generated by vibration from automobile tires and suspensions can be reduced by changing the stiffness of the rubber mounts installed in the suspension systems. Such stiffness, however, is rarely changed to avoid riding discomfort and so on. In this paper, a stiffness optimization method for suspension system rubber mounts that reduces road noise, and improves riding comfort as well, is presented. In the process, Road Noise Contribution Analysis (RNCA) is applied to the target vehicle to specify the major factors of road noise. Furthermore, the suspension system of the vehicle is investigated by Sensitivity Analysis using Measured FRF data (SAMF) to identify the optimal stiffness combination of rubber mounts. As a result, an effective stiffness combination of two mounts is specified to reduce road noise and to improve riding comfort.

In this paper, the simulation of the multi-objective optimization problem of a diesel engine is performed using the phenomenological model of a diesel engine and the genetic algorithm. The target purpose functions are Specific fuel consumption, NOx, and Soot. The design variable is a shape of injection rate. In this research, we emphasize the following three topics by applying the optimization techniques to an emission problem of a diesel engine. Firstly, the multiple injections control the objectives. Secondly, the multi-objective optimization is very useful in an emission problem. Finally, the phenomenological model has a great advantage for optimization. The developed system is illustrated with the simulation examples.

The present study extends the recently developed HIDECS-GA computer code to optimize diesel engine emissions and fuel economy with the existing techniques, such as exhaust gas recirculation (EGR) and multiple injections. A computational model of diesel engines named HIDECS is incorporated with the genetic algorithm (GA) to solve multi-objective optimization problems related to engine design. The phenomenological model, HIDECS code is used for analyzing the emissions and performance of a diesel engine. An extended Genetic Algorithm called the ‘Neighborhood Cultivation Genetic Algorithm’ (NCGA) is used as an optimizer due to its ability to derive the solutions with high accuracy effectively. In this paper, the HIDECS-NCGA methodology is used to optimize engine emissions and economy, simultaneously. The multiple injection patterns are included, along with the start of injection timing, and EGR rate.

In this study, the air suspension is newly applied to the engine mounting layout for getting the significant vibration isolation effect. In this case, the genetic algorithm so called GA is also applied for the optimization of many parameters, calculations of stiffness matrix and inverse stiffness matrix to prevent the coupled vibration of lateral and rolling modes and to obtain the displacement of each mounting point. As a result, inexperienced engineers can easily obtain the optimum engine mounting layout in a minute. By the confirmation test of FEM, the engine lateral vibration level at 25Hz dropped below 1/10 and its effect was significant.

This paper presents an analytical model for the prediction of piston secondary motion and the vibration due to piston slap. For the modeling of piston slap phenomenon, cylinder liner is modeled as a several spring-mass system that are connected by modal characteristics, and lubricant film between the piston and the cylinder is modeled as reaction force vectors which excite resonant mode of them. By comparing experimental results and analytical ones, the validity of the proposed model has been confirmed. The optimization of the piston skirt profile is also carried out with the analytical model, and it is confirmed that the round shape of the lower part of piston skirt is effective for the reduction of piston slap excitation.