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Proportional integral derivative (PID) control technique is the most common control algorithm applied in various engineering applications. Also, particle swarm optimization (PSO) is extensively applied in various optimization problems. This paper introduces an investigation into the use of a PSO algorithm to tune the PID controller for a semi-active vehicle suspension system incorporating magnetorheological (MR) damper to improve the ride comfort and vehicle stability. The proposed suspension system consists of a system controller that determine the desired damping force using a PID controller tuned using PSO, and a continuous state damper controller that estimate the command voltage that is required to track the desired damping force. The PSO technique is applied to solve the nonlinear optimization problem to find the PID controller gains by identifying the optimal problem solution through cooperation and competition among the individuals of a swarm.

The paper will present the design of shift fork for automotive manual gearbox dedicated for the manufacturing with powder metal technology. Based on limitations and requirements of new production technology of shifting sleeve, the new design of shifting sleeve and shifting fork are created. The prototypes of shift fork and sleeve were built, but for cost reasons, were manufactured from steel. The functionality of several forks with different tolerances was tested. Prototypes were put through functional and durability tests on testing bench in real automotive gearbox. The tests were accomplished on the inertia test stand. Drawings and CAD models of tested prototypes, custom tools and designed shift forks are described in detail in this article.

The physical 1-D model of a radial turbine consists of a set of gas ducts featuring total pressure and/or temperature changes and losses. Therefore, the wave propagation and filling/emptying plays a significant role if a turbine is subjected to unsteady gas flow. The results of unsteady turbine simulation using the basic modules of generalized 1-D manifold solver in GT Power are demonstrated. The turbine model calibration parameters can be identified by means of 1-D steady model used in optimization code loop. The examples of model results are compared to steady flow map predictions of turbine efficiency and engine pumping loop work. The model may be used for prediction of turbine data in out-of-design points as presented in the paper. The other important role of a model, however, is an accurate evaluation of turbine parameters from pressure and speed measurements at an engine in operation.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

The aim of the current contribution is to develop a tool for the improvement of accuracy of turbocharger turbine simulation during matching of a turbocharger to an engine. The paper demonstrates the possibility of unsteady turbine simulation in pulsating flow caused by an internal combustion engine using the basic modules of generalized 1-D manifold solver with entities (pipes, channels) under centrifugal acceleration in general direction and under non-uniform angular speed, which has not yet been explored. The developed model extrapolates steady operation turbine maps by this way. It uses 1-D model parameters identified from steady flow experiments. Unlike the lumped-parameter standard models of turbocharger turbines, the model takes into account complete 1-D features of a turbine flow path including arbitrary shape of turbine impeller vanes.

The paper proposes the way of using scavenging curves, i.e., dependence of residual gas fraction in exhaust port or valve on residual fraction in a cylinder, found by CFD simulations. In the general case, exhaust gas recirculation outside of a cylinder (EGR) or internal gas recirculation caused by variable values of burned gas backflow to inlet system may influence in-cylinder residual gas fraction. These deviations may take place during engine optimization, done by 1D models. The determination of scavenging curves via 3D CFD simulations is a time consuming process, which cannot be repeated for every 1D case.

The objective of this study is the development of a computationally efficient CFD-based tool for finding optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses, the duration of each pulse, the duration of the dwell, the exhaust gas recirculation rate and the boost pressure.

The article is focused on a 1-D drive dynamic simulation of a highly turbocharged gas engine. A mono fuel CNG engine has been developed as a downsized replacement of the diesel engine for a medium size van. The basic engine parameters optimization is provided in a steady state operation and a control adjustment is applied to a dynamic vehicle model for a transient response improvement in highly dynamic operation modes of the WLTC (world light duty test cycle), selected for investigation. Vehicle simulation model with optimized control system is used for driving cycle fuel consumption and CO2 emissions predictions compared with the basic engine settings.

The mass and overall dimensions of massively downsized engines for very high bmep (up to 35 bar) cannot be estimated by scaling of designs already available. Simulation methods coupling different levels of method profoundness, as 1-D methods, e.g., GT Suite/GT Power with in-house codes for engine mechanical efficiency assessment and preliminary design of boosting devices (a virtual compressor and a turbine), were used together with optimization codes based on genetic algorithms. Simultaneously, the impact of optimum cycle on cranktrain components dimensions (especially cylinder bore spacing), mass and inertia force loads were estimated since the results were systematically stored and analyzed in Design Assistance System DASY, developed by the authors for purposes of early-stage conceptual design. General thermodynamic cycles were defined by limiting parameters (bmep, burning duration, engine speed and turbocharger efficiency only).