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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.

The objective of this paper is to complete a thorough investigation of the pressure wave supercharger (PWS) to explore the potential of this technology in engine applications. The PWS is a non-steady flow device that uses shock waves to pressurize fluids by transferring energy from a high-pressure flow to a low-pressure flow without separation by physical walls. The paper introduces a 1-D model of PWS in GT-SUITE calibrated by experiments on steady flow test rig. The 1-D model respects both exhaust and fresh air in each of the cells, friction and heat transfer in the cells as well as the continual opening and closing of the cells. Moreover, the cell wall temperature is computed and the leakage flow between the cells and housings modeled. The limits of PWS operation regarding pressures, temperatures and mass flows are first mapped on the virtual test rig utilizing the calibrated 1-D code based on the Mazda Comprex device.

The presented paper deals with a methodology to model cycle-to-cycle variations (CCV) in 0-D/1-D simulation tools. This is achieved by introducing perturbations of combustion model parameters. To enable that, crank angle resolved data of individual cycles (pressure traces) have to be available for a reasonable number of engine cycles. Either experimental data or 3-D CFD results can be applied. In the presented work, experimental data of a single-cylinder research engine were considered while predicted LES 3-D CFD results will be tested in the future. Different engine operating points were selected - both stable ones (low CCV) and unstable ones (high CCV). The proposed methodology consists of two major steps. First, individual cycle data have to be matched with the 0-D/1-D model, i.e., combustion model parameters are varied to achieve the best possible match of pressure traces - an automated optimization approach is applied to achieve that.

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 describes experience obtained with a GT-Power code used for a downsized turbocharged gasoline engine modeling. The steady-performance model, calibrated by preliminary experiments, has been modified to the transient response one. Knock limit prediction has been used for compression ratio and boost pressure optimization. New authors′ models have been developed for extrapolation of compressor and turbine maps to cover the field of operation modes during a typical transient response. GT-Power control elements ensured a realistic engine response to accelerator, brake or clutch positions. The Driver element could drive various speed schedules such as maximum acceleration mode, engine braking mode or the European fuel-consumption/emission test.

The paper describes techniques used for optimization of timing, shaping and control of pressure wave exchangers including the prediction of pressure-flow rate characteristics of these devices. BBC Baden and ETH Zürich originally proposed them in 60's using the direct pressure exchange between exhaust gas and fresh air in a narrow channel (the COMPREX® device). A technique allowing COMPREX® pressure exchanger to be simulated in detail in a commercially available 1-D cycle simulation tool has been developed. Before the design of a specific exchanger is started the layout must be carefully optimized concerning distribution gear for both fresh air and exhaust gas. Simulation facilities provided by advanced 1-D codes like GT-Power from Gamma Technologies create a valuable tool to do this task and to find alternative design solutions.

The 1-D model of a radial centripetal turbine was developed for engine simulation to generalize and extrapolate the results of experiments to high pressure ratio or off-design velocity ratio using calibrated tuning coefficients. The model concerns a compressible dissipative flow in a rotating channel. It considers both bladed or vaneless turbine stators and a twin-entry stator for exhaust pulse manifolds. The experiments were used to find values of all model parameters (outlet flow angles, all loss coefficients including an impeller incidence loss) by an original method using repeated regression analysis. The model is suitable for the prediction of a turbocharger turbine operation and its optimization in 1-D simulation codes.

The boost pressure demands call for high efficiency turbochargers. Perfect matching to an engine and controlling in operation is a prerequisite, especially if highly diluted mixture is used. The main impact on four-stroke engine efficiency is performed via gas exchange work, Correct turbocharger representation, usually performed by maps, should be delivered by turbocharger manufacturers and applied in simulation optimizations. The robust calibration methods are required for fast-running real time simulations used for model-based control. The paper clarifies the relations between apparent and real turbocharger isentropic efficiencies at steady-flow testbed and their impact on engine cycle optimization by simulation. Simple procedures excluding the impact of heat transfer inside a turbocharger are described. The described methods are based on the use of overall turbocharger efficiency.

The physical 1-D model of a radial turbine consists in a set of gas ducts featuring total pressure and/or temperature changes and losses. This model has been developed using the basic modules of generalized 1-D manifold solver. The tools for it were presented at SAE 2008 and 2009 World Congresses. The model published before is amended by a semi-empiric mechanical loss and windage loss modules. The instantaneous power of a turbine is integrated along the rotating impeller channel using Euler turbine theorem, which respects the local unsteadiness of mass flow rate along the channel. The main aim of the current contribution is to demonstrate the use of measured turbine maps for calibration of unsteady turbine model for different lay-outs of turbine blade cascades. It is important for VG turbines for the optimal matching to different engine speeds and loads requirements.

This article presents results of the Design Assistance System (DASY) development and examples of its application for engine concept modeling. The software (DASY) for creating and maintaining knowledge database was developed. This software is targeted to simplify and speed up the concept design process. The targets were met by providing the high level of flexibility along with a simple user interface. Two examples that show interaction of DASY with computer-aided design (CAD) software are presented. The DASY creates a template for conserving the knowledge acquired during engine design in the past. It provides hints for the future design tasks by offering a data of similar engines, based on experiments and simulations at different levels of complexity and profoundness.

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.

This article presents results of the Design Assistance System (DASY, will be referred to as a tool in this paper) development and examples of its application for engine concept modeling. The software tool for creating and maintaining knowledge database is being developed at the Czech Technical University in Prague. This tool is targeted to simplify and speed up the concept design process. The targets were met by providing the high level of flexibility along with a simple user interface. Two examples that show interaction of this tool with computer-aided design (CAD) and computer-aided engineering (CAE) software are presented. One example includes an optimization using implemented genetic algorithm. By using this tool, one can create templates for conserving the knowledge acquired during engine design in the past. It provides hints for the future design tasks by offering a data of similar designs, based on experiments and simulations at different levels of complexity and profoundness.

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 current state-of-the-art offers two extremes of engine mechanical loss models: pure empirical models, using, e.g., regression models based on experimental results, and full-sized 3-D hydrodynamic friction models, solving Reynolds-like lubrication equations for complicated geometry of piston ring/cylinder liner or load-distorted shapes of crankshaft/connecting rod bearings and journals. Obviously, the former method cannot be reliably extrapolated while the latter is too complicated, especially for the early stage of design. The aim of the current paper is describing the development and experimental calibration of the physical cranktrain model for FMEP prediction, based on simplified phenomenological model of mixed friction. The model uses simply defined shapes of Stribeck curves (friction coefficient) in dependence on Sommerfeld number, i.e., on effective sliding velocity, oil viscosity, dimension scaling factor and the normal force load.

The paper describes a way to a 1-D central streamline model of a radial turbine flow, suitable for twin-scroll description and based on approximation of real physics of flow mixing and energy transformation. The original 1-D model of a single scroll turbine, described earlier in numerous SAE papers, has been amended by twin-scroll nozzles (both vaneless or with blade cascades) and mixing of individual partitions of flows upstream of additional vaneless nozzle and an impeller. This model is transferable to 1-D unsteady simulations as it is (i.e., using quasi-steady approach) or using 1-D unsteady solvers. It has suitable features even for more detailed description of turbine flows and energy transformation. The first results of pulse influence on turbine maps delivered expected results consisting of complicated interaction between individual losses.

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).

The objective of this paper is to present the results of the GT Power calibration with engine test results of the air loop system technology down selection described in the SAE Paper No. 2012-01-0831. Two specific boosting systems were identified as the preferred path forward: (1) Super-turbo with two speed Roots type supercharger, (2) Super-turbo with centrifugal mechanical compressor and CVT transmission both downstream a Fixed Geometry Turbine. The initial performance validation of the boosting hardware in the gas stand and the calibration of the GT Power model developed is described. The calibration leverages data coming from the tests on a 2 cylinder 2-stroke 0.73L diesel engine. The initial flow bench results suggested the need for a revision of the turbo matching due to the big gap in performance between predicted maps and real data. This activity was performed using Honeywell turbocharger solutions spacing from fixed geometry waste gate to variable nozzle turbo (VNT).

Current vehicles, especially the electric ones, are complex mechatronic devices. The pickup vehicles of small sizes are currently used in transport considerably. They often operate within a repeating scheme of a limited variety of tracks and larger fleets. Thanks to mechatronic design of vehicles and their components and availability of high capacity data connection with computational centers (clouds), there are many means to optimize their performance, both by planning prior the trip and recalculations during the route. Although many aspects of this opportunity were already addressed, the paper shows an approach developed to further increase the range of e-vehicle operation. It is based on prior information about the route profile, traffic density, road conditions, past behaviour, mathematical models of the route, vehicle and dynamic optimization. The most important part of the procedure is performed in the cloud, using both computational power and rich information resources.