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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.

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 paper deals with model based predictive control of combustion engines. Nonlinear black-box predictive models based on neuro-fuzzy approach are utilized. The structure of the models is optimized within an identification process. The nonlinear models are locally linearized and consequently used for the efficient on-line computation of forthcoming control actions. In desire to respect a fact that the speed of input-output response may vary significantly for different input/output groups, multilevel predictive models are proposed. Predictive control is again applied to approximate the desired behavior of chosen output variables. Potential algebraical constraints between different prediction layers are involved in the control algorithm using quadratic programming. The control scheme is optimized using simplified fast simulation model.

The paper describes the tool of ICE transient response simulation suitable for incorporation into a predictive engine controller. The model is simplified, thus enhancing the simulation speed but keeping its predictive capability at a reasonable level. The main modules of a code suitable for the near-real-time simulation of engine thermodynamics are described in the paper. They include engine cylinder (incl. simplified pressure trace prediction), fuel injection system, main controllers, both inlet and exhaust manifolds, turbocharger and engine dynamics. The laws of conservation are used to describe any of the thermodynamic/hydrodynamic modules of a model. The method of algebraic re-construction of a pressure trace inside a cylinder has been developed and tested for prediction of engine speed variation. The modular structure of a model allows for the implementation of the current operating principles of ICEs.

Diesel fuel injection process calculations have been performed by means of in-house developed mathematical models. An Eulerian multidimensional code for in-cylinder two-phase flow computations is used in conjunction with a hydrodynamic one-dimensional model of a fuel injection system. The multidimensional model comprehends all basic processes, which play a role in spray formation. The compressible gaseous flow with transport of species is solved together with the flow of dispersed liquid phase using the Eulerian reference frame for both phases. The two-way coupling between the phases in mass, momentum, and energy balances is considered. A detailed description of liquid phase is present, taking into account drop size distribution in terms of the multi-continua approach. The hydrodynamic model capable of simulating common fuel injection systems is used for the rate-of-injection computations to provide realistic boundary conditions to the spray model.

The presented work deals with possibilities of modeling divided combustion chamber using available 1-D/0-D software. It is usable for indirect injection diesel engines, gas SI engines with pre-chambers for very lean mixture ignition, etc. The model solves all layouts where main cylinder is connected to additional volumes. This connection allows for heat and energy transfer between connected parts. The application of standard ROHR functions (Wiebe, etc.) which are normalized to constant fuel mass is limited. A new marker gas concentration algorithm is proposed for the use of empiric ROHR functions. The standard approach (without proposed algorithm) was tested modeling large-bore gas SI engine with pre-chamber where the mixture is ignited and experimental direct injection hydrogen one-cylinder engine with an additional volume between fuel injector and the cylinder itself to protect the injector from very high pressures and temperatures in the cylinder.

The paper deals with an application of advanced simulation methods to modeling of hydrogen fueled engines. Two models have been applied - 0-D algorithm and CFD. The 0-D model has been based on GT-Power code. The CFD model has been based on Advanced Multizone Eulerian Model representing general method of finite volume. The influence of main engine parameters, e.g. air excess, spark timing, compression ratio, on NOx formation and engine efficiency has been investigated. Both models have been calibrated with experimental data. Examples of results and comparison with experiments are shown. The means of reducing NOx formation are discussed.

The paper describes patterns of algorithms for different innovative levels of design at parametric, configuration and conceptual levels. They can be applied to Computer-aided Engine Design (CED). Data structures, process simulation hierarchy, used modules of engine simulation and needs for their further development are described. An example of advanced thermodynamics modeling of combustion engines is included.