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Today diesel engines are controlled by electronic control units (ECU's), performing complex functions. New developed control algorithms should already be tested under real-time conditions in the laboratory before they are applied to the real engine. Hardware-in-the-loop simulation (HIL) is a powerful tool for development and test of the control algorithms implemented in the ECU's. Modern diesel ECU's are able to react to rotary oscillations of the crankshaft within a work cycle in order to control idling and running smoothness by a cylinder-individual variation of the start of delivery and the injection time. As a consequence also the simulator has to be able to generate torque oscillations with a resolution adapted to the sample rate of the ECU. The paper describes a high resolution real-time model which was designed by expanding a steady state model by a parallel thermodynamic model with a simplified structure.

The paper presents a new method based on neural networks to model the dynamic behavior of combustion pressure in SI engine cylinders, represented only by conventional input-output data. The approach is based on a functional representation of the pressure curve. The function parameters are adjusted by training a static neural network (SNN) for each working cycle. These parameters resp. “weights” are used in the following as reference pressure feature sequences. The sequences are simulated using time delay neural network (TDNN) as functions of engine speed, manifold pressure, ignition time and A/F ratio. The developed models can be used as stand alone models or as submodels within a global structure. It can be integrated as a real-time model in a HIL simulator to stimulate an ECU or implemented within an ECU for torque estimation. Performance of the proposed modeling strategy is verified by comparing experimental data from a test bench to real-time simulation results.

Common rail fuel injection is the latest breakthrough in diesel engine technology. For research, development and quality control of the used electronic control units (ECU's), hardware-in-the-loop-simulation (HIL) is a useful tool for test and verification. The paper describes a high resolution real-time model of pump, rail, control valve and injectors which results in a reliable approximation of the dynamic characteristic of pressure and mass flow of the fuel. In respect to computing time and system resources this model is combined with a steady state model of a Diesel engine. It describes mainly the effects of the input variables start of injection and injection time on the engine torque at the operating point of the engine, defined by its speed and intake manifold pressure. The theoretical deduction will be completed by simulation results of the transient behavior of a Common Rail engine which are simulated by the real-time simulator CARTS(1) (Figure 1) connected to a Diesel-ECU.

Advanced automatic transmissions are controlled by electronic control units (ECUs) which perform the gear change and furthermore a lot of complex control and diagnostic functions. Hardware-in-the-loop simulation (HIL) is a powerful tool to develop and test the control algorithms implemented in the ECUs. The simulation is based upon mathematical models of the different power train components, adapted to the real-time requirements. In this paper an improved real-time model of an automatic transmission with a Ravigneaux planetary gear train is presented. This transmission contains among other components numerous clutches and brakes. The time-variant states of these nonlinear elements (sliding and static friction) lead to numerical problems with respect to real-time simulation. In the suggested model the transferred torques of the different clutches and brakes are calculated using the methods of multi-variable control.

Advanced passenger car control is based on multiple electronic control units (ECUs), performing complex control algorithms and diagnostic functions for the different power train components like combustion engine, automatic transmission, brakes or chassis. For research and development the engineers need tools to test and verify either the reliability of new control strategies implemented in the ECUs or the interaction of different ECUs in a car. These tests should be done to the highest extent in the laboratory to reduce costs and risks which are involved in test stands or experimental cars. Therefore the optimal solution is the operation of the ECUs in a real-time closed loop environment.

The reduction of engine-out emissions and increase of the total efficiency is a fundamental approach to reduce the fuel consumption and thus emissions of vehicles driven by combustion engines. Conventional passenger cars are operated mainly in lower part loads for most of their lifetime. Under these conditions, oil temperatures are far below the maximum temperature allowed and dominate inside the journal bearings. Therefore, the objective of this research was to investigate possible potentials of friction reduction by optimizing the combustion engine’s thermal management of the oil circuit. Within the engine investigations, it was shown that especially the friction of the main and connecting rod bearings could be reduced with an increase of the oil supply temperature. Furthermore, on a journal bearing test rig, it was shown that no excessive wear of the bearings is to be expected in case of load increase and simultaneous supply of cooler oil.

Increased quantities of fuel in the lubricating oil of CI engines pose a major challenge to the automotive industry in terms of controlling the oil aging and the wear caused by dilution. Due to a lack of methods to calculate the oil-fuel-composite transport across the ring pack, predicting the fuel ratio in the oil sump has been an extremely challenging task for engine manufacturers. An accurate and computationally efficient simulation model is critical to predict the quantity of fuel diluted in the oil in the preliminary development stage of automotive engines. In this work, the complex composite transport across the piston ring pack was reduced to a simple transport model, which was successfully implemented into a multi-body simulation of the ring pack. The calculation domain was partitioned into two parts, the ring grooves and the piston lands. Inside the grooves the oil flow caused by the pumping and squeezing action of the piston rings was calculated using the Reynolds equation.

Real-time models, which reflect dynamic behavior of the SI engine, are needed for building up ECU testing devices like HIL simulators. In this paper the thermodynamic processes are reduced to some basic assumptions and combined with neural approximators of testbench data. So the parameters of the approximators can be easily adapted to similar new engines, while the principle structure describing interaction of the time- and angle-based processes remains unchanged. The model has been implemented and tested in a HIL-simulator. The performance of the proposed modeling strategy could be proved by comparing measurement data from a test bench to real-time simulation results.

High combustion pressure in combination with high pressure gradient, as they e.g. can be evoked by high efficient combustion systems and e.g. by alternative fuels, acts as broadband excitation force which stimulates natural vibrations of piston, connecting rod and crankshaft during engine operation. Starting from the combustion chamber the assembly of piston, connecting rod and crankshaft and the main bearings represent the system of internal vibration transfer. To generate exact input and validation values for simulation models of structural dynamic and elasto-hydrodynamic coupled multi-body systems, experimental investigations are done. These are carried out on a 1.5-l inline four cylinder Euro 6 Diesel engine. The modal behaviour of the system was examined in detail in simulation and test as a basis for the investigations. In an anechoic test bench airborne and structure-borne noises and combustion pressure are measured to identify the engine´s vibrational behaviour.

The paper presents a simulation environment for the test of driver assistance systems. It covers software-in-the-loop and hardware-in-the-loop test capabilities. In the hardware-in-the-loop (HiL) configuration, real components such as electronic control units (ECUs) and actuators are embedded in the system. First, requirements for a virtual environment are defined. They build the basis for the entire simulation. Special emphasis is given to the interaction between the simulated vehicle under test and its traffic environment. A virtual environment was developed in which the simulated vehicle can drive on a road together with the surrounding traffic. The simulation environment is composed mainly of a traffic scenario generator and a simulation of sensor behavior allowing the recognition of the vehicle's surroundings. Appropriate critical traffic scenarios are generated depending on the tested driver assistance system.

In the research project “New Exhaust Emission Concept”, supported by the Minister of Research and Technology of the Federal Republic of Germany, the main goal was the minimization of the raw exhaust emission of a gasoline engine by operating the engine in its (HC +NOx)-minimum, as well as the improvement of its fuel economy. With respect to these goals it was necessary to develop new control strategies. To preadjust the appropriate electronic control systems already in the laboratory, a real time simulator was developed, to reproduce the sensor signals of a gasoline engine under steady state, but also under dynamic conditions. The paper gives a survey over the technical specifications of the simulator, the method of mathematical engine modelling, the simulation algorithms and the used hardware solution. Some characteristic results show the performance and the adventages of the use of the simulation system.

SI engines are dynamic systems with highly nonlinear characteristics which are controlled by ECUs performing complex control algorithms. Hardware-in-the-Loop (HIL) simulation is an important tool to support test and verification during the development phase. The simulation model has to accurately reflect the dynamic behavior of the SI engine in the whole operating area. This paper describes a neural network approach to identify, i.e. to model a nonlinear dynamic system, the SI engine, represented only by I/O measurement data. The neural models have advantages with respect to robustness and measuring extent. They can be used as stand alone models or as sub-models integrated in a global model based on a physical structure. Measurements from a test bench compared to real-time simulation results prove the performance of the proposed modeling strategy.