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Faced with the need to reduce development time and cost, the hardware-in-the-loop (HIL) simulation increasingly proves to be an efficient tool in the automotive industry. It offers the possibility to investigate new engine control systems with fewer expensive engine dynamometer experiments and test drives. In the scope of a research collaboration, Daimler Benz and Darmstadt University of Technology are developing a hardware-in-the loop simulator for the investigation of the electronic engine management of the new Mercedes Benz truck engine series 500 and 900. This paper first describes the necessary models for real-time simulation of the subsystems Diesel engine, turbo charger and vehicle. Then the setup of the simulator test bench is introduced and the performance of the simulator is demonstrated by several experimental results.

This paper deals with physical modelling of a turbocharger with variable turbine geometry (VTG) and its real-time simulation based on dynamic artificial neural networks (ANN). Thermodynamic und fluiddynamic equations, describing the basic functionality and relations between pressure, mass flow and temperature at the inlet and outlet ports of compressor and turbine, build up a multiple input multiple output model (MIMO). A special kind of ANN, namely the LoLiMoT algorithm, is used for real-time simulation. Training the network using measurement and simulated data, the dynamic behaviour can be simulated with less computational effort than the physical model. The neural network may be used in engine control systems as observer for non measurable signals, like rotor speed or turbine and compressor torque, figure 1.

Due to more severe exhaust gas regulations with sharper exhaust gas limitations and rising requirements for on-board diagnosis in this contribution a method for injection mass supervision in diesel engines using a fast broadband oxygen sensor will be presented. Based on a physical model the injected fuel mass can be determined by evaluating the measured air mass and oxygen concentration in the exhaust gas. Cylinder individual injection mass calculation becomes possible using an inverse model of the oxygen sensor dynamic. Thereby the sensor dynamic is specified by evaluating step responses of the oxygen concentration at jumps of the injection mass. For cylinder assignment the runtimes of the exhaust gas in the exhaust pipe have to be determined. They result from the calculation of the cross correlation function of the reconstructed fuel mass and measured mean indicated cylinder pressure.

Methods for model-based fault detection are presented which detect a wide range of faults using only common production sensors, namely air mass sensor, manifold pressure sensor, manifold temperature sensor and engine speed. Five suitable reference models for fault detection are set up and identified at the test stand. The developed fault detection algorithms use the dependencies of the four sensor signals based on the reference models. Thereby five residuals and five symptoms are calculated. The model-based fault detection algorithms are implemented with a dSPACE Rapid Control Prototyping system and verified at the test stand. Measurements of online fault detection are shown.

Because of increasing requirements for low emissions and fuel consumption, combustion engines are getting more and more control inputs, like multiple injection, exhaust gas recirculation (EGR), turbocharger valve position (TVP), variable valve timing (VVT), etc. With the addition of manipulated variables, the required measurement time for obtaining the steady-state characteristics and control look-up tables rises exponentially. A comprehensive design of the measurement experiment is becoming more and more essential. The objective is to measure the engine characteristics and properties with a minimum number of measurement points (with firstly concentrating on the stationary behavior). A new methodology is presented to automatically determine characteristic mappings by incorporating prior knowledge. Since physical modeling of the engine behavior is mostly not appropriate, prior knowledge for experimental design is derived by evaluating measurement data.

For the cylinder-selective monitoring of combustion cycles in spark-ignition engines, the dynamic exhaust-gas pressure is analyzed. A time domain based diagnostic system for misfire detection has been developed and tested on data measured in a BMW 750i, V-12 engine. It uses features of the suitable low-pass-filtered exhaust-gas pressure signal by calculating differences of the locally determined extrema. For the detection and localization of all misfire combinations a simple inference system in the form of linguistic rules is used. It is shown that even within the operating areas of high engine speeds and low loads on engines with a high number of cylinders good classification rates can be obtained.

Modern Diesel injection systems have to serve different demands. Beside the improvement of the injection timing and assignment special concentration is focused on increasing injection pressure to improve combustion and lower exhaust gas emissions. With the higher complexity of these systems and the high burden on the pump components especially in the high pressure part of the injection pumps, the wish for supervision of delicate components occurs. Therefore suitable and efficient supervision methods have to be developed to early detect initiating faults. Because of the correlation between combustion and injection, one way to detect faults in the injection system is to supervise the combustion in the individual cylinders. This can be done by evaluating the crankshaft speed at the flywheel. Speed is directly related to combustion by the indicated pressure and the indicated torque respectively, the crankshaft drive and the resulting torque at the crankshaft.

Icing is a major hazard for aviation safety. Over the last decades an additional risk has been identified when flying in clouds with high concentrations of ice-crystals where ice accretion may occur on warm parts of the engine core, resulting in engine incidents such as loss of engine thrust, strong vibrations, blade damage, or even the inability to restart engines. Performing physical engine tests in icing wind tunnels is extremely challenging, therefore, the need for numerical simulation tools able to accurately predict ICI (Ice Crystal Icing) is urgent and paramount for the aeronautics industry, especially regarding the development of new generation engines (UHBR = Ultra High Bypass Ratio, CROR = Counter rotating Open Rotor, ATP = Advanced Turboprop) for which analysis methods largely based on previous engines experience may be less and less applicable. The European research project MUSIC-haic has been conceived to fill this gap and has started in September 2018.