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Vehicle thermal management (VTM) simulations are becoming increasingly important in the development phase of a vehicle. These simulations help in predicting the thermal profiles of critical components over a drive cycle. They are usually done using two methodologies: (1) Solving every aspect of the heat transfer, i.e., convection, radiation, and conduction, in a single solver (Conjugate Heat Transfer) or (2) Simulating convection using a fluid solver and computing the other two mechanisms using a separate thermal solver (Co-simulation). The first method is usually computationally intensive, while the second one isn’t. This is because Co-simulation reduces the load of simulating all heat transfer mechanisms in a single code. This is one of the reasons why the Co-simulation method is widely used in the automotive industry. Traditionally, the methods developed for Co-simulation processes are load case specific.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

Air charge calibration of turbocharged SI gasoline engines with both variable inlet valve lift and variable inlet and exhaust valve opening angle has to be very accurate and needs a high number of measurements. In particular, the modeling of the transition area from unthrottled, inlet valve controlled resp. throttled mode to turbocharged mode, suffers from small number of measurements (e.g. when applying Design of Experiments (DoE)). This is due to the strong impact of residual gas respectively scavenging dominating locally in this area. In this article, a virtual residual gas sensor in order to enable black-box-modeling of the air charge is presented. The sensor is a multilayer perceptron artificial neural network. Amongst others, the physically calculated air mass is used as training data for the artificial neural network.

The successful design and especially the control of the SCR system is a challenging process that can be supported by the application of simulation tools. As a first step, we employ physico-chemically informed ‘off-line’ models that are calibrated with the help of targeted small- and full-scale tests. Despite their high level of sophistication, this SCR model is able to be integrated in a control-oriented simulation software platform and connected to other powertrain simulation blocks. The target is to use this simulation platform as a virtual environment for the development and optimization of SCR control strategies. The above process is demonstrated in the case of a passenger car SCR. The model is calibrated at both fresh and aged catalyst condition and validated using experimental data from the engine bench under a wide variety of operating conditions. Next, the calibrated model was coupled with embedded control models, developed for Euro 6 passenger car powertrains.

Among the existing concepts that help to improve the efficiency of spark-ignition engines at part load, Controlled Auto-Ignition™ (CAI™) is an effective way to lower both fuel consumption and pollutant emissions. This combustion concept is based on the auto-ignition of an air-fuel-mixture highly diluted with hot burnt gases to achieve high indicated efficiency and low pollutant emissions through low temperature combustion. To minimize the costs of conversion of a standard spark-ignition engine into a CAI engine, the present study is restricted to a Port Fuel Injection engine with a cam-profile switching system and a cam phaser on both intake and exhaust sides. In a 4-stroke engine, a large amount of burnt gases can be trapped in the cylinder via early closure of the exhaust valves. This so-called Negative Valve Overlap (NVO) strategy has a key parameter to control the amount of trapped burnt gases and consequently the combustion: the exhaust valve-lift profile.

An individual cylinder AFR estimator using a single proportional oxygen sensor (UEGO) situated at the confluence point of the exhaust manifold has previously been described ([1],[2]). As this model is nonlinear, it proposes a linear slicing by zone [3], enabling it to apply the estimator to the entire range of engine speeds. However, several problems remain; the model [3] is complicated and therefore difficult to program in an electronic engine control, the model is no longer valid with the ageing of sensors, injectors, or the motor, it is impossible to diagnostic the defaulting organ or one which deviates. The work set out in this article describes a model, and the conditions for its identification, which resolve these. The resultats obtained on engine tests show that the model is robust, precise and capable of estimating cylinder AFR as well as diagnosticing an injector or UEGO sensor deviation.

The optimization of fuel efficiency and the minimization of the residual gas fraction require individual cylinder control of the amounts of inducted air mass and injected fuel mass. Determination of an individual cylinder air/fuel ratio (AFR) regulator is based on the measured AFR for each cylinder, using 4 proportional UEGO sensors. The innovative character of this study describes a unified and robust individual cylinder AFR estimator, using a single measuring point: a proportional oxygen sensor located in the exhaust manifold. The model used for the estimator is a state model such that the dimension of the state and measurement matrices are unique, whatever the manifold configuration and the sensor position (confluence point or exhaust manifold: unified model), the engine speed (robust model).

Exhaust acoustics simulation is an important part of the exhaust system process. Especially important is the trend towards a coupled approach to performance and acoustics design. The present paper describes a new simulation tool developed for such coupled simulations. This tool is based on a one-dimensional fluid dynamics solution of the flow in the engine manifolds and exhaust and intake elements. To represent the often complex geometries of mufflers, an easy-to-use graphical pre-processor is provided, with which the user builds a model representation of mufflers using a library of basic elements. A comparison made to two engines equipped with exhaust silencers, shows that the predictions give good results.

For the BMW V8 engine, a new LEV/EU3 emission concept has been developed by improvements to the previous engine management and secondary air supply and a complete new exhaust system. Beside the emission limits, also high engine output targets and high operating reliability were targeted. In addition the new exhaust system had to meet low cost targets. Based on these requirements an exhaust concept with separate pre catalyst and main catalyst was chosen. To reduce the heat mass and to optimize the pressure drop, 4.3mil/400cpsi thin wall ceramic substrates were used for the pre and main catalyst.

To meet LEV and EU Stage III emission requirements, it is necessary for new catalytic converters to be designed which exceed light-off temperature as quickly as possible. The technical solutions are secondary air injection, active heating systems such as the electrically heated catalytic converter, and the close coupled catalytic converter. Engine control functions are extensively used to heat the converter and will to play a significant role in the future. The concept of relocating the converter to a position close to the engine in an existing vehicle involves new conflicts. Examples include the space requirements, the thermal resistance of the catalytic coating and high temperature loads in the engine compartment.

The production of the BMW ALPINA B12 5.7 with Switch-Tronic transmission provides the markets of Europe and Japan with an exclusive, luxury-orientated, high performance limited series limousine. This is the first vehicle worldwide to be fitted with the progressive exhaust gas aftertreatment technology known as the Electrically Heated Catalyst (EHC), in which the effectiveness of the power utilized is increased significantly by an alternating heating process for both catalytic converters. Only since this achievement has the implementation of the EHC been viable without extensive modification to the battery and alternator. With this exhaust gas aftertreatment concept, the emissions of this high performance vehicle will fall to less than half the maximum permissible for compliance with 1996 emission standards.

Apart from the reduction of engine-out emissions from the powerplant, the development of an efficient and reliable catalytic converter heating system is an important task of automotive engineering in the future to meet standards that will require reduction of cold start emissions. Carrying out a comprehensive study in this field, BMW has tested and evaluated possible solutions to this challenge. In additon to the electrically heated catalytic converter (E-cat) and the afterburner chamber, an incorporated burner system would meet the requirement for fast catalyst light-off in the future, particularly in the case of larger engines.

Post-treatment of diesel exhaust was studied on a laboratory scale, using a reactor to simulate the post-combustion of soot collected inside a monolithic particulate trap. A parametric study of the trap regeneration was carried out. A periodic hydrocarbon injection system was developed to assist the catalyzed trap regeneration. This technique led to the trap regeneration with a temperature of the entering gas of 150°C, which is very low. An optimization of the injection process allowed one to minimize the injected amount of hydrocarbons and to have good control of the trap temperature. Another advantage of the hydrocarbon injection is to provide good conditions for reducing NO in an oxidizing atmosphere (10% O2). The importance of the hydrocarbon content was pointed out by a parametric study of NO conversion under a wide range of hydrocarbon concentrations (1000 ppm to 2.5% in CH4 equivalents).