Dissertations / Theses on the topic 'Mean value engine models'

VehProLib is one of many libraries being developed for the object oriented multi-domain language Modelica. The layout and the current status of the library are shown. The aims of the library are to provide the user with a number of different components with different levels of complexity. The components included range from mean value engine components to in-cylinder models. An efficient way to handle parameters using records is provided. Different bus systems are implemented and discussed. Furthermore are replaceable fluid models introduced in the library. It will be shown that Modelica is a very efficient way to create an advanced modelling library.

Having an engine model that is accurate but not too complicated is desirable when working with on-board diagnosis or engine control. In this thesis a four state mean value model is introduced. To make the model usable in an on-line automotive application it is discrete and simulated with a fixed step size solver. Modelling is done with simplicity as main object. Some simple static models are also presented.

To validate the model measuring is carried out in a Scania R124LB truck with a 12 liter six-cylinder turbo charged diesel engine. In general, for this relatively simple model, the mean errors must be considered low. The inlet manifold pressure mean error during highway driving is 3.4\%.

Due to stricter emission legislation, there is a need for more efficient control of diesel engines with exhaust gas recirculation(EGR). In particular, it is important to estimate the air/fuel ratio accurately in transients. Therefore a new engine gas flow model has been developed. This model divides the gas into one part for oxygen and one part for inert gases. Based on this model an observer has been designed to estimate the oxygen concentration in the gas going into the engine, which can be used to calculate the air/fuel ratio. This observer can also be used to estimate the intake manifold pressure. The advantage of estimating the pressure, instead of low pass filtering the noisy signal, is that the observer does not cause time delay.

Over the last years, the emission and on board diagnostics legislations for heavy duty trucks are getting more and more strict. An accurate engine model that is possible to execute in the engine control system enables both better diagnosis and lowered emissions by better control strategies.

The objective of this thesis is to extend an existing mean value diesel engine model, to include turbo compound. The model should be physical, accurate, modular and it should be possible to execute in real time. The calibration procedure should be systematic, with some degree of automatization.

Four different turbo compound models have been evaluated and two models were selected for further evaluation by integration with the existing model. The extended model showed to be quite insensitive to small errors in the compound turbine speed and hence, the small difference in accuracy of the tested models did not affect the other output signals significantly. The extended models had better accuracy and could be executed with longer step length than the existing model, despite that more complexity were added to the model. For example, the mean error of the intake manifold pressure at mixed driving was approximately 3.0%, compared to 5.8% for the existing model. The reasons for the improvements are probably the good performance of the added submodels and the systematic and partly automatized calibration procedure including optimization.

The emission legislations and the new On Board Diagnostics (OBD) legislations are becoming more strict and making the demands on control and fault detection higher. One way to

control and diagnose the engine is to use a control/diagnose strategy based on physical models and therefore better models are necessary. Also, to be competitive and meet the markets demand of higher power, longer durability and better fuel economy, the models needs to be improved continuously. In this thesis a mean value model of the intake system that predicts the charge air temperature has been developed. Three models of different complexity for the intercooler heat-exchanger have been investigated and validated with various results. The suggested intercooler heat-exchanger model is implemented in the mean value model of the intake system and the whole model is validated on three different data sets. The model predicts the intake manifold temperature with a maximum absolute error of 10.12 K.

Because of new emission and on board diagnostics legislations, heavy truck manufacturers are facing new challenges when it comes to improving the engines and the control software. Accurate and real time executable engine models are essential in this work. One successful way of lowering the NOx emissions is to use Exhaust Gas Recirculation (EGR). The objective of this thesis is to create a mean value model for Scania's next generation EGR system consisting of a poppet valve and a two stage cooler. The model will be used to extend an existing mean value engine model. Two models of different complexity for the EGR system have been validated with sufficient accuracy. Validation was performed during static test bed conditions. The resulting flow models have mean relative errors of 5.0% and 9.1% respectively. The temperature model suggested has a mean relative error of 0.77%.

Since measurements in engine test cells are closely coupled with high costs it is of interest to use physically interpretable engine models instead of engine maps. Such engine models can also be used to do off-line tests of how new or altered components affects engine performance.

In the thesis an existing mean value engine model will be extended with a model of a compressor bypass valve. A controller for that valve will also be developed. The purpose with that controller is to save torque and boost pressure but at the same time avoid having the compressor entering surge during fast closing transients in the throttle position.

Both the extension and controller is successfully developed and implemented. The extension lowers the pressure after the compressor and increases the pressure before the compressor when the bypass valve is being opened and the controller shows better results in simulations than the controller used in the research lab. By using the proposed controller, as much as 5 percent higher torque can be achieved in simulations.

Finally there is a discussion on wastegate control alternatives and the use of TOMOC for optimization of wastegate control.

Mean Value Engine Modeling (MVEM) is used to make engine control development less expensive. With more and more cars equipped with turbocharged engines good turbo MVEM models are needed. A turbocharger consists of two major parts: turbine and compressor. Whereas the turbine is relatively durable, there exist phenomenons on the compressor that can destroy the turbocharger. One of these is surge.

Several compressor models are developed in this thesis. Methods to determine the compressor model parameters are proposed and discussed both for the stable operating range as well as for the surge region of a compressor map. For the stationary region methods to automatically parameterize the compressor model are developed. For the unstable surge region methods to get good agreement for desired surge properties are discussed. The parameter sensitivity of the different surge properties is also discussed. A validation of the compressor model shows that it gives good agreement to data, both for the stationary region as well as the surge region.

Different open loop and closed loop controllers as well as different performance variables are developed and discussed. A benchmark is developed, based on a measured vehicle acceleration, and the control approaches are compared using this benchmark. The best controller is found to be a open loop controller based on throttle and surge valve mass flow.