<p>Knock is a phenomenon that limits how effciently an engine can operate. Severe knock is harmful to the engine and must therefore be avoided. Controlling the knock intensity is complicated by a phenomenon called cycle to cycle variations. Because of these variations, the knock intensity must be considered a stochastic variable and the control is made on a mean value from a large number of cycles. </p><p>The SVC (Saab Variable Compression) concept adds the compression ratio as an extra degree of freedom. At Vehicular systems, research is done on how to put this additional variable to its best use. </p><p>A controller is developed that control the engine to a desired knock intensity and torque, using the ignition angle and the pedal position. The controller is implemented as two separate controllers in Matlab and Simulink. These are merged together with a Stateflow chart. A confidence interval calculation is implemented for the mean value of the knock intensity. A program is also developed to process a large number of operating points and make measurements in all of them. </p><p>The conclusion is that the basic construction of the controller and the script are fi;lling their functions but that there are some improvements left to be done. The controller is rather slow and the calculations of the confi;dence interval needs further refi;nement.</p>

Knock is a phenomenon that limits how effciently an engine can operate. Severe knock is harmful to the engine and must therefore be avoided. Controlling the knock intensity is complicated by a phenomenon called cycle to cycle variations. Because of these variations, the knock intensity must be considered a stochastic variable and the control is made on a mean value from a large number of cycles. The SVC (Saab Variable Compression) concept adds the compression ratio as an extra degree of freedom. At Vehicular systems, research is done on how to put this additional variable to its best use. A controller is developed that control the engine to a desired knock intensity and torque, using the ignition angle and the pedal position. The controller is implemented as two separate controllers in Matlab and Simulink. These are merged together with a Stateflow chart. A confidence interval calculation is implemented for the mean value of the knock intensity. A program is also developed to process a large number of operating points and make measurements in all of them. The conclusion is that the basic construction of the controller and the script are fi;lling their functions but that there are some improvements left to be done. The controller is rather slow and the calculations of the confi;dence interval needs further refi;nement.

In this study, an appearance reconstruction method based on extraction of material re&amp / #64258 / ectance properties of a three-dimensional (3D) object from its twodimensional (2D) images is explained. One of the main advantages of this system is that the reconstructed object can be rendered in real-time with photorealistic quality in varying illumination conditions. Bidirectional Re&amp / #64258 / ectance Distribution Functions (BRDFs) are used in representing the re&amp / #64258 / ectance of the object. The re&amp / #64258 / ectance of the object is decomposed into di&amp / #64256 / use and specular components and each component is estimated seperately. While estimating the di&amp / #64256 / use components, illumination-invariant images of the object are computed from the input images, and a global texture of the object is extracted from these images by using surface particles. The specular re&amp / #64258 / ectance data are collected from the residual images obtained by taking di&amp / #64256 / erence between the input images and corresponding illumination-invariant images, and a Lafortune BRDF model is &amp / #64257 / tted to these data. At the rendering phase, the di&amp / #64256 / use and specular components are blended into each other to achieve a photorealistic appearance of the reconstructed object.