Jakub Sevcik

University of West Bohemia · Faculty of Electrical Engineering

Accurate prediction of temperatures in power modules is crucial for proper thermal management. Lumped parameter thermal models are preferred in this application for their low computational cost. The estimation procedure of parameters of these models requires measurements of temperatures of all active elements. This requirement is relaxed in this co...

When designing new electric vehicles for urban transport, both vehicle producers and operators need to establish and verify requirements that the vehicle has to fulfil regarding, e.g., energy storage capacity, driving range, or battery wear. These requirements are typically verified using simulation tools that concentrate mostly on electrical quant...

Proper traffic simulation of electric vehicles, which draw energy from overhead wires, requires adequate modeling of traction infrastructure. Such vehicles include trains, trams or trolleybuses. Since the requested power demands depend on a traffic situation, the overhead wire DC electrical circuit is associated with a non-linear power flow problem...

Accurate knowledge of temperatures in power semiconductor modules is crucial for proper thermal management of such devices. Precise prediction of temperatures allows to operate the system at the physical limit of the device avoiding undesirable over-temperatures and thus improve reliability of the module. Commonly used thermal models can be based o...

Prediction of junction temperatures in power semiconductor modules is essential to improve reliability of the device and prevent module failures due to thermal stress. Lumped parameter network is a popular approach for temperature modeling. Calibration of the thermal model is based on thermal measurements of the junction temperatures that are diffi...

The electrification of transport is one of the key parts of the present aim to reduce undesirable vehicular emissions in the atmosphere. While the full electrification of personal vehicles is mostly associated with employing a big battery pack on the board and charging on (static) charging stations, another interesting possibility appears in the ca...

Design of regularization term is an important part of solution of an ill-posed linear inverse problem. Another important issue is selection of tuning parameters of the regularization term. We address this problem using Bayesian approach which treats tuning parameters as unknowns and estimates them from the data. Specifically, we study a regularizat...

Image restoration is typically defined as an ill-posed problem which has to be regularized to obtain an acceptable solution. In Bayesian interpretation, regularization is equivalent to prior model of the image. An added value of Bayesian point of view is the ability to form a hierarchical model and estimate the hyper-parameters of the prior from th...