2022 Daniel Jung, Bjorn Kleman, Henrik Lindgren, Hakan Warnquist (2022) Fault Diagnosis of Exhaust Gas Treatment System Combining Physical Insights and Neural Networks IFAC PAPERSONLINE, p. 97-102 Continue to DOI Daniel Jung, Joakim Säfdal (2022) A flexi-pipe model for residual-based engine fault diagnosis to handle incomplete data and class overlapping IFAC PAPERSONLINE, p. 84-89 Continue to DOI Kevin Lindstrom, Max Johansson, Daniel Jung (2022) A Data-Driven Clustering Algorithm for Residual Data Using Fault Signatures and Expectation Maximization IFAC PAPERSONLINE, p. 121-126 Continue to DOI Erik Frisk, Fabian Jarmolowitz, Daniel Jung, Mattias Krysander (2022) Fault Diagnosis Using Data, Models, or Both - An Electrical Motor Use-Case Arman Mohammadi, Mattias Krysander, Daniel Jung (2022) Analysis of grey-box neural network-based residuals for consistency-based fault diagnosis
Daniel Jung, Bjorn Kleman, Henrik Lindgren, Hakan Warnquist (2022) Fault Diagnosis of Exhaust Gas Treatment System Combining Physical Insights and Neural Networks IFAC PAPERSONLINE, p. 97-102 Continue to DOI
Daniel Jung, Joakim Säfdal (2022) A flexi-pipe model for residual-based engine fault diagnosis to handle incomplete data and class overlapping IFAC PAPERSONLINE, p. 84-89 Continue to DOI
Kevin Lindstrom, Max Johansson, Daniel Jung (2022) A Data-Driven Clustering Algorithm for Residual Data Using Fault Signatures and Expectation Maximization IFAC PAPERSONLINE, p. 121-126 Continue to DOI
Erik Frisk, Fabian Jarmolowitz, Daniel Jung, Mattias Krysander (2022) Fault Diagnosis Using Data, Models, or Both - An Electrical Motor Use-Case
Arman Mohammadi, Mattias Krysander, Daniel Jung (2022) Analysis of grey-box neural network-based residuals for consistency-based fault diagnosis
Route planning of heavy-duty electric vehicles Electrification of heavy-duty vehicles calls for intelligent methods to optimize the planning of their use and charging. With Scania and Ragn-Sells we develop mathematical models and algorithms for the next generation of transportation systems.
Arvind Balachandran PhD student Abhijeet Behera Karin Blomdahl Coordinator Nils Dressler Lars Eriksson Professor Erik Frisk Deputy Head of Department, Professor, Head of Division Fatemeh Hashemniya PhD student Robin Holmbom Postdoc Olov Holmer Postdoc Erik Höckerdal Adjunct Associate Professor Max Johansson PhD student Svante Johansson Tomas Uno Jonsson Adjunct Assistant Lecturer Sogol Kharrazi Adjunct Associate Professor, Docent Oskar Lind Jonsson PhD student Tobias Lindell Research Engineer Arman Mohammadi PhD student Lars Nielsen Professor Björn Olofsson Arezou Safdari-Vaighani PhD student Christofer Sundström Associate Professor, Docent Theodor Westny PhD student Jian Zhou PhD student Jan Åslund Senior Associate Professor Show all Show less
Vehicular Systems (FS) The research in Vehicular Systems has a clear focus on control, diagnosis, and supervision of functions in vehicles.
Department of Electrical Engineering (ISY) The department is central to the engineering education at the Institute of Technology, one of four faculties at Linköping University, and this regards both basic and applied knowledge.
Electrification of heavy transports requires new thinking Electrification of heavy transports places new and high demands on planning for vehicle use and charging. Researchers at LiU have launched a project with the final aim of developing calculation software for planning routes for electric trucks.