@misc{PischingerEschDuesmann2006, author = {Pischinger, Martin and Esch, Thomas and Duesmann, Klaus}, title = {Elektromagnetischer Aktuator mit gelenkig abgest{\"u}tzter R{\"u}ckstellfeder}, year = {2006}, abstract = {Die Erfindung betrifft einen elektromagnetischen Aktuator zur Bet{\"a}tigung eines Stellgliedes (7) mit wenigstens einem gesteuert bestrombaren Elektromagneten (1, 2) und einem mit dem Stellglied (7) in Wirkverbindung stehenden Anker (5), der bei Bestromung des Elektromagneten (1, 2) gegen die Kraft wenigstens einer an einem Geh{\"a}use (12) abgest{\"u}tzten R{\"u}ckstellfeder (10) an der Polfl{\"a}che (3, 4) des Elektromagneten (1, 2) zur Anlage kommt, und daß zumindest der Anker (5) {\"u}ber eine sph{\"a}rische Gelenkanordnung (11) auf der R{\"u}ckstellfeder (10) abgest{\"u}tzt ist.}, language = {de} } @inproceedings{HuthElsenHartwigetal.2006, author = {Huth, Thomas and Elsen, Olaf and Hartwig, Christoph and Esch, Thomas}, title = {Innovative modular valve trains for 2015 - logistic benefits by EMVT}, series = {IFAC Proceedings Volumes, Volume 39, Issue 3}, booktitle = {IFAC Proceedings Volumes, Volume 39, Issue 3}, publisher = {Elsevier}, address = {Amsterdam}, doi = {10.3182/20060517-3-FR-2903.00172}, pages = {315 -- 320}, year = {2006}, abstract = {In this paper the way to a 5-day-car with respect to a modular valve train systems for spark ignited combustion engines is shown. The necessary product diversity is shift from mechanical or physical components to software components. Therefore, significant improvements of logistic indicators are expected and shown. The working principle of a camless cylinder head with respect to an electromagnetical valve train (EMVT) is explained and it is demonstrated that shifting physical diversity to software is feasible. The future design of combustion engine systems including customisation can be supported by a set of assistance tools which is shown exemplary.}, language = {en} } @article{FunkeEschRoosen2022, author = {Funke, Harald and Esch, Thomas and Roosen, Petra}, title = {Antriebssystemanpassungen zur Verwendung von LPG als Flugkraftstoff}, series = {Motortechnische Zeitschrift (MTZ)}, volume = {2022}, journal = {Motortechnische Zeitschrift (MTZ)}, number = {83}, publisher = {Springer Nature}, address = {Basel}, doi = {10.1007/s35146-021-0778-2}, pages = {58 -- 62}, year = {2022}, abstract = {Auch in der allgemeinen Luftfahrt w{\"a}re es w{\"u}nschenswert, die bereits vorhandenen Verbrennungsmotoren mit weniger CO₂-tr{\"a}chtigen Kraftstoffen als dem heute weit verbreiteten Avgas 100LL betreiben zu k{\"o}nnen. Es ist anzunehmen, dass im Vergleich die unter Normalbedingungen gasf{\"o}rmigen Kraftstoffe CNG, LPG oder LNG deutlich weniger Emissionen produzieren. Erforderliche Antriebssystemanpassungen wurden im Rahmen eines Forschungsprojekts an der FH Aachen untersucht.}, language = {de} } @article{FayyaziSardarThomasetal.2023, author = {Fayyazi, Mojgan and Sardar, Paramjotsingh and Thomas, Sumit Infent and Daghigh, Roonak and Jamali, Ali and Esch, Thomas and Kemper, Hans and Langari, Reza and Khayyam, Hamid}, title = {Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles}, volume = {15}, number = {6}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/su15065249}, pages = {38}, year = {2023}, abstract = {Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.}, language = {en} }