Identification of multi-faults in GNSS signals using RSIVIA under dual constellation

This publication presents the development of integrity monitoring and fault detection and exclusion (FDE) of pseudorange measurements, which are used to aid a tightly-coupled navigation filter. This filter is based on an inertial measurement unit (IMU) and is aided by signals of the global navigation satellite system (GNSS). Particularly, the GNSS signals include global positioning system (GPS) and Galileo. By using GNSS signals, navigation systems suffer from signal interferences resulting in large pseudorange errors. Further, a higher number of satellites with dual-constellation increases the possibility that satellite observations contain multiple faults. In order to ensure integrity and accuracy of the filter solution, it is crucial to provide sufficient fault-free GNSS measurements for the navigation filter. For this purpose, a new hybrid strategy is applied, combining conventional receiver autonomous integrity monitoring (RAIM) and innovative robust set inversion via interval analysis (RSIVIA). To further improve the performance, as well as the computational efficiency of the algorithm, the estimated velocity and its variance from the navigation filter is used to reduce the size of the RSIVIA initial box. The designed approach is evaluated with recorded data from an extensive real-world measurement campaign, which has been carried out in GATE Berchtesgaden, Germany. In GATE, up to six Galileo satellites in orbit can be simulated. Further, the signals of simulated Galileo satellites can be manipulated to provide faulty GNSS measurements, such that the fault detection and identification (FDI) capability can be validated. The results show that the designed approach is able to identify the generated faulty GNSS observables correctly and improve the accuracy of the navigation solution. Compared with traditional RSIVIA, the designed new approach provides a more timely fault identification and is computationally more efficient

Scientific Railway Signalling Symposium 2018 - Digital neue Wege fahren

Die Leit- und Sicherungstechnik (LST) ist für die Durchführung von Zugfahrten von kritischer Bedeutung. Von ihr hängen nicht nur die Sicherheit von Fahrgästen, Fracht und Infrastruktureinrichtungen ab, sondern auch die Kapazität der Infrastruktur. Digitalisierung ist das Schlagwort der Stunde. Es ist die Klammer für zahllose innovative Ideen, die das System Eisenbahn revolutionieren sollen. Allen Akteuren ist klar, dass auch und gerade im Bereich der Leit- und Sicherungstechnik Veränderungen kommen werden und notwendig sind, um die Wettbewerbsfähigkeit des Verkehrsträgers Eisenbahn zu erhalten und dessen nachhaltigen Beitrag zum Erreichen der Klimaziele zu sichern. Doch noch ist unklar, welche Veränderungen sich wirklich in den kommenden Jahren durchsetzen werden und welche in absehbarer Zeit nur Luftschlösser bleiben. Um diese Herausforderungen zu meistern ist ein intensiver Austausch aller Beteiligten notwendig, insbesondere auch zwischen Wissenschaft und Praxis. Diesem Ziel widmete sich das 2. Scientific Railway Signalling Symposium am 13. Juni 2018 in Darmstadt. Der Tagungsband enthält vier wissenschaftliche Beiträge des Symposiums

Model-Based Emission Control of a Compression Ignition Engine

There is an ongoing need for investigation of clean and efficient combustion processes, within the automotive sector in particular, as combustion engines will remain an important power source for the next decades. Therefore, the development of new combustion processes and adequate combustion control strategies is required to fulfill the increasing demands regarding comfort, driveability, and eco-friendliness. Overall objectives are the reduction of pollutants without efficiency loss. In this context, low-temperature combustion (LTC) is a promising alternative to conventional diesel combustion (CDC), during part-load Operation in particular. LTC is characterized by advanced injection timings and higher amounts of recirculated exhaust gas (EGR). Hence, LTC lacks a direct trigger for the start of combustion (SOC) and tends to an incomplete and unstable combustion. Therefore, combustion control is essential. This thesis focuses on the research of sophisticated control approaches for automotive compression-ignition (CI) engines applying LTC. Challenges are the determination of relevant correlations among actuators and engine responses, the adequate modeling of these relations as a basis for model-based control methods, and the control of the complex, coupled, and non-linear combustion system. The control objective is the reduction of nitrogen oxides (NOx) in a new and direct way considering unburnt hydrocarbons (THC) emissions as well. The presented cycle-based approach allows a combustion with less pollutants and equal or higher efficiency level than CDC. Experiments and evaluations are carried out with a four-cylinder engine on a test bench. The results are presented and discussed. Finally, a further control approach is introduced, which is able to influence the combustion and the corresponding pollutant formation more directly within the combustion cycle. Therefore, a rate-shaping capable injector system is combined with a model-based iterative learning method to adjust the in-cyclevariant fuel rate. The potential of this new method is evaluated in simulations