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Computational Modeling of Slow Axonal Transport of NeurofilamentsLi, Yinyun 25 September 2013 (has links)
No description available.
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Sub-optimal Energy Management Architecture for Intelligent Hybrid Electric Bus : Deterministic vs. Stochastic DP strategy in Urban Conditions / Architecture de gestion de l'énergie sous-optimale pour les bus électriques hybrides intelligents : stratégie basée DP déterministe versus stratégie basée DP stochastique en milieu urbainAbdrakhmanov, Rustem 27 June 2019 (has links)
Cette thèse propose des stratégies de gestion de l'énergie conçues pour un bus urbain électrique hybride. Le système de commande hybride devrait créer une stratégie efficace de coordination du flux d’énergie entre le moteur thermique, la batterie, les moteurs électriques et hydrauliques. Tout d'abord, une approche basée sur la programmation dynamique déterministe (DDP) a été proposée : algorithme d'optimisation simultanée de la vitesse et de la puissance pour un trajet donné (limité par la distance parcourue et le temps de parcours). Cet algorithme s’avère être gourmand en temps de calcul, il n’a pas été donc possible de l’utiliser en temps réel. Pour remédier à cet inconvénient, une base de données de profils optimaux basée sur DP (OPD-DP) a été construite pour une application en temps réel. Ensuite, une technique de programmation dynamique stochastique (SDP) a été utilisée pour générer simultanément et d’une manière optimale un profil approprié de la vitesse du Bus ainsi que sa stratégie de partage de puissance correspondante. Cette approche prend en compte à la fois la nature stochastique du comportement de conduite et les conditions de circulations urbaines (soumises à de multiples aléas). Le problème d’optimisation énergétique formulé, en tant que problème intrinsèquement multi-objectif, a été transformé en plusieurs problèmes à objectif unique avec contraintes utilisant une méthode ε-constraint afin de déterminer un ensemble de solutions optimales (le front de Pareto).En milieu urbain, en raison des conditions de circulation, des feux de circulation, un bus rencontre fréquemment des situations Stop&Go. Cela se traduit par une consommation d'énergie accrue lors notamment des démarrages. En ce sens, une stratégie de régulation de vitesse adaptative adaptée avec Stop&Go (eACCwSG) apporte un avantage indéniable. L'algorithme lisse le profil de vitesse pendant les phases d'accélération et de freinage du Bus. Une autre caractéristique importante de cet algorithme est l’aspect sécurité, étant donné que l’ACCwSG permet de maintenir une distance de sécurité afin d’éviter les collisions et d’appliquer un freinage en douceur. Comme il a été mentionné précédemment, un freinage en douceur assure le confort des passagers. / This PhD thesis proposes Energy Management Strategies conceived for a hybrid electrical urban bus. The hybrid control system should create an efficient strategy of coordinating the flow of energy between the heat engine, battery, electrical and hydraulic motors. Firstly, a Deterministic Dynamic Programming (DDP) based approach has been proposed: simultaneous speed and powersplit optimization algorithm for a given trip (constrained by the traveled distance and time limit). This algorithm turned out to be highly time consuming so it cannot be used in real-time. To overcome this drawback, an Optimal Profiles Database based on DP (OPD-DP) has been constructed for real-time application. Afterwards, a Stochastic Dynamic Programming (SDP) technique is used to simultaneously generate an optimal speed profile and related powersplit strategy. This approach takes into account a stochastic nature of the driving behavior and urban conditions. The formulated energy optimization problem, being intrinsically multi-objective problem, has been transformed into several single-objective ones with constraints using an ε-constraint method to determine a set of optimal solutions (the Pareto Front).In urban environment, due to traffic conditions, traffic lights, a bus encounters frequent Stop&Go situations. This results in increased energy consumption during the starts. In this sense, a relevant Eco Adaptive Cruise Control with Stop&Go (eACCwSG) strategy brings the undeniable benefit. The algorithm smooths speed profile during acceleration and braking phases. One more important feature of this algorithm is the safety aspect, as eACCwSG permits to maintain a safety distance in order to avoid collision and apply a smooth braking. As it was mentioned before, smooth braking ensures passengers comfort.
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Validierung einer spezialisierten Studiendatenanalyse für Mobilitätsindikatoren durch Desktop-GISTümmler, Bartholomeus 03 May 2023 (has links)
In dieser Arbeit wurde eine Studiendatenanalyse der TU Berlin zur Analyse von menschlichen Bewegungsdaten der Studie Mobil im Havelland der Charité Berlin anhand von Mobilitätsindikatoren auf Grundlage von zwei Testdatensätzen mithilfe der Desktop-GIS ArcGIS Pro und QGIS validiert. Des Weiteren wurde in dieser Arbeit anhand der Auswertungsergebnisse der Desktop-GIS ArcGIS Pro und QGIS diskutiert, inwieweit sich Analysen von Bewegungsdaten anhand von Mobilitätsindikatoren auch unter einem preissensiblen Anspruch mit einem Open-Source-System wie QGIS off the shelf durchführen lassen.
Die Validierung hat ergeben, dass die Studiendatenanalyse der TU Berlin im Vergleich mit den Desktop-GIS gleichwertige und zum Teil sogar höherwertigere Ergebnisse generieren konnte. Vor allem der auf neuartige Verfahren aufbauende Stop & Go Classifier der Studiendatenanalyse der TU Berlin konnte mit seiner Performance bei der Detektion von Verweilorten überzeugen. Somit kann der Studiendatenanalyse der TU Berlin ohne Einschränkungen eine Eignung für die Auswertung der Bewegungsdaten der Studie Mobil im Havelland bescheinigt werden. In Bezug auf den Vergleich der Desktop-GIS kann festgehalten werden, dass solche Analysen mit QGIS möglich sind. Eine Umsetzung mit off the shelf Verfahren ist aber vor allem in Bezug auf den zentralen Aspekt der Detektion von Verweilorten bis dato mit QGIS nicht gewährleistet. Hier muss auf externe Python-Bibliotheken wie MovingPandas oder Scikit-mobility zurückgegriffen werden. / In this paper, a study data analysis of the TU Berlin for the analysis of human movement data of the study Mobil im Havelland based on mobility indicators is validated on the basis of two test data sets using the desktop GIS ArcGIS Pro and QGIS. Furthermore, this paper uses the evaluation results of the desktop GIS ArcGIS Pro and QGIS to discuss the extent to which analyses of movement data using mobility indicators can also be carried out off the shelf with an OSS such as QGIS under a price-sensitive claim.
The validation showed that the TU Berlin's study data analysis was able to generate equivalent and in some cases even higher quality results compared to desktop GIS. The performance of the TU Berlin's Stop & Go Classifier, which is based on innovative procedures, was particularly convincing. Thus, the study data analysis of the TU Berlin can be certified without restrictions as suitable for the evaluation of the movement data of the study Mobile in Havelland. With regard to the comparison of desktop GIS, it can be stated that such analyses are possible with QGIS. However, an implementation with off-the-shelf methods is not yet guaranteed with QGIS, especially with regard to the central aspect of the detection of dwelling places. However, external Python libraries such as MovingPandas or scikit-mobility can be used here.
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Design and Formal Verification of an Adaptive Cruise Control Plus (ACC+) SystemVakili, Sasan January 2015 (has links)
Stop-and-Go Adaptive Cruise Control (ACC+) is an extension of Adaptive Cruise Control (ACC) that works at low speed as well as normal highway speeds to regulate the speed of the vehicle relative to the vehicle it is following. In this thesis, we design an ACC+ controller for a scale model electric vehicle that ensures the robust performance of the system under various models of uncertainty. We capture the operation of the hybrid system via a state-chart model that performs mode switching between different digital controllers with additional decision logic to guarantee the collision freedom of the system under normal operation. We apply different controller design methods such as Linear Quadratic Regulator (LQR) and H-infinity and perform multiple simulation runs in MATLAB/Simulink to validate the performance of the proposed designs. We compare the practicality of our design with existing formally verified ACC designs from the literature. The comparisons show that the other formally verified designs exhibit unacceptable behaviour in the form of mode thrashing that produces excessive acceleration and deceleration of the vehicle.
While simulations provide some assurance of safe operation of the system design, they do not guarantee system safety under all possible cases. To increase confidence in the system, we use Differential Dynamic Logic (dL) to formally state environmental assumptions and prove safety goals, including collision freedom. The verification is done in two stages. First, we identify the invariant required to ensure the safe operation of the system and we formally verify that the invariant preserves the safety property of any system with similar dynamics. This procedure provides a high level abstraction of a class of safe solutions for ACC+ system designs. Second, we show that our ACC+ system design is a refinement of the abstract model. The safety of the closed loop ACC+ system is proven by verifying bounds on the system variables using the KeYmaera verification tool for hybrid systems. The thesis demonstrates how practical ACC+ controller designs optimized for fuel economy, passenger comfort, etc., can be verified by showing that they are a refinement of the abstract high level design. / Thesis / Master of Applied Science (MASc)
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