Global ETD Search

331	Fuzzy-Rule-Based Failure Detection and Early Warning System for Lithium-ion Battery Wu, Meng 05 September 2013 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / Lithium-ion battery is one kind of rechargeable battery, and also renewable, sustainable and portable. With the merits of high density, slow loss of charge when spare and no memory effect, lithium-ion battery is widely used in portable electronics and hybrid vehicles. Apart from its advantages, safety is a major concern for Lithium-ion batteries due to devastating incidents with laptop and cell phone batteries. Overcharge and over-discharge are two of the most common electrical abuses a lithium-ion battery suffers. In this thesis, a fuzzy-rule-based system is proposed to detect the over-charge and over-discharge failure in early time. The preliminary results for the failure signatures of overcharged and over-discharged lithium-ion are listed based on the experimental results under both room temperature and high temperature. A fuzzy-rule-based model utilizing these failure signatures is developed and validated. For over-charge case, the abnormal increase of the surface temperature and decrease of the voltage are captured. While for over discharge case, unusual temperature increase during overcharge phases and abnormal current decrease during overcharge phases are obtained. The inference engine for fuzzy-rule-based system is designed based on these failure signatures. An early warning signal will be given by this algorithm before the failure occurs. This failure detection and early warning system is verified to be effective through experimental validation. In the validation test, the proposed methods are successfully implemented in a real-time system for failure detection and early warning. The result of validation is compatible with the design expectation. Finally an accurate failure detection and early warning system is built and tested successfully. Lithium ion batteries Electric vehicles Hybrid electric vehicles Motor vehicles -- Energy conservation Fuzzy systems Electric power system stability Real-time control Sustainable engineering -- Research Electric power systems -- Control
332	Analysis and Design of Stable and Optimal Energy Management Strategies for Hybrid Electric Vehicles Sampathnarayanan, Balaji January 2012 (has links) No description available. Alternative Energy Automotive Engineering Electrical Engineering Mechanical Engineering hybrid electric vehicles pre-transmission parallel hev energy management strategies optimal control law constrained optimization problem
333	Novel Computational Methods for the Reliability Evaluation of Composite Power Systems using Computational Intelligence and High Performance Computing Techniques Green, Robert C., II 24 September 2012 (has links) No description available. Artificial Intelligence Computer Science Electrical Engineering State space pruning Monte Carlo simulation Power system reliability Plug-in hybrid electric vehicle Ant colony optimization Particle swarm optimization Latin hypercube sampling Low discrepancy sequences
334	ASEMS: Autonomous Specific Energy Management Strategy Amirfarhangi Bonab, Saeed January 2019 (has links) This thesis addresses the problem of energy management of a hybrid electric power unit for an autonomous vehicle. We introduce, evaluate, and discuss the idea of autonomous-specific energy management strategy. This method is an optimization-based strategy which improves the powertrain fuel economy by exploiting motion planning data. First, to build a firm base for further evaluations, we will develop a high-fidelity system-level model for our case study using MATLAB/Simulink. This model mostly concerns about energy-related aspects of the powertrain and the vehicle. We will derive and implement the equations for each of the model subsystems. We derive model parameters using available data in the literature or online. Evaluation of the developed model shows acceptable conformity with the actual dynamometer data. We will use this model to replace the built-in rule-based logic with the proposed strategy and assess the performance.\par Second, since we are considering an optimization-based approach, we will develop a novel convex representation of the vehicle and powertrain model. This translates to reformulating the model equations using convex functions. Consequently, we will express the fuel-efficient energy management problem as the convex optimization problem. We will solve the optimization problem using dedicated numerical solvers. Extracting the control inputs using this approach and applying them on the high-fidelity model provides similar results to dynamic programming in terms of fuel consumption but in substantially less amount of time. This will act as a pivot for the subsequent real-time analysis.\par Third, we will perform a proof-of-concept for the autonomous-specific energy management strategy. We implement an optimization-based path and trajectory planning for a vehicle in the simplified driving scenario of a racing track. Accordingly, we use motion planning data to obtain the energy management strategy by solving an optimization problem. We will let the vehicle to travel around the circuit with the ability to perceive and plan up to an observable horizon using the receding horizon approach. Developed approach for energy management strategy shows a substantial reduction in the fuel consumption of the high-fidelity model, compared to the rule-based controller. / Thesis / Master of Science in Mechanical Engineering (MSME) / The automotive industry is on the verge of groundbreaking transformations as a result of electrification and autonomous driving. Electrified autonomous car of the future is sustainable, energy-efficient, more convenient, and safer. In addition to the advantages of electrification and autonomous driving individually, the intersection and interaction of these mainstreams provide new opportunities for further improvements on the vehicles. Autonomous cars generate an unprecedented amount of real-time data due to excessive use of perception sensors and processing units. This thesis considers the case of an autonomous hybrid electric vehicle and presents the novel idea of autonomous-specific energy management strategy. Specifically, this thesis is a proof-of-concept, a trial to exploit the motion planning data for a self-driving car to improve the fuel economy of the hybrid electric power unit by adopting a more efficient energy management strategy. With the ever-increasing number of autonomous hybrid electric vehicles, particularly in the self-driving fleets, the presented method shows an extremely promising potential to reduce the fuel consumption of these vehicles. Autonomous Vehicle Hybrid Electric Vehicle Autonomous Driving Energy Management Strategy Self-driving car Optimization Convex Optimization Electrification Sustainability Optimal Control Model Predictive Control Receding Horizon Fuel Economy Path Planning Trajectory Planning Powertrain
335	<b>OPTIMIZATION OF ENERGY MANAGEMENT STRATEGIES FOR FUEL-CELL HYBRID ELECTRIC AIRCRAFT</b> Ayomide Samuel Oke (14594948) 23 April 2024 (has links) <p dir="ltr">Electric aircraft offer a promising avenue for reducing aviation's environmental impact through decreased greenhouse gas emissions and noise pollution. Nonetheless, their adoption is hindered by the challenge of limited operational range. Addressed in the study is the range limitation by integrating and optimizing multiple energy storage components—hydrogen fuel cells, Li-ion batteries, and ultracapacitors—through advanced energy management strategies. Utilizing meta-heuristic optimization methods, the research assessed the dynamic performance of each energy component and the effectiveness of the energy management strategy, primarily measured by the hydrogen consumption rate. MATLAB simulations validated the proposed approach, indicating a decrease in hydrogen usage, thus enhancing efficiency and potential cost savings. Artificial Gorilla Troop Optimization yielded the best results with the lowest average hydrogen consumption rate (102.62 grams), outperforming Particle Swarm Optimization (104.68 grams) and Ant Colony Optimization (105.96 grams). The findings suggested that employing a combined energy storage and optimization strategy can significantly improve the operational efficiency and energy conservation of electric aircraft. The study highlighted the potential of such strategies to extend the range of electric aircraft, contributing to a more sustainable aviation future.</p> Energy Management Strategies Fuel cell Electric Aircraft Ant Colony Optimization algorithm (ACO) Artificial Gorilla Troop Optimization Hybrid electric aircraft
336	Modular Vehicle Design Concept Rue, Timothy James 23 January 2015 (has links) Outlined herein is the Modular Vehicle [MODV] concept as a cost effective, utilitarian, and highly functional vehicle concept for the changing demands placed on a MAGTF [Marine Air-Ground Task Force] or SP-MAGTF [Special Purpose Marine Air-Ground Task Force] in the 21st century. A large focus is put on the importance of modularity and cost effectiveness of having a 24 hour configurable vehicle to a specific mission and area of operation. Off-road vehicle progression through history is presented and successful design features are noted in order to develop underlying goals for the modular vehicle. The thesis emphasizes recent technology advancements that can shift the foundations of vehicle design including wheel hub motors, high capacity batteries, solid oxide fuel cells, autonomy, structural health monitoring, energy harvesting shock absorbers, non-pneumatic tires, and drive-by-wire options. Predictions on the outlook for the technology progressions is discussed to give insight into the viability of basing a vehicle concept on these technologies. Finally, physical design bounds are presented to provide a foundation for the future design of such a vehicle. / Master of Science Hybrid-Electric Vehicle Autonomy Wheel Hub Motors Vehicle Concept Logistics Demand Reduction Expeditionary Power Silent Operation Batteries Solid Oxide Fuel Cells Structural Health Monitoring Energy Harvesting Shock Absorbers Non-pneumatic
337	Assessing the potential of fuel saving and emissions reduction of the bus rapid transit system in Curitiba, Brazil Dreier, Dennis January 2015 (has links) The transport sector contributes significantly to global energy use and emissions due to its traditional dependency on fossil fuels. Climate change, security of energy supply and increasing mobility demand is mobilising governments around the challenges of sustainable transport. Immediate opportunities to reduce emissions exist through the adoption of new bus technologies, e.g. advanced powertrains. This thesis analysed energy use and carbon dioxide (CO2) emissions of conventional, hybrid-electric, and plug-in hybrid-electric city buses including two-axle, articulated, and biarticulated chassis types (A total of 6 bus types) for the operation phase (Tank-to-Wheel) in Curitiba, Brazil. The systems analysis tool – Advanced Vehicle Simulator (ADVISOR) and a carbon balance method were applied. Seven bus routes and six operation times for each (i.e. 42 driving cycles) are considered based on real-world data. The results show that hybrid-electric and plug-in hybrid-electric two-axle city buses consume 30% and 58% less energy per distance (MJ/km) compared to a conventional two-axle city bus (i.e. 17.46 MJ/km). Additionally, the energy use per passenger-distance (MJ/pkm) of a conventional biarticulated city bus amounts to 0.22 MJ/pkm, which is 41% and 24% lower compared to conventional and hybrid-electric two-axle city buses, respectively. This is mainly due to the former’s large passenger carrying capacity. Large passenger carrying capacities can reduce energy use (MJ/pkm) if the occupancy rate of the city bus is sufficient high. Bus routes with fewer stops decrease energy use by 10-26% depending on the city bus, because of reductions in losses from acceleration and braking. The CO2 emissions are linearly proportional to the estimated energy use following from the carbon balance method, e.g. CO2 emissions for a conventional two-axle city bus amount to 1299 g/km. Further results show that energy use of city bus operation depends on the operation time due to different traffic conditions and driving cycle characteristics. An additional analysis shows that energy use estimations can vary strongly between considered driving cycles from real-world data. The study concludes that advanced powertrains with electric drive capabilities, large passenger carrying capacities and bus routes with a fewer number of bus stops are beneficial in terms of reducing energy use and CO2 emissions of city bus operation in Curitiba. advanced powertrain Advanced Vehicle Simulator ADVISOR Brazil BRT bus rapid transit carbon dioxide CO2 city bus Curitiba driving cycle emissions energy consumption energy efficiency energy use fuel economy hybrid propulsion hybrid-electric parallel hybrid passenger carrying capacity plug-in hybrid-electric Tank-to-Wheel analysis vehicle simulation Analyse Brasilien Emissionen Energieeffizienz Energienutzung Energieverbrauch Fahrzeugsimulation Fahrzeugwirkungsgrad Fahrzyklus Fortschrittlicher Antriebsstrang Hybridantrieb Hybridelektrofahrzeug Kohlenstoffdioxid Kraftstoffverbrauch Passagiertransportkapazität Schnellbussystem Stadtbus Steckdosen-Hybrid Vollhybrid analys bränsleförbrukning drivlina energianvändning energieffektivit energiförbrukning fordonssimulering hybriddrift koldioxidutsläpp körcykel laddhybrid passagerarkapacitet stadsbuss strombuss Energy Engineering Energiteknik Energy Systems Energisystem Vehicle Engineering Farkostteknik
338	Réjection de perturbation sur un système multi-sources - Application à une propulsion hybride / Disturbance rejection of hybrid energy sources applied in hybrid electric vehicles Dai, Ping 19 January 2015 (has links) Ce mémoire porte sur l'étude d'un système de gestion d'énergie électrique dans un système multi-sources soumis à des perturbations exogènes. L'application visée est l'alimentation d'une propulsion hybride diesel/électrique équipée d'un système d'absorption des pulsations de couple. Les perturbations exogènes considérées peuvent être transitoires ou persistantes. Une perturbation transitoire correspond à une variation rapide du couple de charge, due par exemple à une accélération ou une décélération du véhicule. Une perturbation persistante provient du système de compensation des pulsations de couple générées par le moteur thermique. Le premier objectif du contrôle est de maintenir constante la tension du bus continu. Le deuxième objectif est d'absorber dans un système de stockage rapide constitué de super condensateur ces perturbations qui peuvent à terme provoquer une usure prématurée de la batterie. Le troisième objectif est de compenser l'auto-décharge dans le super condensateur en maintenant constante sa tension nominale. Les deux sources (batterie et super condensateur) sont reliées au bus continu par l'intermédiaire de deux convertisseurs boost DC/DC. La commande consiste à piloter les rapports cycliques de chaque convertisseur. C'est un système non linéaire où la commande est multiplicative de l'état. L'approche classique consistant à résoudre les équations Francis-Byrnes-Isidori ne s'applique pas directement dans ce cas où la sortie et la matrice d'interconnection dépendent de la commande. De plus, si cette approche est bien adaptée au rejet de perturbations persistantes, elle montre ces limites pour le rejet de perturbations non persistantes combiné à des objectifs de régulation. Notre approche a consisté à écrire le système sous un formalisme Port-Controlled Hamiltonian et à s'affranchir de la contrainte de la dépendance de la matrice d'interconnection avec la commande en utilisant la théorie des perturbations singulières. La commande du système dégénéré peut ensuite être calculée par une approche passive. Les performances de cette commande ont été testées en simulation et à l'aide d'un banc d'essai expérimental. Les résultats montrent l'efficacité du système d'absorption des différents types de perturbation tout en respectant les deux objectifs de régulation. / This thesis presents the research of energy management in a battery/ultracapacitor hybrid energy storage system with exogenous disturbance in hybrid electric vehicular application. Transient and harmonic persistent disturbances are the two kinds of disturbances considered in this thesis. The former is due to the transient load power demand during acceleration and deceleration, and the latter is introduced from the process of the internal combustion engine torque ripples compensation. Our control objective is to absorb the disturbances causing battery wear via the ultracapacitor, and meanwhile, to maintain a constant DC voltage and to compensate the self-discharge in the ultracapacitor to maintain it operating at the nominal state of charge. The object system is nonlinear due to the multiplicative relation between the input and the state. The traditional approach to solve Francis-Byrnes-Isidori equations cannot be directly applied in this case since the interconnect matrix depends on the control input. Besides, even if this approach is well suited to the rejection of persistent disturbances, it shows the limits for the case of non-persistent disturbances which is also our object. Our contributed control method is realized through a cascade control structure based on the singular perturbation theory. The ultracapacitor current with the fastest motion rate is controlled in the inner fast loop through which we impose the desired dynamic to the system. The reduced system controlled in the outer slow loop is a Hamiltonian system and the controller is designed via interconnection and damping assignment. Simulations and experiments have been carried out to evaluate the control performance. A contrast of the system responses with and without the control algorithm shows that, with the control algorithm, the ultracapacitor effectively absorbs the disturbances; and verifies the effectiveness of the control algorithm. Véhicules hybrides électriques Système multi-Source Gestion d'énergie Rejet des perturbations persistantes Régulation de sortie Formalisme Port-Controlled Hamiltonian Perturbations singulières Hybrid electric vehicles Hybrid energy storage system Energy management Persistent disturbance rejection Output regulation Port-Controlled Hamiltonian system Singular perturbation theory 629.8
339	Optimisation énergétique de chaînes de traction hybrides essence et Diesel sous contrainte de polluants : Étude et validation expérimentale / Energy Optimization of Gasoline and Diesel Hybrid Powertrains with Pollutant Constraints : Study and Experimental Validation Simon, Antoine 05 July 2018 (has links) L’hybridation électrique de la chaîne de traction automobile est l’une des solutions adoptées pour respecter les règlementations futures sur ses émissions. La stratégie de supervision de la chaîne de traction hybride répartit la puissance produite par le moteur à combustion interne et la machine électrique. Elle répond habituellement à un problème d’optimisation où l’objectif est de réduire la consommation de carburant mais nécessite à présent d’y ajouter les émissions polluantes. La chaîne de dépollution, placée à l’échappement du moteur, permet de diminuer la quantité de polluants émise dans l’atmosphère. Cependant, elle n’est efficace qu’à partir d’un seuil de température, et dépend de la chaleur apportée par les gaz d’échappement du moteur thermique. La première partie de ce travail est donc consacrée à la modélisation de la consommation énergétique et des émissions polluantes de la chaine de traction hybride. La modélisation de l’efficacité de la chaîne de dépollution est réalisée selon deux contextes. Le modèle zéro-dimensionnel est adapté aux contraintes de calcul de la commande optimale. Le modèle unidimensionnel associé à un estimateur d’état permet d’être embarqué et calculé en temps réel. À partir de ces travaux, la seconde partie de cette thèse déduit des stratégies de supervision à l’aide de la théorie de la commande optimale. Dans un premier cas, le principe de Bellman permet de calculer la commande optimale d’un véhicule hybride Diesel selon des critères de supervision ayant plus ou moins connaissance de l’efficacité de la chaîne de dépollution des émissions de NOX. Dans un second cas, une stratégie issue du Principe du Minimum de Pontryagin, embarquée sur un véhicule hybride essence, fonctionnant en temps réel et calibrée selon deux paramètres est proposée. L’ensemble de ces travaux est validé expérimentalement au banc moteur et montre une réduction significative des émissions polluantes pour une faible pénalité de carburant. / Powertrain hybridization is a solution that has been adopted in order to conform to future standards for emissions regulations. The supervisory strategy of the hybrid powertrain divides the power emitted between the internal combustion engine and the electric machine. In past studies, this strategy has typically responded to an optimization problem with the objective of reducing consumption. However, in addition to this, it is now necessary to take pollutant emissions into account as well. The after-treatment system, placed in the exhaust of the engine, is able to reduce pollutants emitted into the atmosphere. It is efficient from a certain temperature threshold, and the temperature of the system is dependent on the heat brought by the exhaust gas of the engine. The first part of this dissertation is aimed at modelling the energy consumption and pollutant emissions of the hybrid powertrain. The efficiency model of the after-treatment system is adapted for use in two different contexts. The zero-dimensional model conforms to the constraints of the optimal control calculation. The one-dimensional model associated with a state estimator can be embedded in a vehicle and calculated in real time. From this work, the second part of this dissertation deduces supervisory strategies from the optimal control theory. On the one hand, Bellman’s principle is used to calculate the optimal control of a Diesel hybrid vehicle using different supervisory criteria, each having more or less information about the after-treatment system efficiency over NOX emissions. On the other hand, a strategy from Pontryagin’s minimum principle, embedded in a gasoline hybrid vehicle, running in real time and calibrated with two parameters, is proposed. The whole of this work is validated experimentally on an engine test bed and shows a significant reduction in pollutant emissions for a slight fuel consumption penalty. Véhicule hybride électrique Moteur essence Catalyseur 3-voies Moteur Diesel Catalyseur d’oxydation, Réduction catalytique sélective Optimisation énergétique Émissions polluantes Estimation Commande optimale Principe de Bellman Programmation dynamique Principe du minimum de Pontryagin Hybrid Electric Vehicle Gasoline Engine 3-Way Catalytic Converter Diesel Engine Diesel Oxidation Catalyst Selective Catalytic Reduction Energy Optimization Pollutant Emissions Estimation Optimal Control Bellman’s Principle Dynamic Programming Pontryagin’s Minimum Principle 621.436 621.46
340	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 urbain Abdrakhmanov, 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. Véhicule électrique hybride Gestion de l’énergie Programmation dynamique Programmation dynamique stochastique MPC stochastique Base de données multidimensionnelle ACC avec Stop&Go Hybrid Electric Vehicle Energy Management Strategy Dynamic Programming based optimization Stochastic Dynamic Programming Stochastic MPC Multi-Dimensional Database ACC with Stop&Go

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