Tesis sobre el tema "Battery state-of-health"
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Grube, Ryan J. "Automotive Battery State-of-Health Monitoring Methods". Wright State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=wright1229787557.
Texto completoSöderhielm, Camilla. "Investigation of Battery Parameters for Li-ion Battery State of Health Estimation". Thesis, KTH, Kemiteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299432.
Texto completoEnvironmental concerns associated with greenhouse gas emissions from conventional combustion engines have contributed to a transition towards electric mobility. In this transition, lithium-ion (Li-ion) batteries play an important part as an energy storage system. However, Li-ion batteries can pose a safety risk due to their reactive chemistry. The Swedish Armed Forces are approaching a transition towards electric mobility, therefore, understanding Li-ion battery behavior with regard to non-normal use and ageing is critical for safe military applications. This project aimed to identify and evaluate battery parameters (impedance, resistance, capacity and surface temperature) suitable for State of Health (SOH) estimation of Li-ion batteries in military applications. Furthermore, this project aimed to investigate the ambient temperature’s effect on battery parameters, and identify the battery’s end of life (EOL) based on battery parameter tracking. Commercial NMC/graphite Li-ion batteries were exposed to ageing through repeated charge and discharge cycles. A critical application was mimicked, where the batteries operated at 1C charge rate (4 A) and 2.5C discharge rate (10 A) between 100 % and 0 % state of charge, for up to 250 charge/discharge cycles. The ageing process was tracked through regular measurements of impedance, resistance, capacity and surface temperature. In order to investigate the ambient temperature’s effect on the investigated battery parameters, the batteries were aged at either 52 ± 3 °C, 21 ± 3 °C or −15 ± 3 °C. Impedance measured at 980 Hz was the most stable battery parameter with respect to variations in state of charge and temperature, and was therefore regarded as the most suitable parameter for SOH estimation with respect to flexibility. Measurements of resistance and capacity at given temperatures were likely reflecting electrochemical ageing phenomena more accurately, hence the most suitable battery parameters for SOH estimation with respect to accuracy. Tracking of surface temperature provided insufficient information for accurate estimation of the batteries SOH. Decreasing the ambient temperature from 21 °C to −15 °C had a major effect on capacity and resistance; the resistance increased and the capacity decreased, corresponding to a decrease in battery performance. With respect to capacity fade, neither of the batteries aged at 21 °C reached their EOL within 250 cycles, while batteries aged at 52 °C or −15 °C reached their EOL after 150–200 cycles. With respect to resistance, one battery kept at 21 °C reached their EOL after 200 cycles, all batteries kept at 52 °C reached their EOL after 150–200 cycles, and batteries kept at −15 °C reached their EOL between 200–250 cycles. Finally, with respect to impedance measured at 980 Hz, one battery kept at 21 °C reached their EOL after 200 cycles, one battery kept at 52 °C reached their EOL after 150 cycles, and batteries kept at −15 °C reached their EOL between 200–250 cycles.
Kerley, Ross Andrew. "Automotive Lead-Acid Battery State-of-Health Monitoring System". Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/64870.
Texto completoMaster of Science
Suozzo, Christopher. "Lead-Acid Battery Aging and State of Health Diagnosis". The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1212002134.
Texto completoSamolyk, Mateusz y Jakub Sobczak. "Development of an algorithm for estimating Lead-Acid Battery State of Charge and State of Health". Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2937.
Texto completoI detta papper, är ett laddningstillstånd (SOC) och hälsotillstånd (SOH) skattningsmetod för blybatterier presenteras. I algoritmen mätningarna av batteriets polspänning, ström och temperatur används i processen för SOC beräkning. Avhandlingen är skriven i samarbete med Micropower AB. Algoritmen har utformats för att uppfylla de särskilda kraven för elektriska fordon: ett fel under 5% av SOC, computational enkelhet och möjligheten att genomföras i ett grundläggande programmeringsspråk. Den nuvarande metoden vid Micropower, Coulomb räkning, jämförs med en metod som presenteras av Chiasson och Vairamohan 2005 baserad på modifierad Thevein kretsen under laddning och urladdning av batteriet.
Salyer, Zachary M. "Identification of Optimal Fast Charging Control based on Battery State of Health". The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587037951166857.
Texto completoCordoba, Arenas Andrea Carolina. "Aging Propagation Modeling and State-of-Health Assessment in Advanced Battery Systems". The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385967836.
Texto completoKlass, Verena. "Battery Health Estimation in Electric Vehicles". Doctoral thesis, KTH, Tillämpad elektrokemi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-173544.
Texto completoQC 20150914
Schmidt, Alexander Patrick [Verfasser]. "A Novel Electrochemical Battery Model For State Of Charge And State Of Health Estimation / Alexander Patrick Schmidt". Aachen : Shaker, 2010. http://d-nb.info/1084536315/34.
Texto completoHyun, Ji Hoon. "State of Health Estimation System for Lead-Acid Car Batteries Through Cranking Voltage Monitoring". Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71796.
Texto completoMaster of Science
Juhlin, Olof. "Modeling of Battery Degradation in Electrified Vehicles". Thesis, Linköpings universitet, Fordonssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-134114.
Texto completoQuintero, Cedeño Vanessa Lisbeth. "Design of a medium-access-control protocol for wireless sensor networks considering the battery state of charge and state of health". Tesis, Universidad de Chile, 2019. http://repositorio.uchile.cl/handle/2250/170130.
Texto completoLa disponibilidad de energía es una de las limitaciones que presentan las Redes de Sensores Inalámbricas (WSN, Wireless Sensor Network). Tradicionalmente, las baterías han sido utilizadas para proveer energía a los nodos de sensores y al tener una vida útil limitada afectan el tiempo de vida de la red. Soluciones como el uso de baterías de gran tamaño o el reemplazo de ellas no son viables, debido al gran número de sensores que componen la red y a que pueden ser desplegados en zonas de difícil acceso. Esta situación ha motivado que las soluciones para la conservación de la energía en las WSNs se enfoquen en el desarrollo de técnicas que actúen a nivel de las capas física y de enlace de datos, como es el caso de los protocolos de Control de Acceso al Medio (MAC, Medium Access Control). Los protocolos MAC son una de las soluciones ampliamente estudiadas y utilizadas porque permiten un equilibrio entre la conservación de energía y otros parámetros críticos de la red, como el rendimiento, latencia, reducción de colisiones y mensajes de control. También tienen la facilidad de adaptarse a las nuevas aristas de trabajo que surgen al incorporar nuevas tecnologías como lo son los Dispositivos de Recolección de Energía (EHD, Energy Harvesting Device). Otro aspecto que está siendo considerado y estudiado en el diseño de los protocolos MAC es la información que se puede extraer de la batería, ya que al estimar la capacidad disponible de la misma, el mecanismo del Duty Cycling (DuC) puede ser ajustado con el propósito de aumentar la eficiencia energética y por lo tanto, extender la vida útil de la red. Es necesario desarrollar técnicas que incorporen un mecanismo de conservación de energía que integre información de la batería a través de indicadores como el Estado de Carga (SOC, State of Charge) y Estado de Salud (SOH, State of Health) para mejorar la eficiencia energética en WSN. La idea de incorporar información de la batería se debe a que la capa MAC está a cargo de controlar los modos de operación del nodo sensor, lo que está directamente relacionado con la cantidad de corriente exigida a la batería. Conocidos los perfiles de uso de la batería es posible estimar los indicadores SOC y SOH que se han utilizado ampliamente en diversas aplicaciones para conocer la cantidad de energía disponible en la batería y la degradación que ha sufrido la misma. En este trabajo se propuso el desarrollo de un protocolo que actúa en la subcapa MAC y que considera la información de la batería para tomar decisiones con respecto al tiempo activo y de reposo del nodo de sensor, con la finalidad de promover el uso eficiente de la energía y extender la vida útil de la red. Los resultados obtenidos validan esta nueva propuesta de algoritmo y establecer pautas para guiar el diseño de protocolos MAC que se centren en minimizar el consumo de energía teniendo en cuenta los dispositivos de recolección de energía y la información de la batería.
Zhang, Klaus. "Comparison of Nonlinear Filtering Methods for Battery State of Charge Estimation". ScholarWorks@UNO, 2014. http://scholarworks.uno.edu/td/1896.
Texto completoEl, outmani Sohaïb. "On-line estimation of thermodynamic properties for Lithium-Ion battery state of health and composition analysis". Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT111.
Texto completoRechargeable batteries and especially Li-Ion batteries are already present in a multitude of applications among which we can mention the storage of wind or solar energy, mobile phones, airplanes and automotive. In the latter sector, since the market share of hybrid or electric vehicles is expected to increase from 1% to 30% in the coming years, batteries will experience unprecedented growth.In all these applications, battery diagnosis represents a major challenge in terms of performance and safety. The news is full of battery issue examples: overheating, fire or even explosion.It is therefore essential to develop tools that provide a better diagnose of the state of the batteries, and in particular the state of health.There is a relationship between the internal state of a battery and the thermodynamic quantities associated with it, in particular the entropy variation. Indeed, it has been observed that the thermodynamic profiles are dependent on some battery characteristics. These profiles depend on cycle, overcharge and thermal ageing. They also depend on the chemical composition of the battery. A knowledge of thermodynamic data is therefore a valuable source of information on the state and the past of a battery. From this observation, three major contributions have been done in this study.The first contribution is the determination of a lithium-ion cell chemical elements. Electrode cell components can play a critical role in assessing quality at different stages of the manufacturing process. In addition, for a second life of battery cells, it is important to know the battery characteristics, such as its composition, to be able to assemble them in battery packs. We propose a new approach to determine the chemical composition of a cell. This methodology consists of measuring thermodynamic profiles of different cells. Then by training, machine learning algorithms recognize the chemical composition of the batteries from these profiles. The work done in this study is a first approach that requires confirmation.The second contribution the state of health (SOH) estimation. The battery state of health is a key parameter because it controls the energy and performance of the battery, as well as its cycle and its life. An accurate assessment of SOH is very important for life performance and prediction. In this work, we have developed a new methodology to evaluate the SOH of the battery by entropy variation (ΔS) profile analysis. A relationship between ΔS and SOH is then established by Machine Learning algorithms.The last contribution is the real-tie estimation of battery cell thermodynamic quantities. It has become necessary to develop a methodology for in-situ and real-time estimation of lithium-ion cell thermodynamic quantities. This will emphasize the interest of the thermodynamic measurement in the battery field. Indeed the existing standard methodology is long, it takes several days / weeks to obtain the thermodynamic profiles. We propose a system identification approach to estimate entropy variation. This allow us to access the thermodynamic value quickly and to update it while the cell is in use
Huhman, Brett Michael. "A Single-Frequency Impedance Diagnostic for State of Health Determination in Li-ion 4P1S Battery Packs". Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/80573.
Texto completoPh. D.
Lièvre, Aurélien. "Développement d'un système de gestion de batterie lithium-ion à destination de véhicules "mild hybrid" : détermination des indicateurs d'état (SoC, SoH et SoF)". Thesis, Lyon 1, 2015. http://www.theses.fr/2015LYO10065/document.
Texto completoHybrid vehicles are developing with increasing use of energy storage elements based on lithium-ion battery. In this context, the use of battery is atypical and highly dependent on energy allocation strategies within the vehicle. Among these vehicles, the mild hybrid category retains heat engine for the autonomy that offer and adds to it an electric machine associated with a reversible storage system, to allow the kinetic energy recovery of the vehicle. The object of this work involves the development of algorithms for determining the states of charge (SoC) and health (SoH) and function (SoF) of each cell that compose a lithium-ion battery pack. These features are implemented in a Battery Management System (BMS) for industrial production. In order to reduce production costs, our work attempts to limit the computing power and the measuring sensors necessary for these states determination. From battery measurements in a "mild hybrid" use, developed methods allow the states determination, as well as some of the internal parameters of cells. This application is characterized by high currents and maintaining a SoC of around 50%, in order to maximize the availability of the battery and to minimize aging. The use of observers and estimators, using a simplified model cell, allows us to achieve satisfactory results with a reduced computing power
Riesco, Refoyo Javier. "Development of battery models for on-board health estimation in hybrid vehicles". Thesis, KTH, Materialvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211680.
Texto completoChristophersen, Jon Petter. "Battery state-of-health assessment using a near real-time impedance measurement technique under no-load and load conditions". Diss., Montana State University, 2011. http://etd.lib.montana.edu/etd/2011/christophersen/ChristophersenJ0511.pdf.
Texto completoOvejas, Benedicto Victòria Júlia. "Determination of the state of health of Li-ion batteries : the irreversible entropy production approach". Doctoral thesis, Universitat Politècnica de Catalunya, 2017. http://hdl.handle.net/10803/461681.
Texto completoEn els darrers anys, la demanda de bateries ha augmentat considerablement gràcies a la creixent proliferació de dispositius portàtils. Tot i això, és ben sabut que el funcionament de les bateries empitjora amb el temps i l'ús. Aquesta pèrdua de rendiment es mesura amb un paràmetre anomenat State-oh-Health (SoH) encara que, avui dia, no s'ha arribat a un consens per a definir-lo. A la literatura o als mateixos sistemes comercials s'hi poden trobar aproximacions experimentals, teòriques o heurístiques, que generalment funcionen en situacions particulars i que, moltes sovint, no estan directament relacionades amb la degradació que pateixen les cel·les. L'objectiu d'aquest estudi és trobar un paràmetre que estigui directament relacionat amb la degradació patida per les cel·les. Per aquest motiu, ens hem centrat en la producció d'entropia irreversible perquè aquesta està relacionada amb la dissipació d'energia i, per tant, amb les irreversibilitats degudes a la degradació del sistema o de l'energia. Es va treballar amb vàries químiques de bateries d'ions de liti (NMC, LFP i LCO) per tal d’avaluar la degradació patida per aquestes i la correspondència amb la generació d'entropia irreversible. Aquestes cel·les van ser avaluades a taxes baixes i elevades a diferents nivells de SoH. En particular, la disminució de capacitat i l’augment d’impedància, que són les tècniques més utilitzades per a determinar el SoH, van ser determinades i posteriorment relacionades amb la generació d’entropia irreversible. A més a més, l’anàlisi post-mortem de les cel·les ens va permetre obtenir un coneixement major de les causes i els efectes de la degradació. Com a resultat d’aquest estudi, hem introduït un nou paràmetre per a la caracterització de la degradació d’un sistema. Aquest paràmetre l’hem anomenat Relative-Entropy-Production (REP) i l’hem definit com la relació entre la generació d’entropia irreversible en el moment actual i l’estat inicial. En particular, hem trobat que la producció d’entropia irreversible a taxes baixes de descàrrega és més gran com més degradades estan les cel·les de NMC. En canvi, en el cas de les cel·les de LFP, hem trobat que la generació d’entropia irreversible disminueix durant els primers cicles per després augmentar fins al final de la seva vida útil. S’ha vist que aquesta disminució coincideix amb un increment de la capacitat. A més a més, a totes les cel·les amb les que hem treballat, hem trobat una relació entre la producció d’entropia irreversible i les transformacions de fase que tenen lloc als elèctrodes durant la descàrrega. Aquesta relació ha sigut associada al fet de que els materials que pateixen una canvi de fase s’expandeixen i es contrauen el que fa que es produeixin fractures o esquerdes o altres modificacions estructurals. Totes elles produeixen degradació i, per tant, generen entropia irreversible. S’ha trobat que REP i la generació d’entropia irreversible són magnituds prometedores per a caracteritzar l’envelliment de bateries. Encara que queda molta feina per fer, la idea és, en un futur, poder definir un llindar de REP o de generació d’entropia irreversible que les cel·les siguin capaces de suportar abans no es consideri que han assolit el final de les seves vides útils.
Savvidis, Charalampos y Zeyang Geng. "Onboard Impedance Diagnostics Method of Li-ion Traction Batteries using Pseudo-Random Binary Sequence". Thesis, Linköpings universitet, Tekniska fakulteten, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-118970.
Texto completoHashemi, Seyed Reza. "An Intelligent Battery Managment System For Electric And Hybrid Electric Aircraft". University of Akron / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=akron1615732366021405.
Texto completoSingh, Baljot. "A case study about the potential of battery storage in Culture house : Investigation on the economic viability of battery energy storage system with peak shaving & time-of-use application for culture house in Skellefteå". Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-52998.
Texto completoVaria, Adhyarth C. "In-Situ Capacity and Resistance Estimation Algorithm Development for Lithium-Ion Batteries Used in Electrified Vehicles". The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1408665208.
Texto completoSchlasza, Christian. "Analysis of aging mechanisms in Li-ion cells used for traction batteries of electric vehicles and development of appropriate diagnostic concepts for the quick evaluation of the battery condition". Thesis, Belfort-Montbéliard, 2016. http://www.theses.fr/2016BELF0155.
Texto completoIn this thesis, the aging mechanisms withing Li-ion cells are analyzed on a theoretical level, supported by an FMEA(Failure ode and Effects Analysis). The focus lies on the group of lithium iron phosphate (LFP) cells used fortraction batteries in electric vehicles. Scope of the experimental part of the thesis is the development of a diagnosticconcept for the quick battery state determination. A group of high capacity LFP cells (70Ah) designed for tractionpurposes in electric vehicles is aged artificially and investigated afterwards by impedance measurements in the timeand frequency domain. Electrochemical impedance spectroscopy (EIS) is found to reveal interesting information onthe battery's State-of-Health (SOH).For the interpretation of the measurement results, battery models are employed. Different equivalent circuit models(ECMs) are compared and an appropriate model is chosen, which is used for the SOC (State-of-Charge)determination and extended for the SOH (State-of-Health) determination. An SOH determination concept isdeveloped, which allows the approximation of the cell capacity in less than 30s, if the battery and environmentalconditions, such as the temperature and the cell's SOC, are known
Andersson, Joakim. "Lifetime estimation of lithium-ion batteries for stationary energy storage system". Thesis, KTH, Skolan för kemivetenskap (CHE), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-212987.
Texto completoMaillard, Florian. "Méthodologie de diagnostic des batteries Li-ion par la mesure des bruits électrochimiques". Thesis, Poitiers, 2015. http://www.theses.fr/2015POIT2302.
Texto completoThis work concerns the electrochemical voltage fluctuations Li-ion batteries, commonly known as electrochemical noise. The idea is to use the electrochemical measurement noise in operation to generate, via signal processing, statistical descriptors to characterize the SOH (health). The objective is to develop an innovative method noninvasive diagnostic to complement traditional methods (impedance,...). DCNS St Tropez has participated and intends to develop this approach in the context of an arms supply subsea application, which requires a very high level of security and reliability. The measurement of Li-ion batteries is difficult because of very low signal levels and requires efficient appliances. We installed a measurement system for acquiring voltage fluctuations landfill. Then we extracted noise due to robust numerical method. The discharge voltage is non-stationary, which requires a specific treatment. The short-term analysis by moments of order 2, 3 and 4 shows that there are three areas in which the noises are completely different. The middle of the discharge has a uniform distribution characterized by a V-shape (minimum to SOC = 55 %), tempo-frequency coherent structures on the edges revealed by wavelet analysis. Our model allows to find the predominant noise sources and identify the parameters responsible for the electrochemical noise. Future applications include the characterization of aging and quality of manufacture of batteries
Vichard, Loic. "Contribution à l’étude du vieillissement des composants batterie et pile à combustible en usage réel". Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCA018.
Texto completoThese thesis works are associated to the AsDeCoEUR project. This project is part of the current context of the development of new energy technologies for mobility and focuses more specifically on the study of battery and fuel cell components located in the heart of electric power train. The project is based on the work already carried out by the UTBM and IFSTTAR actors of the FCLAB research federation among the Mobypost project. Mobypost european project has allowed the experimentation of a fleet of 10 fuel cell electric vehicles under actual operating conditions on two postal platforms in the Franche-Comté region.During the Mobypost experiment, a deep monorting was performed on all the vehicles so numerous physical data of their power train were recorded. All of these information now constitutes a very rich database to exploit. Among the AsDeCoEUR project, we propose a scientific approach carried out around a thesis work wich aims at understanding dynamic behavior, studying aging and estimating the state of health of batteries and fuel cells in real use. This approach is based on the analysis of the data recorded on these components among the Mobypost project and is reinforced by specific experiments set up in the laboratory. The implementation of skills and digital analysis tools developed especially for batteries by the Ampère laboratory and IFSTTAR aims at understanding and reproducing the degradation phenomena. The works should finally allow, by combining the skills of UFC, UTBM, IFSTTAR and Ampère laboratory researchers, to contribute to the study of batteries and fuel cells aging and to estimate their state of health under actual operating conditions. This constitutes a remarkable advance in this field, particularly with a view to the industrialization of vehicles equipped with this type of component
Eddahech, Akram. "Modélisation du vieillissement et détermination de l’état de santé de batteries lithium-ion pour application véhicule électrique et hybride". Thesis, Bordeaux 1, 2013. http://www.theses.fr/2013BOR14992/document.
Texto completoIn this thesis, we focus on the reliability of lithium batteries used for automotive applications. For this purpose, electric and thermal characterization methodologies as well as aging tests under several modes (calendar, power cycling, calendar/power cycling) are carried out.In a first part of the work, battery modeling and battery state estimation (state-of-charge and state-of-health) are considered.Then, based on periodic characterization from electrochemical impedance spectroscopy, calendar aging is investigated. Next, we proposed an original process for precise battery state-of-health determination that exploits a full recharge and mainly constant-voltage charge step which allows easily its integration within a battery management system. Our experimental results, up to two years real-life data, confirm effectiveness of our technique.Finally, we study the capacity recovery phenomenon occurring due to combined battery aging (calendar/power cycling). This final part is almost dedicated to introduce strategies for battery use presenting at the same time a thermal behavior study
Zenati, Ali. "Gestion haut niveau et suivi en ligne de l'état de santé des batteries lithium-ion". Thesis, Université de Lorraine, 2012. http://www.theses.fr/2012LORR0391/document.
Texto completoLithium-ion batteries are considered nowadays as the optimal issue for the energy storage systems, it is mainly due to their high energy and power density. Their performances, lifetime, and reliability are related and depend on the operating conditions such as the temperature and requested current by the application. And in order to track the evolution of the ageing of the battery, the determination of its State-Of-Health -SOH- is a major function to consider. This thesis presents both methodologies and techniques developed for the management of the lifetime of lithium-ion battery, and more particularly the assessment of its state-of-health, based on its own main parameters which are the capacity and the ohmic resistance. This approach allows to switch from a static SOH (based on a predefined ageing model, which take into account the calendar and cycling ageing of the battery, according to some characteristics such as the temperature and the courant of the battery tracked in real time) to a dynamic SOH (self-adaptive) using an online assessment of the previous parameters according to the operating conditions. The first chapter is an overview about the lithium-ion technology: characteristics, performances, cell design, choice and nature of the electrodes... The operating principle with the general equations are also developed. The second chapter is a state of the art of the lifetime prediction methodologies with the different kinds of classification of models and prediction techniques. Then in the third chapter, we will discuss our methodologies and the developed techniques, such as the use of statistics, fuzzy logic and rules of ageing to assess a dynamic state of health of the battery, which not only does take into account the static SOH (calendar and cycling ageing), but also considers the evolution of the ohmic resistance and the capacity of the battery, depending on the time and the operating conditions. This allows taking into consideration unlikely phenomena. Finally, in the last chapter, we will expose obtained results from validation tests. These tests were done under a power electrical testbench and a rapid prototyping testbench with real cells
Farfan-Ramos, Luis. "Real-time Fault Diagnosis of Automotive Electrical Power Generation and Storage System". Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1303129393.
Texto completoRiviere, Elie. "Détermination in-situ de l'état de santé de batteries lithium-ion pour un véhicule électrique". Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAI048/document.
Texto completoAccurate lithium-ion battery State of Charge (SoC) and State of Health (SoH) estimations are nowadays a crucial point, especially when considering an industrial use. These estimations enable to improve robustness and reliability of hardware using such batteries. This thesis focuses on researching lithium-ion batteries state of health estimators, in particular considering Lithium Iron Phosphate (LFP) and Lithium Manganese Oxide (LMO) chemistries.Researches have been targeted towards SoH estimators straight embeddable into electric vehicles (EV) computers. Cost and reliability constraints are thus the main guideline for this work.Although existing literature offers various SoH estimators, those who are embedded or embeddable are still little studied. A complete literature review about SoH estimators, embedded or not, is therefore proposed. Lithium-ion batteries detailed operation and ageing mechanisms are also presented.The main part of this work is dedicated to Incremental Capacity Analysis (ICA) use with electric vehicle constraints, such as current levels available with a typical EV mission profile or existing measurements on the Battery Management System (BMS). Incremental Capacity Analysis is implemented in an innovative way and leads to a remaining capacity estimator with a high robustness to conditions of use variations, including an extended temperature range.A second method, dedicated to LMO chemistry, take advantage of the fact that the battery potential is representative of its state of charge. Partial Coulomb counting is thus performed, with a dynamic management of integration limits, depending on the battery state.Outcomes of this work are two complete and accurate SoH estimators, one for each chemistry, leading to a remaining capacity estimation accurate within 4 %
Urbain, Matthieu. "Modélisation électrique et énergétique des accumulateurs Li-Ion. Estimation en ligne de la SOC et de la SOH". Thesis, Vandoeuvre-les-Nancy, INPL, 2009. http://www.theses.fr/2009INPL028N/document.
Texto completoThis dissertation of thesis deals with the electrical modelling of lithium-ion accumulators and the determination of both state-of-charge (SOC) and state-of-health (SOH). The first chapter is focused on generalities about lithium-ion technology: characteristics, qualities, constitution of the storage device, choice and nature of the electrodes and their consequences on energetical features. The principle and the general equations of the electrochemical phenomena are developed as well. Application examples from different industrial areas are displayed for several power and energy ranges. The second section is about the electrical modelling of lithium-ion accumulators. With a view to better understand the complex electrochemical phenomena, elements of physical modelling are proposed. Then, the synthesis of different electrical models released in the press is considered. On the basis of experimental campaigns lead on a 6.8 Ah lithium-element, we proposed, in a third chapter, our own equivalent electrical model suitable for both discharge phases and relaxation period. In particular, we depict several alternatives to distribute the energy and describe the different line effects. Both characterization tools and parameters extraction procedure are clearly detailed. In the last section, we tackle both SOC and SOH on-line determination. After a short review of academicals and industrial solutions, we rapidly head towards the use of a Kalman filter. In order to compare its features versus the coulombmeter, we propose a model and an algorithm, numerical simulations and experimental tests are performed
Nazer, Rouba Al. "Système de mesure d'impédance électrique embarqué, application aux batteries Li-ion". Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENT007/document.
Texto completoEmbedded electrical impedance measurement is a key issue to enhance battery monitoring and diagnostic in a vehicle. It provides additional measures to those of the pack's current and cell's voltage to enrich the aging's indicators in a first time, and the battery states in a second time. A classical method for battery impedance measurements is the electrochemical impedance spectroscopy (EIS). At each frequency, a sinusoidal signal current (or voltage) of a variable frequency sweeping a range of frequencies of interest is at the input of the battery and the output is the measured voltage response (or current). An active identification technique based on the use of wideband signals composed of square patterns is proposed. Particularly, simulations were used to compare the performance of different excitation signals commonly used for system identification in several domains and to verify the linear and time invariant behavior for the electrochemical element. The evaluation of the estimation performance is performed using a specific quantity: the spectral coherence. This statistical value is used to give a confidence interval for the module and the phase of the estimated impedance. It allows the selection of the frequency range where the battery respects the assumptions imposed by the non-parametric identification method. To experimentally validate the previous results, an electronic test bench was designed. Experimental results are used to evaluate the wideband frequency impedance identification. A reference circuit is first used to evaluate the performance of the used methodology. Experimentations are then done on a Li–ion battery. Comparative tests with EIS are realized. The specifications are established using a simulator of Li-ion battery. They are used to evaluate the performance of the proposed wide band identification method and fix its usefulness for the battery states estimation: the state of charge and the state of health
Mallangi, Siva Sai Reddy. "Low-Power Policies Based on DVFS for the MUSEIC v2 System-on-Chip". Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229443.
Texto completoNuförtiden så har multifunktionella bärbara hälsoenheter fått en betydande roll. Dessa enheter drivs vanligtvis av batterier och är därför begränsade av batteritiden (från ett par timmar till ett par veckor beroende på tillämpningen). På senaste tiden har det framkommit att dessa enheter som används vid en fast spänning och frekvens kan användas vid flera spänningar och frekvenser. Genom att byta till lägre spänning och frekvens på grund av effektbehov så kan enheterna få enorma fördelar när det kommer till energibesparing. Dynamisk skalning av spänning och frekvens-tekniker (såkallad Dynamic Voltage and Frequency Scaling, DVFS) har visat sig vara användbara i detta sammanhang för en effektiv avvägning mellan energi och beteende. Hos Imec så använder sig bärbara enheter av den internt utvecklade MUSEIC v2 (Multi Sensor Integrated circuit version 2.0). Systemet är optimerat för effektiv och korrekt insamling, bearbetning och överföring av data från flera (hälso) sensorer. MUSEIC v2 har begränsad möjlighet att styra spänningen och frekvensen dynamiskt. I detta examensarbete undersöker vi hur traditionella DVFS-tekniker kan appliceras på MUSEIC v2. Experiment utfördes för att ta reda på de optimala effektlägena och för att effektivt kunna styra och även skala upp matningsspänningen och frekvensen. Eftersom att ”overhead” skapades vid växling av spänning och frekvens gjordes också en övergångsanalys. Realtidsoch icke-realtidskalkyler genomfördes baserat på dessa tekniker och resultaten sammanställdes och analyserades. I denna process granskades flera toppmoderna schemaläggningsalgoritmer och skalningstekniker för att hitta en lämplig teknik. Genom att använda vår föreslagna skalningsteknikimplementering har vi uppnått 86,95% effektreduktion i jämförelse med det konventionella sättet att MUSEIC v2-chipets processor arbetar med en fast spänning och frekvens. Tekniker som inkluderar lätt sömn och djupt sömnläge studerades och implementerades, vilket testade systemets förmåga att tillgodose DPM-tekniker (Dynamic Power Management) som kan uppnå ännu större fördelar. En ny metod för att genomföra den djupa sömnmekanismen föreslogs också och enligt erhållna resultat så kan den ge upp till 71,54% lägre energiförbrukning jämfört med det traditionella sättet att implementera djupt sömnläge.
Yuan, Hsiang-Fu y 原祥富. "A Study on Battery State-of-Health Management Technology for Battery Second-Use". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/4ke9yf.
Texto completo國立交通大學
電控工程研究所
104
Battery second-use (B2U) is a new business model in the future electric vehicle (EV) market to offset the high EV cost to customers by repurposing used EV batteries to a second-life application, such as a battery energy storage system (BESS) with a renewable energy source (RES), for maximizing its economic benefits. For B2U, battery state-of-health (SOH) managements are essential technology for evaluating the remaining value of an aging EV battery and maximizing the battery second lifetime. In this dissertation, an off-line SOH estimation based on the charge transfer resistance is proposed for high power and high capacity lithium-ion battery cells, such as lithium iron phosphate or LFP battery cells, to estimate an unbiased and reliable SOH, so it can be a useful information for EV manufacturers and second-hand battery buyers in trading evaluation. As shown in the experimental results, the charge transfer resistance has a great aging change with battery degradation and good abilities against the state-of-charge (SOC) effect and external resistance variation in impedance parameters of a single time-constant equivalent circuit model (ECM) including ohmic resistance, charge transfer resistance, double-layer capacitance, and time constant, for SOH estimation. A fast and efficient three-point impedance extraction (TPIE) method is further proposed in this dissertation for accurately extracting the charge transfer resistance in off-line SOH estimation. The results of long-term cycling test demonstrate that the TPIE method can successfully indicate the SOH of LFP battery cells with low estimation error of 6.1%. This dissertation also presents a dual second-life battery energy storage system (DSLBESS) with the battery depth-of-discharge (DOD) management for extending battery cycle life and system service time. The proposed system consists of a power management system, a dual-battery energy storage unit (ESU), a fuel cell (FC) stack, and two DC-DC unidirectional power converters. Unlike conventional BESSs, the dual-battery ESU in the DSLBESS serves as the primary power source, while the FC stack serves as the secondary power source. The proposed power management is based on a state-machine-based mechanism, using a battery interchanging strategy to limit batteries operating within a given DOD range. The state-machine-based mechanism is employed for reducing the effects of battery overcharging or overdischarging; thus, it can significantly improve the battery life time. In addition, this algorithm has the ability to distribute the power flow efficiently between the dual batteries and the FC stack, and also to keep providing a stable and continuous energy output for the load. A current-mode control DC-DC boost converter is designed to regulate the FC current and try to maximize the FC power for battery charging time reduction. The proposed system is designed and implemented with a 20W proton exchange membrane fuel cell (PEMFC) stack and two 12Ah LiFePO4 batteries. The experimental results of capacity fades on various DOD tests verify the usefulness of the proposed DSLBESS. The comparison of life improvement shows that the cycle life has a 66.93% improvement when the normal operating region is limited within 60% DOD.
Liang, Yi-Min y 梁翊民. "On-line State-of-Health Estimation for LiFePO4 Battery". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/sp3q7x.
Texto completo國立中山大學
電機工程學系研究所
104
The demand of batteries for electric vehicle (EV) and Energy Storage System (ESS) is increasing. After battery has been used for a long time, the actual available capacity of battery will decrease, so State-of-Health (SOH) estimation is important in EV and ESS operations. An on-line SOH estimation method is proposed in the thesis. It is different from the conventional off-line estimation methods that need to remove battery from the system and connect to other devices. The key component in the proposed SOH estimation procedure is to obtain aging indicators according to the data from aging experiment performed off-line, and then use the indicators, including model parameters in a battery equivalent circuit to estimate SOH. Test data are used to determine the model parameter values during different battery ages by least square error method. The battery characteristic parameters computed at each age of the battery are then used in an Artificial Neural Network (ANN) to train and setup the automatic SOH estimator. In the proposed procedure, a regression model is used to determine the relationship of battery open-circuit voltage with State-of-Charge (SOC) and SOH. An on-line SOH estimation can be achieved after the battery open-circuit voltage and the equivalent circuit model parameters are calculated real time and fed into the ANN model. Test results indicate that the average absolute error of the proposed SOH estimator under different usage scenarios is 1.7732% based on 5 LiFePO4 batteries.
GUO, GUAN-DE y 郭冠德. "The Development of Detection Methods for Battery State of Health". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/72423278053198512596.
Texto completo高苑科技大學
電機工程研究所
104
A novel detection method for the health of a battery is proposed. Combined DC resistance and AC impedance method calculate the internal resistance of the battery. The internal resistance of a battery includes the ohmic resistance, the charge transfer resistance and the mass transfer impedance. When the battery is aging, the reduction of electrode active material, the separator obstruction, the electrolyte aging will be the reaction to the internal resistance of the battery.Since the ohmic resistance of a battery typically only a few milliohms, this paper uses DC resistance method to measure the ohmic resistance. DC resistance method could be obtained with a high accuracy compared with AC impedance method. Moreover, this paper uses AC impedance method with low frequency AC test signals is proposed to measure the charge transfer resistance and the mass transfer impedance. Based on the ohmic resistance, the charge transfer resistance and the mass transfer impedance that estimate the battery state of health compared with the battery aging database, as estimated remaining life of the battery.
Liu, Sung-Hsun y 劉松洵. "Model-Based State of Charge and State of Health Estimation Method for Lithium-Ion Battery". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/7dpawd.
Texto completo大同大學
電機工程學系(所)
106
In this thesis, a state of charge (SOC) and state of health (SOH) estimation method for lithium-ion (Li-ion) battery is proposed. The proposed estimation method can be divided into three parts: (1) parameters identification; (2) SOH estimation; (3) and SOC estimation. A first-order RC model is adopted as the equivalent circuit model (ECM) of the battery in this thesis. The aging models are established by experiments. The parameters of the battery are identified by the proposed aging level estimation method and the recursive least square (RLS) method. A proper aging model is chosen according to the aging level estimation. Based on the aging level estimation, this thesis proposes a resistance-capacity fusion method to estimate the usable capacity of the battery and the SOH. The SOC estimation is fulfilled by the adaptive extended Kalman filter (AEKF). To experimentally validate the proposed estimation method, the Li-ion battery cells with unknown aging level have been discharged by the federal urban driving schedule (FUDS) and dynamic stress test (DST) profile under room temperature condition. According to the validation results, the proposed estimation method has good performance.
Huang, Sheng-Yu y 黃勝煜. "Estimation of State of Health of Lithium-ion Battery Using Deep Learning". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/zr8h48.
Texto completo國立臺灣大學
機械工程學研究所
106
In development of Battery models are vital for the development of electric vehicles. The battery life change the battery response. As a result, the model, which has battery degradation factors helps improve the efficiency of other control algorithms and maintain the safe usage of the battery. In this thesis, use charge-discharge cycle that is similar to a vehicle testing pattern and TensorFlow™ to build artificial neural network of battery cell which can predict the battery life. The battery model considers different parameters like patterns of charge current and the number of cycle which have an influence on the result of prediction. We have training data that is for a Deep Neural Network and test data that is identified for the model accuracy. The best result is that it can predict state of health within 0.1 of mean square error. In this thesis, the other model that is Recurrent Neural Network has the ability of remembering previous data. It has also good performance on estimating SOH.
Chao, Liang-Chieh y 趙良傑. "Evaluation of Battery Model, State of Charge, and State of Health with Measurement of DC Internal Resistance". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/x992sh.
Texto completo國立虎尾科技大學
電機工程系碩士班
104
Lead-acid battery can be used for the energy storage systems of solar power, UPS of the power system and the battery of hybrid vehicles and electric vehicles…etc. Therefore, the measurement of the lead-acid battery internal resistance has a high place in the application of battery. It is proposed a kind of the technology to measure the lead-acid battery internal resistance in this paper. The circuit architecture in this paper is not complicated, so the cost is cheaper than the normal measurement of DC internal resistance. It is convenient and not loss the accuracy. And it can help the people to know the battery status to prevent low power battery. The measurement of DC internal resistance in this paper is based on the Electrochemistry Impedance Spectroscopy (EIS) to establish the First-order battery model. With the First-order battery model, it can get the Ohmic resistance(R_ohm), Polarization resistance(R_ct) and Electric double layer capacitor(C_dl) in this measurement of Direct-Current Resistance(DCR) to establish the First-order dy battery models. After the establishment of the first-order dynamical battery models, it can calculate the State Of Charge (SOC) and State Of Health (SOH).
Chen, Yu-chieh y 陳育傑. "ONLINE STATE OF CHARGE AND STATE OF HEALTH ESTIMATION FOR LITHIUM-ION BATTERY BY THE NEURAL NETWORK MODEL". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/p6cx36.
Texto completo大同大學
電機工程學系(所)
107
The online estimation of the state of charge and the state of health of lithium-ion battery (Li-ion battery) is studied in this thesis. The state of health (SOH) and state of charge (SOC) of Li-ion battery are two important items in Li-ion battery management systems. It is known that the usable capacity of a Li-ion battery varies with the SOH and the ambient temperature. In order to obtain good estimation of the SOC, it is necessary to have good estimation of the SOH of the Li-ion battery. A first-order RC equivalent circuit model (ECM) is adopted as dynamic model of the Li-ion battery. We design a characteristic test to find the relationship between the open-circuit voltage (Voc) and the SOC of the battery; the relationship between the ECM parameters (Rs) and the SOC of the battery under different SOH and different ambient temperatures. A back-propagation neural network is applied to estimate the SOH of the battery. The value of the Rs obtained from the characteristic test, SOC and ambient temperature (T) are adopted as the input data of the back-propagation neural network, and the usable capacity as output data. Thus, the SOH can be estimated by the usable capacity. Then, an online parameter update method is employed to find the values of the parameters (Rp, Cp) of the ECM. Finally, the adaptive extended Kalman filter (AEKF) is applied to estimate the SOC. The experimental results show the modeling error that caused by SOH and temperature effect can be compensated, and the SOC of the Li-ion battery can be accurately estimated by the proposed method.
Chuang, Kuo-Shun y 莊國順. "Estimation of State of charge and State of health for lithium-ion battery pack using dual extended Kalman filter". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/ds7u43.
Texto completo國立臺北科技大學
車輛工程系所
105
A dual extended Kalman filter is employed to estimate the state of charge (SOC) and the state of health (SOH) for a lithium-ion battery pack in this thesis. The sample time of the parameter estimator is larger than that of the state estimator. Due to the lack of the experiment data of the aged battery pack, a virtual battery pack is established using MapleSim. First, a cell model is established using the experiment data of the new cell. The aged cell model is then established according to the characteristics of the aged cell. The battery pack model can then obtained by connecting cells in series and parallel according to the specification of the target battery pack. Measurement resolutions and noises of the current and voltage are also considered in this thesis. An adaptive law is proposed to adjust the measurement noise covariance matrix of the parameter estimator according to the estimated SOC to reduce the noise effect to the estimator. Incorrect initial conditions of the parameters and states, and the battery pack with 3% parameter variations are used to evaluate the performance and robustness of the proposed approach. Simulation results show that the proposed adaptive law can accurately estimate the SOC and SOH of the aged battery pack with 3% parameter variations, and effectively reduce the noise sensitivity and enhance the robustness.
LIN, DAO-QIN y 林道勤. "Estimation of State of Charge and State of Health for Aging Lithium-ion Battery Pack using Automatic Data Update". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/f39g85.
Texto completoLin, Chiung-Ming y 林熲珉. "State of Health Prediction for Lithium Ion Battery Using a New Equivalent Circuit Model". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/07156700457980708285.
Texto completo國立虎尾科技大學
電機工程研究所
102
This paper is using a new equivalent circuit model; Meanwhile analyze the state of health for the battery. Because the high frequency dynamic response has been ignored in equivalent circuit model, we can further simplify the equivalent circuit model that Kalman filter calculation can be easier. We will verify the above calculation. The new equivalent circuit model with dual circuit will be got exact value prediction by Kalman filter. Finally,Finally, we use the estimate state of health to amend the state of charge after battery aging and getting more accurate state of charge. Improve reliability of the battery, and get more accurate value. The reliability of the battery can be improved if we avoided the battery overcharge or over discharge.
Lin, Chiung-Ming y 林熲? "State of Health Prediction for Lithium Ion Battery Using a New Equivalent Circuit Model". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/vvruzj.
Texto completo國立虎尾科技大學
電機工程研究所
102
This paper is using a new equivalent circuit model; Meanwhile analyze the state of health for the battery. Because the high frequency dynamic response has been ignored in equivalent circuit model, we can further simplify the equivalent circuit model that Kalman filter calculation can be easier. We will verify the above calculation. The new equivalent circuit model with dual circuit will be got exact value prediction by Kalman filter. Finally,Finally, we use the estimate state of health to amend the state of charge after battery aging and getting more accurate state of charge. Improve reliability of the battery, and get more accurate value. The reliability of the battery can be improved if we avoided the battery overcharge or over discharge.
Bibin, Nataraja Pattel. "An evaluation of the moving horizon estimation algorithm for online estimation of battery state of charge and state of health". Thesis, 2014. http://hdl.handle.net/1805/6293.
Texto completoMoving Horizon Estimation (MHE) is a powerful estimation technique for tackling the estimation problems of the state of dynamic systems in the presence of constraints, nonlinearities and disturbances and measurement noises. In this work, the Moving Horizon Estimation approach is applied in estimating the State of Charge (SOC) and State of Health (SOH) of a battery and the results are compared against those for the traditional estimation method of Extended Kalman Filter (EKF). The comparison of the results show that MHE provides improvement in performance over EKF in terms of different state initial conditions, convergence time, and process and sensor noise variations. An equivalent circuit battery model is used to capture the dynamics of the battery states, experimental data is used to identify the parameters of the battery model. MHE based state estimation technique is applied to estimates the states of the battery model, subjected to various estimated initial conditions, process and measurement noises and the results are compared against the traditional EKF based estimation method. Both experimental data and simulations are used to evaluate the performance of the MHE. The results shows that MHE performs better than EKF estimation even with unknown initial state of the estimator, MHE converges faster to the actual states,and also MHE is found to be robust to measurement and process noises.
Li, Li-gang y 李立綱. "STATE OF CHARGE AND STATE OF HEALTH ESTIMATION OF LITHIUM-ION BATTERY BY THE NEURAL NETWORK AND ADAPTIVE EXTENDED KALMAN FILTER". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/p589vc.
Texto completo大同大學
電機工程學系(所)
107
In this thesis, a hybrid SOC and SOH estimator for the Lithium-ion battery in different ambient temperature is proposed. In order to obtain good estimation of the SOC, it is necessary to have good estimation of the SOH of the Lithium-ion battery. A first-order RC model is adopted as the equivalent circuit model (ECM) of the Lithium-ion battery. It is known that such an ECM can well describe the static characteristics and dynamic characteristics of the Lithium-ion battery. However, it is seen that all the numerical values of the parameters in the ECM vary with the SOH, SOC and the ambient temperature T. In this thesis, we will design the characteristic tests, under different ambient temperature, for the Lithium-ion batteries with different SOH to find the relations between the open circuit voltage (OCV) and the SOC, the relations between the numerical values of the parameters in the ECM and the SOC. A back-propagation neural network (BPNN) will be used to mimic the relations between the parameters in the ECM, the ambient temperature T with the SOH of the Lithium-ion battery. Therefore, the numerical values of the parameters in the ECM and the ambient temperature T are adopted as the input of BPNN and the SOH as the output of BPNN. Finally, the adaptive extended Kalman filter (AEKF) is applied to estimate the SOC of the lithium-ion battery. According to the experimental results, the absolute values of the SOC estimation errors of the tested batteries can be maintained in a 3% band, which means that the proposed estimator can accurately estimate the SOC.
Locorotondo, Edoardo, Luca Pugi, Lorenzo Berzi y Marco Pierini. "Advanced modeling and development of mathematical methods for real-time diagnosis on lithium-ion batteries and state prediction". Doctoral thesis, 2021. http://hdl.handle.net/2158/1238304.
Texto completoReddy, T. Mohan. "Capacity and Life Estimation of Flooded Lead Acid Batteries using Eddy Current Sensors". Thesis, 2016. http://etd.iisc.ernet.in/handle/2005/2971.
Texto completoSilva, Bruno Joel Ribeiro da. "Desenvolvimento de um Posto de Carregamento Lento com BMS e Interface com o Cockpit para o CEPIUM". Master's thesis, 2013. http://hdl.handle.net/1822/39835.
Texto completoAtualmente, os veículos elétricos têm vindo a ganhar notoriedade dentro do ramo da indústria automóvel. Assim, existe um interesse crescente na substituição dos veículos com motor de combustão interna por veículos elétricos, devido às vantagens inerentes aos mesmos. No entanto, o desenvolvimento do veículo elétrico exige novas infraestruturas e soluções ao nível do carregamento, bem como novas soluções para o armazenamento de energia. O recurso às baterias para o armazenamento de energia nos veículos elétricos tem sido a solução mais adotada, assim, nesta dissertação descreve-se a implementação de um sistema de gestão e monitorização de baterias. Este sistema visa proteger as baterias contra abusos durante o seu funcionamento (não permite que os seus valores máximos e mínimos sejam excedidos), aumentando assim o seu tempo de vida útil, mas tentando sempre obter o melhor desempenho possível das baterias. Além disso, este sistema também informa o utilizador do veículo elétrico sobre diversos parâmetros do sistema de baterias, necessários para uma condução agradável e desprovida de ansiedade da autonomia, provocada pela falta de conhecimento do estado de carga das mesmas. Nesta dissertação, numa fase inicial apresenta-se o estado de arte sobre as tecnologias de baterias. De seguida, descreve-se a estrutura e constituição de um sistema de gestão de baterias. Posteriormente, realizam-se várias simulações para validar a topologia de equalização. Por último, implementa-se e testa-se o sistema de gestão de baterias proposto.
Currently, electric vehicles have been gaining notoriety within the field of car industry. Thus, there is a growing interest in the replacement of vehicles with internal combustion engine for electric vehicles, due to the inherent advantages of these. However, the development of the electric vehicle requires new infrastructures and solutions in what concerns loading, as well as new solutions for energy storage. The use of batteries for energy storage is the main solution adopted for electric vehicles. Thus, this work describes the implementation of a battery management system. This system aims to protect the batteries from abuse during operation (not allowing their maximum and minimum values to be exceeded), thereby increasing their lifetime, but always trying to get the maximum performance from the batteries. In addition, this system also informs the user of the electric vehicle about various parameters of the battery system required for a pleasant driving, and devoid of range anxiety, caused by the unawareness of the battery status. This work, initially presents the state of the art on battery technologies. Afterwards, describes the structure and constitution of a battery management system. Thereafter, several simulations are carried out to validate the topology of equalization. Finally, it presents the implementation and testing of the battery management system.