The functionality to both charge and discharge energy from and to the power grid to a Battery Electric Vehicle (BEV) is referred to as Vehicle-to-Grid (V2G). This allows the customer to buy energy when the spot price is low and sell energy when the price is high to make a profit, called energy arbitrage. However, when the battery is charging, discharging, or idling for storage, battery degradation occurs due to chemical properties and reactions. This thesis developed a mathematical optimisation model in Python, using the modelling language Pyomo. Mathematical equations are used to integrate energy arbitrage and degradation data to reduce the total cost in terms of degradation and energy by finding an optimised charge and discharge pattern. The model allows different user scenarios to be analysed by changing inputs such as charger power, battery cost or daily driving distance. When using V2G technology, the State-of-Charge (SoC) level of BEVs battery packs can be adjusted to find SoC levels which minimise the battery degradation, while allowing the user to make a profit from energy arbitrage. The result shows that the V2G charging protocol, compared to protocols without a bidirectional charger could be beneficial for the simulated time periods, by both reducing degradation and the total energy cost. The results also indicate that the degradation cost of the battery is often the determining factor in the decision of when to charge or discharge, i.e., the substantial cost-saving strategy is to control the storage and cycle degradation to reduce the total degradation, rather than controlling the energy arbitrage. The model and the result of this thesis can be used by car manufacturers to learn more about how battery cell types behave in V2G mode and influence further work on V2G control.

Dans un contexte de progression du stockage d’énergie sous forme électrochimique dans les transports, notamment dans l’aéronautique, les problématiques de performance, de fiabilité, de sureté de fonctionnement et de durée de vie du stockeur sont essentielles pour utilisateurs. Cette thèse se focalise ces voltes pour l’avion plus électrique. Les technologies étudiées correspondent à des éléments commerciaux de dernière génération de type Lithium-ion (NMC/graphite+SiO, NCA/graphite, LFP/graphite, NMC/LTO), Lithium-Soufre (Li-S), supercondensateur et hybride (LiC). Une première partie de ce manuscrit s’attache à la quantification des performances des différents éléments dans l’environnement aéronautique [-20°C, 55°C] et pour l’usage aéronautique. Un modèle comportemental de type électro-thermique est développé et validé. La seconde partie est consacrée à la quantification du vieillissement des différents éléments. Les résultats de vieillissement calendaire et en cyclage actif sont présentés ainsi que ceux des tests abusifs. Une méthode d’estimation de l’état de santé (SOH) des éléments basés sur l’analyse de la capacité incrémentale (ICA) est proposée. Enfin, l’évaluation de la robustesse des éléments de stockage lors de tests de vieillissement accéléré avec un profil spécifique à l’usage aéronautique est proposé. Les modèles de vieillissement et la méthode d'estimation de SOH proposés précédemment sont utilisés ici pour évaluer l'impact de la température sur la vitesse de dégradation et pour estimer le SOH des cellules vieillies à l’aide de ce profil aéronautique. / In the context of progress in the electrochemical energy storage systems in the transport field, especially in the aeronautics, the issues of performance, reliability, safety and robustness of these elements are essential for users. This thesis is focused on these issues for the more electric aircraft. The technologies studied correspond to the latest generation commercial elements of Lithium-ion batteries (NMC/ graphite + SiO, NCA/graphite, LFP/graphite, NMC/LTO), Lithium-Sulfur (Li-S), Supercapacitor and Lithium-ion capacitors. The first part of this manuscript is dedicated to the performance quantification of the different electrochemical energy storage elements in aeronautical environment [-20°C, 55°C] and usage. An efficient and accurate electro-thermal model is developed and validated. The second part is devoted to the calendar and power cycling ageings as well as to the presentation of abuse testing results. A State Of Health (SOH) estimation based on incremental capacity analysis method is proposed. Finally, the robustness of the storage elements during accelerated ageing tests with a specific profile for the aeronautical usage is evaluated. The ageing models and SOH estimation methods proposed in the previous sections are used here to evaluate the impact of temperature on the degradation rate and to estimate the SOH of the cells with this aeronautical profile.

Dans cette thèse, les mécanismes de vieillissement des cellules Li-ion sont analysés sur un niveau théorique,assisté par une AMDEC (Analyse des modes de défaillance, de leurs effets et de leur criticité). L'accent est mis surla famille des cellules lithium fer phosphate (LFP) utilisées comme batteries de traction dans les applicationsvéhicules électriques.L'objectif de la partie xpérimentale de cette thèse est le développement d'un concept d'un outil de diagnostic pourla détermination rapide d'état de la batterie. Une expérience de vieillissement accélérée est réalisée avec un groupede cellules LFP de haute capacité (70Ah). Les cellules sont analysées en utilisant des méthodes de mesured'impédance dans les domaines temporel et fréquentiel. La pectroscopie d'Impédance Électrochimique (SIE, ouEIS en anglais) s'est trouvée être un bon outil pour révéler des informations intéressantes sur l'état de santé (Stateof-Health, SOH) de la batterie.Des modèles de batterie sont utilisés pour l'interprétation des résultats de mesure. En comparant différents modèlesdu circuit équivalent (ECMs), un modèle est choisi. Ce modèle est utilisé pour la détermination du SOC et étendupour la détermination du SOH. Un concept pour la détermination du SOH est développé, permettant uneapproximation de la capacité de la batterie dans une période de temps de moins de 30s, si les onditions de labatterie et d'environnement, comme la température et l'état de charge de la batterie, sont connus. / In 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.

Pour assurer une énergie électrique de qualité et de façon permanente, il existe des systèmes électroniques d'alimentation spécifiques. Il s'agit des Alimentations Sans Interruptions (ASI). Une ASI comme tout autre système peut tomber en panne ce qui peut entrainer une perte de redondance. Cette perte induit une maintenance corrective donc une forme d'indisponibilité ce qui représente un coût. Nous proposons dans cette thèse de travailler sur deux composants parmi les plus sensibles dans les ASI à savoir les condensateurs électrolytiques et les batteries au plomb. Dans une première phase, nous présentons, les systèmes de surveillance existants pour ces deux composants en soulignant leurs principaux inconvénients. Ceci nous permet de proposer le cahier des charges à mettre en oeuvre. Pour les condensateurs électrolytiques, nous détaillons les différentes étapes de caractérisation et de vieillissement ainsi que la procédure expérimentale de vieillissement standard accéléré et les résultats associés. D'autre part, nous présentons les résultats de simulation du système de surveillance et de prédiction de pannes retenu. Nous abordons la validation expérimentale en décrivant le système développé. Nous détaillons les cartes électroniques conçues, les algorithmes mis en oeuvre et leurs contraintes d'implémentation respectifs pour une réalisation temps réel. Enfin, pour les batteries au plomb étanches, nous présentons les résultats de simulation du système de surveillance retenu permettant d'obtenir le SOC et le SOH. Nous détaillons la procédure expérimentale de vieillissement en cycles de charge et décharge de la batterie nécessaire pour avoir un modèle électrique simple et précis. Nous expliquons les résultats expérimentaux de vieillissement pour finir avec des propositions d'amélioration de notre système afin d'obtenir un SOH plus précis.

Le syndrome d’apnées obstructives du sommeil (SAOS) est associé à de nombreuses co-morbidités métaboliques et cardiovasculaires. L’hypoxie intermittente chronique, une des composantes du SAOS, induit des mécanismes intermédiaires délétères tels que stress oxydatif, inflammation, insulino-résistance ou encore dyslipidémie, à l’origine de ces comorbidités. Ces mécanismes intermédiaires sont également communs à d’autres pathologies respiratoires chroniques telles que la bronchopneumopathie chronique obstructive (BPCO) et le syndrome d’obésité hypoventilation (SOH).L’hypoxie intermittente et les mécanismes intermédiaires associés sont aussi à l’origine de l’existence et de la progression de la stéatopathie métabolique (« non alcoholic fatty liver disease »). Ce lien entre pathologies respiratoires chroniques et atteinte hépatique est un mécanisme essentiel mais plus récemment étudié des co-morbidités dans le SAOS et la BPCO. Différents biomarqueurs cardiométaboliques ont donc été étudiés dans ces pathologies respiratoires chroniques à la fois pour caractériser les co-morbidités et l’atteinte systémique et pour apprécier l’impact de différentes thérapeutiques. La première partie de cette thèse sera consacrée à une revue systématique des différents biomarqueurs cardio-métaboliques liés à chacune de ces 3 pathologies respiratoires chroniques : SAOS, BPCO et SOH.Le traitement du SAOS par pression positive continue (PPC) a un effet bénéfique sur les symptômes fonctionnels liés à cette pathologie. Cependant, l’impact de la PPC sur d’autres conséquences cardio-métaboliques délétères du SAOS reste encore à démontrer par des essais randomisés contrôlés, notamment sur l’atteinte hépatique.Dans la seconde partie de cette thèse, nous détaillerons l’impact de la PPC sur les différents marqueurs cardiométaboliques du SAOS à l’aide d’une revue systématique puis d’une étude randomisée contrôlée sur l’impact de la PPC sur les marqueurs d’atteinte hépatique.Par ailleurs, les patients atteints de SAOS, BPCO ou SOH reçoivent du fait de leur polypathologie (multimorbidité) des traitements médicamenteux multiples qui visent à contrôler au mieux les co-morbidités. Il est donc primordial de considérer la prise en charge globale de ces patients du point de vue de leurs traitements instrumentaux (PPC et ventilation non invasive) mais aussi en considérant l’impact des traitements médicamenteux associés. En effet, les traitements médicamenteux peuvent interférer avec la sévérité de la pathologie elle-même et impacter les biomarqueurs liés aux comorbidités associées. La troisième partie de cette thèse sera consacrée à l’étude d’un antihypertenseur chez le patient SAOS et envisagera l’influence des médicaments sur la pertinence de l’usage des bicarbonates comme marqueurs diagnostiques du SOH.En conclusion, nous insisterons sur la nécessité d’une prise en charge intégrée multi systémique et d’une prise en charge personnalisée de ces patients. / Obstructive sleep apnea (OSA) is associated with related metabolic and cardiovascular comorbidities. Chronic intermittent hypoxia the hallmark of OSA induces deleterious intermediary mechanisms such as oxidative stress, systemic inflammation, insulin resistance and dyslipidemia. Cardiovascular and metabolic comorbidities are also key features of other chronic respiratory diseases such as chronic obstructive pulmonary disease (COPD) and obesity hypoventilation syndrome (OHS). Chronic hypoxia and deleterious intermediary mechanisms also trigger occurrence and progression of non alcoholic fatty liver disease. This link between chronic respiratory diseases and liver injury is observed through modifications of specific liver biomarkers in OSA and COPD. A variety of cardiometabolic biomarkers have been studied for stratification of cardio-metabolic risk and assessing treatment impact in chronic respiratory diseases. The first part of this PhD thesis is a systematic review of cardio-metabolic biomarkers in 3 respiratory diseases: OSA, COPD and OHS.Continuous positive airway pressure (CPAP) the first line therapy for OSA improves symptoms and quality of life. However, CPAP effects on cardio-metabolic consequences remains still debated. In the second part of the PhD thesis, we will address CPAP impact on different cardiometabolic biomarkers and more specifically in markers of liver injury by reporting original results of a randomized controlled trial (RCT).Polypharmacy is usual in patients with OSA, COPD or OHS. Beyond CPAP or non invasive ventilation treatment, it is essential address the contribution of associated medications. Indeed, pharmacological treatments can interfere with the severity of the disease and control of associated comorbidities. The third part of the thesis will present a RCT evaluating Bosentan in hypertensive OSA patients and will present how medications for comorbidities decrease bicarbonate diagnosis value for OHS.We will conclude by underlining the crucial importance of personalized medicine and integrated care in chronic respiratory diseases.

Electric vehicles have received substantial attention in the past few years since they provide a more sustainable, efficient, and greener transportation alternative in comparison to conventional fossil-fuel powered vehicles. Lithium-Ion batteries represent the most important component in the electric vehicle powertrain and thus require accurate monitoring and control. Many challenges are still facing the mass market production of electric vehicles; these challenges include battery cost, range anxiety, safety, and reliability. These challenges can be significantly mitigated by incorporating an efficient battery management system. The battery management system is responsible for estimating, in real-time, the battery state of charge, state of health, and remaining useful life in addition to communicating with other vehicle components and subsystems. In order for the battery management system to effectively perform these tasks, a high-fidelity battery model along with an accurate, robust estimation strategy must work collaboratively at various power demands, temperatures, and states of life. Lithium ion batteries are considered in this research. For these batteries, electrochemical models represent an attractive approach since they are capable of modeling lithium diffusion processes and track changes in lithium concentrations and potentials inside the electrodes and the electrolyte. Therefore, electrochemical models provide a connection to the physical reactions that occur in the battery thus favoured in state of charge and state of health estimation in comparison to other modeling techniques. The research presented in this thesis focuses on advancing the development and implementation of battery models, state of charge, and state of health estimation strategies. Most electrochemical battery models have been verified using simulation data and have rarely been experimentally applied. This is because most electrochemical battery model parameters are considered proprietary information to their manufacturers. In addition, most battery models have not accounted for battery aging and degradation over the lifetime of the vehicle using real-world driving cycles. Therefore, the first major contribution of this research is the formulation of a new battery state of charge parameterization strategy. Using this strategy, a full-set of parameters for a reduced-order electrochemical model can be estimated using real-world driving cycles while accurately calculating the state of charge. The developed electrochemical model-based state of charge parameterization strategy depends on a number of spherical shells (model states) in conjunction with the final value theorem. The final value theorem is applied in order to calculate the initial values of lithium concentrations at various shells of the electrode. Then, this value is used in setting up constraints for the optimizer in order to achieve accurate state of charge estimation. Developed battery models at various battery states of life can be utilized in a real-time battery management system. Based on the developed models, estimation of the battery critical surface charge using a relatively new estimation strategy known as the Smooth Variable Structure Filter has been effectively applied. The technique has been extended to estimate the state of charge for aged batteries in addition to healthy ones. In addition, the thesis introduces a new battery aging model based on electrochemistry. The model is capable of capturing battery degradation by varying the effective electrode volume, open circuit potential-state of charge relationship, diffusion coefficients, and solid-electrolyte interface resistance. Extensive experiments for a range of aging scenarios have been carried out over a period of 12 months to emulate the entire life of the battery. The applications of the proposed parameterization method combined with experimental aging results significantly improve the reduced-order electrochemical model to adapt to various battery states of life. Furthermore, online and offline battery model parameters identification and state of charge estimation at various states of life has been implemented. A technique for tracking changes in the battery OCV-R-RC model parameters as battery ages in addition to estimation of the battery SOC using the relatively new Smooth Variable Structure Filter is presented. The strategy has been validated at both healthy and aged battery states of life using driving scenarios of an average North-American driver. Furthermore, online estimation of the battery model parameters using square-root recursive least square (SR-RLS) with forgetting factor methodology is conducted. Based on the estimated model parameters, estimation of the battery state of charge using regressed-voltage-based estimation strategy at various states of life is applied. The developed models provide a mechanism for combining the standalone estimation strategy that provide terminal voltage, state of charge, and state of health estimates based on one model to incorporate these different aspects at various battery states of life. Accordingly, a new model-based estimation strategy known as the interacting multiple model (IMM) method has been applied by utilizing multiple models at various states of life. The method is able to improve the state of charge estimation accuracy and stability, when compared with the most commonly used strategy. This research results in a number of novel contributions, and significantly advances the development of robust strategies that can be effectively applied in real-time on-board of a battery management system. / Thesis / Doctor of Philosophy (PhD)

蓄電池は携帯機器，電気自動車をはじめ，自然エネルギー有効利用に至るまで広範囲に利用され，その重要性はますます高まっている。これら機器の使用時間や特性は蓄電池の特性に大きく依存することから，電池自体の特性改善に加え，劣化を診断してより効率的に電池を運用することが求められている。本論文は，非線形情報処理を得意とする人工知能を用いた2次電池の劣化診断法を開発し，エネルギーの有効利用に資する技術を確立した。機器動作時の電池電圧・電流波形と電池劣化特性との関連性を，人工知能を用い学習することにより，機器稼働時に電池の劣化を診断することができる。なお，この関連性は非線形で複雑であるが，非線形分析を得意とする人工知能は劣化診断に適している。学習には時間を要するものの，診断は短時間になし得ることから，提案法は稼働時劣化診断に適している。本論文では，この特徴を生かし，電池の等価回路（ECM）を導出し，充電率（SOC），容量維持率（SOH）を推定している。また，本論文では現在産業応用分野で用いられている，リチウムイオン電池，ニッケル水素電池，鉛蓄電池を対象とし，提案法はあらゆる電池使用機器に応用可能である。また，提案法を電池状態監視装置（BMU）や，マイコンなどを用いた組み込みシステムに応用可能とし，実証している。以上のことから，本論文は，新たな蓄電池の劣化診断法の確立し，その有効性を確認している。 / The importance of rechargeable batteries nowadays is increasing from the portable electronic devices and solar energy industry up to the development of new EV models. The rechargeable batteries have a crucial role in the storage system, mostly in mobile applications and transportation, because the period of its usage and the flexibility of the function are determined by the battery. Due to the black box approach of the ANN it is possible to connect the complex physical phenomenon with a specific physical meaning expressed with a nonlinear logic between inputs and output. Using specific input data to relate with the desired output, makes possible to create a pattern connection with input and output. This ability helps to estimate in real time the desired outputs, behaviors, phenomes and at the same time it can be used as a real time diagnosis method. / 博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University

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<p>This work focuses on the collection and analysis of Lithium-ion battery operational and temperature data during nail penetration testing through two different experimental approaches. Raman spectroscopy, machine learning, and internal temperature sensors are used to collect and analyze data to further investigate the effects on cell operation during and after nail penetrations, and the feasibility of using this data to predict future performance.</p> <p><br></p> <p>The first section of this work analyzes the effects on continued operation of a small Lithium-ion prismatic cell after nail penetration. Raman spectroscopy is used to examine the effects on the anode and cathode materials of cells that are cycled for different amounts of time after a nail puncture. Incremental capacity analysis is then used to corroborate the findings from the Raman analysis. The study finds that the operational capacity and lifetime of cells is greatly reduced due to the accelerated degradation caused by loss of material, uneven current distribution, and exposure to atmosphere. This leads into the study of using the magnitude and corresponding voltage of incremental capacity peaks after nail puncture to forecast the operation of damaged cells. A Gaussian process regression is used to predict discharge capacity of different cells that experience the same type of nail puncture. The results from this study show that the method is capable of making accurate predictions of cell discharge capacity even with the higher rate of variance in operation after nail puncture, showing the method of prediction has the potential to be implemented in devices such as battery management systems.</p> <p><br></p> <p>The second section of this work proposes a method of inserting temperature sensors into commercially-available cylindrical cells to directly obtain internal temperature readings. Characterization tests are used to determine the effect on the operability of the modified cells after the sensors are inserted, and lifetime cycle testing is implemented to determine the long-term effects on cell performance. The results show the sensor insertion causes a small reduction in operational performance, and lifetime cycle testing shows the cells can operate near their optimal output for approximately 100-150 cycles. Modified cells are then used to monitor internal temperatures during nail penetration tests and how the amount of aging affects the temperature response. The results show that more aging in a cell causes higher temperatures during nail puncture, as well as a larger difference between internal and external temperatures, due mostly to the larger contribution of Joule heating caused by increased internal resistance.</p>