Lead acid batteries are widely used in domestic, industrial and automotive applications. Even after lot of advancements in battery technologies, lead acid cells are still in use because of their high capacity and low cost. To use any battery effectively, first we should be able to identify the available capacity or State of Charge (SoC). There are many techniques available to measure SoC of a lead acid battery. One such unique method is to measure the capacity using eddy current sensors. This method is unique because it is non-obtrusive and online. Eddy current sensors (ECS) are wire wound inductors which work on the principle of electromagnetic induction. Eddy currents are the currents generated on a conductive material when it is kept in a varying magnetic. Eddy current sensors generate varying magnetic eldest and will be able to identify the properties of conductive materials like thickness, conductivity, material composition etc. Also they can be used as proximity sensors. Lead acid batteries use lead metal as cathode. Upon usage(discharge) the lead metal converts to lead sulfate and revert back to lead after charging. These changes in lead electrode can be monitored using eddy current sensors. The impedance of an eddy current sensor will change when it is kept close to the lead electrode when the battery is charging or discharging. These impedance parameters can be monitored to determine the battery SoC. When lead is deposited on cathode, there will be more eddy current loss in the target and the total resistance of coil increases. On the other hand, when lead is deposited on the electrode because of increase in the magnitude of eddy currents which oppose the source magnetic, the total inductance of coil decreases. We can observe exactly opposite behaviour of coil resistance and inductance when the lead electrode is converted to less conductive lead sulfate. There is a lot of research on using ECS to measure SoC of lead acid batteries and there are still many challenges to be addressed. First we have explained about different circuit designs we have used to monitor the battery capacity using eddy current sensors. After that, we have explained about our complete experimental setup and the procedure to measure the sensor parameters using the setup. Then, we have discussed about different issues involved in the eddy current sensing based state of charge measurement. Eddy current sensors are affected by temperature variations. We have studied the coil resistance behaviour with temperature at different frequencies using simulations and experiments. We have obtained the conditions for linear variation of coil resistance with temperature. The measured temperature compensation scheme is applied and the results are discussed. We have also modified the measurement system design in order to minimize the lift o errors. We have used a metallic clamp structure to minimize the lift o errors. We have used finite element analysis based simulations to study different design parameters and their effect on the sensitivity of eddy current sensor. We have created 2D eddy current models and the sensitivity of coil resistance is computed by changing the coil dimensions and the core permeability. We have also performed error analysis and computed the error due to the tilt angle shift between coil and electrode. We have also computed the error due to the internal heating of battery. We have also studied the effect of acid strati cation on state of charge for both sealed and hooded batteries. We have proposed a multi coil method to minimize the errors in SoC measurement due to acid strati cation for Flooded type batteries. We have used finite element analysis based simulations to compute the error due to acid strati cation by increasing the number of coils. Finally we have derived the equation for electrode Q factor using the transformer model of eddy current sensor. The derived Q factor equation is then used to study the aging of lead acid batteries both by using experiments and simulations. Finally we have explained a detail procedure to measure the state of charge(SoC) and state of health(SoH) of a hooded lead acid battery using eddy current sensing method.

<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>

1. Unterschiedliche Definitionen der Gesundheit mit verschiedenen Betrachtungsweisen (WHO: Der Mensch eine biopsychosoziale Einheit. Schulmedizin: ohne klinischen und paraklinischen Befund mit Orientierung an kritikbedürftigen Referenzmittelwerten) führt bei Fachleuten, Behörden und Laien zu Verwirrungen, wenn es um die Beurteilung gesundheitlicher Schäden geht. 2. Es wurde die Aufgabe gestellt zu prüfen, welche der beiden Definitionen der Realität näher kommt. 3. Mittels der chronopsychobiologischen Regulationsdiagnostik, des Dreiphasenentspannungstests (Hecht und Balzer 2001), wurden unter dem Aspekt der beiden Gesundheitsdefinitionen drei Gruppen untersucht (je 40 Probanden). - klinisch Gesunde (klinisch Gesunde nach Schulmedizin ) - Gesunde nach Definition der WHO - Probanden mit nichtorganische Insomnie (ohne pathologische klinische und paraklinische Befunde) 4. Die mit den verwendeten Methoden gewonnenen Daten wiesen aus, dass zwischen den klinisch Gesunden und den Probanden mit nichtorganischer Insomnie weitgehend größere Ähnlichkeiten bestehen. Beide Gruppen zeigten aber zu der Gruppe der Gesunden nach WHO-Definition, welche die biopsychosoziale Einheit des Menschen berücksichtigt, noch hochsignifikante Unterschiede. Die Gruppe der klinisch Gesunden kann daher auf Grund unserer Ergebnisse nicht den Anspruch erheben, real gesund zu sein. 5. Mit der Bezugnahme auf die Internationale Klassifikation der Krankheiten (ICD 10F) haben die von uns untersuchten klinisch Gesunden und die nichtorganischen Insomniker eine mehr oder weniger stark ausgeprägte Symptomatik von psychischen Störungen. Dies müsste bei der Beurteilung von Schadstoff-, Lärm-, und EMF-Wirkungen auf den Menschen, wie auch bei den klinisch-pharmakoloischen Untersuchungen beachtet werden. Die in der Arbeit erzielten Ergebnisse bedürfen durch weitere Untersuchungen eine Fundierung. Sie signalisieren aber sowohl unter praktischen als auch unter theoretischen Aspekten einen dringenden Forschungsbedarf. / 1. Differing definitions of health using different criterea (WHO: The human being as a bio- psycho-social unit versus classical medicine: without clinical and paraclinical results based on suspect reference values) bring confusion to experts, authorities and laymen when assessing health damages. 2. The given task was to check which of the two definitions is closer to reality. 3. Using the chrono-psycho-biological diagnostic of regulation, the three-phase-relaxation test (Hecht and Balzer 2001), three groups were examined considering the aspects of the two health definitions (40 test subjects in the study group). - clinically healthy (clinically healthy per classical medicine definition) - healthy per definition of the WHO - test persons with non organic insomnia (i.e. no pathological or paraclinical findings) 4. The data gained from the employed methods revealed bigger similarities between clinically healthy persons and those with non organic insomnia. Both groups still showed highly significant differences to the group which fulfils the definition of the WHO regarding a human as a bio-psycho-social unit. As a result of this study, persons, though classified as "clinically healthy" might nevertheless not absolutely be healthy in reality. 5. In reference to the international classification of illnesses (ICD 10 F) the groups examined, both of clinically healthy and those with non organic insomnia, have more or less severe psychological symptoms. This should be taken into account when assessing the effects of pollution, noise, and EMF as well as clinical pharmacological studies. These present findings still need broader confirmation by further investigations. However, they clearly indicate, for practical and theoretical considerations, an urgent need for further research.