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.

Die Arbeit befaßt sich mit der Messung und Analyse der spezifischen Wärme verschiedener stark korrelierter Elektronensysteme bei tiefen Temperaturen und hohen Magnetfeldern. Zunächst wird der im Rahmen dieser Arbeit verwendete, auf der Meßmethode der thermischen Relaxation beruhende Aufbau des Kalorimeters (Einsatzbereich 0.05K<T<4K und 0<B<12T) ausführlich erläutert. Danach werden die Ergebnisse von Messungen an den drei Schwere-Fermionen-Verbindungen CeCu2Si2, CeNi2Ge2 und YbRh2Si2 dargelegt. Wenngleich alle drei Systeme bei tiefen Temperaturen durch den für Schwere-Fermionen-Systeme charakteristischen, stark erhöhten elektronischen Beitrag zur spezifischen Wärme gekennzeichnet sind zeigen sich deutliche Unterschiede im beobachteten Grundzustandsverhalten. An CeCu2Si2 wird die für T<1K auftretende Konkurrenz zwischen einem supraleitenden und einem magnetischen Grundzustand ausführlich studiert. In YbRh2Si2 zeigt sich bei einer für 4f-Systeme bemerkenswert tiefen Temperatur von ca. 70mK ein Übergang in eine magnetische Phase, während der Grundzustand von CeNi2Ge2 wegen stark ausgeprägter Probenabhängigkeiten immer noch kontrovers diskutiert wird. Des weiteren zeigen alle drei Verbindungen deutliche Abweichungen vom Verhalten einer Fermi-Flüssigkeit. Die Theorie der Fermi-Flüssigkeit hat sich für metallische Verbindungen als sehr erfolgreich auch bei der Beschreibung des Verhaltens eines Systems aus stark wechselwirkenden Ladungsträgern erwiesen. Warum diese Theorie auf die untersuchten Verbindungen nicht anwendbar zu sein scheint, wird im Rahmen moderner Modellvorstellungen wie z. B. der Nähe zu einem quantenkritischen Punkt diskutiert. Die an Sr2RuO4, dem ersten Kupfer-freien Perowskit Supraleiter, durchgeführten Messungen der spezifischen Wärme dokumentieren das Auftreten von zwei Zusatzbeiträgen für T<Tc, die eine Interpretation der spezifischen Wärme des supraleitenden Zustands von Sr2RuO4 im Hinblick auf die Topologie des Ordnungsparameters deutlich erschweren.