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In this work, a battery consisting of eight commercial NMC/graphite cells connected in series was cycled to 60% of its initial capacity. During the test, special care was taken to ensure that the results were not influenced by either the module assembly or the module design. For this purpose, the cells were virtually connected in a laboratory environment with the help of the test device as if they were operated together in a battery. Extrinsic influences that affect cell aging were thus reduced to a minimum. Differential Voltage Analysis (DVA), Electrochemical Impedance Spectrum (EIS), and relaxation measurements were performed to analyze the aging behavior of each cell. The results show that despite a theoretically perfect module design, Cell-to-Cell Variations (CtCV) occurred during aging. The shifting Depth of Discharge (DoD) values among the cells further amplify CtCV. Lithium plating was also observed in the faster aging cells after cyclic aging, suggesting that this aging effect contributes significantly to the development of CtCV. After the aging test, the battery was equipped with an active balancing system that maximizes capacity utilization. More important, the balancing charges which are calculated iteratively within the used balancing algorithm show a strong correlation to the pure capacity losses and thus provide a new way to determine the capacity values of each cell individually without disassembling the battery.

The aim of this work is to age commercial battery cells far beyond their expected lifetime. There is a gap in the literature regarding run to failure tests of lithium-ion batteries that this work intends to address. Therefore, twenty new Samsung ICR18650-26F cells were aged as a battery pack in a run to failure test. Aging took place with a constant load current and a constant charge current to accelerate capacity decrease. Important aging parameters such as capacity and internal resistance were measured at each cycle to monitor their development. The end of the test was initiated by the explosion of a single battery cell, after which the battery pack was disassembled and all parameters of the still intact single cells were measured. The distribution of all measured capacities and internal resistances is displayed graphically. This clearly shows the influence of the exploded cell on the cells in its immediate vicinity. Selected cells from this area of the battery were subjected to computed tomography (CT) to detect internal defects. The X-rays taken with computed tomography showed clear damage within the jelly roll, as well as the triggered safety mechanisms.

In most cases, batteries consist of multiple cells with different interconnections in which the weakest cells determine the usable capacity, performance and lifetime. Since data on initial production-related cell to cell parameter variance is well known, only little data on variance change over lifetime is available. This work investigates how variance spreads with age. Twenty differently aged electric bike (pedelec) batteries are disassembled and the state of health, as well as the internal resistance, are measured cell by cell for each of these batteries. The results show the development of cell to cell variation of aged batteries. Gathered data is also used to calculate capacity limitations through progressed variation. The methodology of the investigation can be used to analyse potential use cases for active balancing systems.

A capacity-based equalization method for active balancing is proposed to increase the usable capacity of aged lithium-ion batteries within a minimum of balancing effort. The main goal of the presented algorithm is to predict the equalization charge for each cell, which is needed to fully charge and discharge every cell of the battery in the next cycle. For this, State-Of-Charge (SOC) and State-Of-Health (SOH) of each cell must be determined. The predicted energy is balanced at the beginning of the cycle and further balancing is performed only if the parameters of the cells change. This ensures that the minimum possible balancing effort is achieved. To validate the performance of the proposed method, a simulation is carried out. For this purpose, a battery model and Battery Management System (BMS) model are built in Matlab/Simulink. The parameters of the simulated cells differ in capacity and initial SOC to imitate an aged battery. The simulation results verify that the developed balancing method can improve the usage of aged batteries compared to conventional methods. This algorithm for active balancing can be used in second life cases of battery systems.