Understanding the aging behavior in lithium-ion cells for automotive applications and its underlying physical-chemical degradation processes that lead to a decrease in energy and power density is crucial for the prediction of battery lifetime. Furthermore, the process of parameterization for physical-chemical motivated models with implemented aging mechanisms is a challenging task. In this work, we present a technique to quantify the loss of cyclable lithium and the decrease of electrode capacities. In addition, the inhomogeneous distribution of lithium inside the cell is estimated by introducing a fit factor to describe the vanishing of peaks in the first derivative of the open circuit voltage curve in respect to state of charge. Differential voltage analysis is performed using an algorithm inspired by pattern search. The algorithm uses the idea of superpositioning multiple open circuit voltage curves with individual distribution of losses. A dataset of ten automotive pouch cells with NMC-622 cathode and graphite anode that were cycled with varying load profiles is used for testing and validation of the method. The method reveals significant differences in the aging behavior and state of homogeneity of cells that cannot be obtained by solely analyzing capacity and resistance evolution.