Recent advances in energy density of Li-ion cells together with high current fast-charging ask for improved strategies for on board safety and reliability observation of the cells. Potential degradation effects are stimulated by lithium plating and dendrite growth. The latter may ultimately cause an internal short circuit of the cell and can lead to serious damage. Increased self-discharge is an early indicator for safety-critical cell conditions. In this work, accelerated methods for self-discharge determination of Li-ion cells are presented. They are based on the analysis of cell voltage gradients during idle periods and can be applied in state of the art battery management systems performing low drift measurement. However, transition into the idle state after driving requires a settling time of several hours before the voltage gradient can be extracted. For the new accelerated self-discharge determination, a model-based approach was chosen, which also considers aging effects of the open circuit voltage and the cell capacity. The self-discharge behavior of more than 100 automotive cells is studied using the presented methods during a 48-week aging experiment with real driving current profiles. A fast leakage detection procedure is based on the voltage gradient comparison of cell stacks under identical load and temperature conditions. The method is suitable for implementation in battery management systems and improves battery safety monitoring.