This PhD project develops a novel parallel testing methodology to significantly shorten lifetime tests of lithium-ion cells. It integrates experimental characterization, accelerated aging, and predictive lifetime estimation using electrochemical methods (e.g., EIS, ICA), physics-based models (ECM, SPMe, DFN), and data-driven estimation. Continuous parameterization and simulation during testing enable adaptive strategies that identify critical stress regions and reduce test durations from 30,000 to ~3,000 hours. A focus on coupled electrochemical and thermal models allows realistic representation of high-demand commercial vehicle applications. Results aim to accelerate the development of future battery systems and provide a foundation for industrial qualification procedures.