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This work proposes a novel approach for state of health estimation of lithium-ion cells by developing a capacity fade model with temperature and Ah throughput dependencies. Two accelerated life cycle testing datasets are used for model calibration: a multi discharge rate dataset of an NMC/graphite cylindrical cell and a multi temperature dataset for an LCO/graphite pouch cell. The multi discharge rate dataset has been recorded at 23 °C and for 4 discharge-rates (C/4, C/2, 1C and 3C). The multi-temperature dataset considers the accelerated ageing of the cells at 4 temperatures (10, 25, 45 and 60 °C). An Arrhenius model is chosen for describing the temperature dependency while a power law model is chosen for cycle (Ah throughput) dependency. The model shows a good agreement with experimental data in each analyzed condition, allowing a precise description of the capacity degradation over time.