Data-driven and temperature-cycles based remaining useful life estimation of an electronic device

A method for estimation of remaining useful life or state of health of an electronic device, such as a battery, the method comprising the steps of: estimating state of charge (SoC) of the electronic device based on measured voltage, and/or current, and/or cell temperature using a machine learning state of charge estimation model;5estimating an accumulated damage in the electronic device based on the output of the machine learning state of charge estimation model and a machine learning incremental damage model, wherein the machine learning incremental damage model is trained with laboratory data and real life and/or field operation data from the electronic device itself and/or from similar electronic devices; and based on the accumulated damage, 10estimating the remaining useful life or the state of health of the electronic device.