Capacity Degradation of Flexible Li-Ion Power Sources Subjected to Shallow Discharging

Abstract

Estimating the state of a system especially for lithium-ion battery has been an area of extensive research; where most of the remaining useful life (RUL) prediction techniques are highly dependent on usage of offline data. Development of a prognostics health management (PHM) framework for flexible electronics and flexible components is still in its nascent stages due to the novelty and understanding of the flexible regime. Little to no information exists on techniques which incorporate depth of discharge (DoD) and other varying test parameters such as varying load (across test conditions) and can then successfully evaluate the degradation in capacity and compute the remaining useful life for flexible lithium-ion power sources. Flexible electronic systems need to have a thin, robust power system that also has the capability to sustain dynamic stresses which are replicative of daily motions. Such applications can foresee the usage of flexible power sources in areas with both direct mechanical and environmental stresses. Current health monitoring techniques and test standards for rigid power sources which are used in portable electronics and electric vehicles (EVs) demonstrate robust and efficient RUL techniques with some of them considered as the benchmark in terms of model accuracy. With the current boom in internet of things (IoT), flexible power sources/flexible energy harvesting units will be the go to product of the industry for the next couple of decades. Therefore it is the need of the hour to develop PHM frameworks for such flexible lithium-ion based power sources. In this research study, 60mAh flexible lithium-ion batteries have been analyzed by cycling them through multiple full charge and shallow discharge cycles at distinct DoD operating conditions. Effects of simultaneous thermal stresses and repeated cyclic events have been studied on output parameters such as efficiency, capacity and charge-discharge time. State-Of-the-art Li-Ion batteries have been tested under: multiple operating temperatures of 40°C and 25°C with different Crates. In this paper, capacity and “number of cycles” have been used as vectors to monitor the health of the power source and assess remaining useful life. Regression based modeling technique has been used to estimate the battery capacity deterioration in form of number of cycles to reach the end of life (EoL) which is about 80% of the original life.