No abstract

No abstract

No abstract

No abstract

No abstract

No abstract

Accurate State of Health (SoH) diagnosis and prognosis of Lithium-ion batteries (LIBs) may become an important estimate for the Battery Management System (BMS) if it can be acted upon to de-rate the demands placed on the battery in order to reduce the rate of ageing and to extend battery life. The BMS often quantifies SoH based on capacity (SoHE) and power fade (SoHP) without diagnosing the root causes. In line with this, Incremental Capacity (IC) and Differential Voltage (DV) techniques are used to identify and quantify degradation modes as well as to estimate and to predict the SoHE. These techniques were applied to four parallelised LIBs loaded with a constant current profile for 500 cycles. Loss of active material and loss of lithium ions were identified to be the most relevant degradation modes for this experiment. Moreover, a linear relationship between the intensity of the peaks of the IC and DV curves were identified with respect to the SoHE. This result may enable the future estimation and prediction of SoHE in a simple way. Overall, the outcomes of this work may support novel strategies to control SoHE within the BMS, so that the rate of battery degradation can be reduced.