Accurate online state-of-health (SOH) estimation can improve the operational efficiency of lithium-ion batteries (LIBs) and ensure the safety of energy storage systems. However, the complex electrochemical properties of LIBs make accurate SOH estimation challenging. To overcome this challenge, we propose a secondary structural ensemble learning (SSEL) cluster.
View Article and Find Full Text PDFWith the development of China's electric power, power electronics devices such as insulated-gate bipolar transistors (IGBTs) have been widely used in the field of high voltages and large currents. However, the currents in these power electronic devices are transient. For example, the uneven currents and internal chip currents overshoot, which may occur when turning on and off, and could have a great impact on the device.
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