With the advancement of machine-learning and deep-learning technologies, the estimation
of the state of charge (SOC) of lithium-ion batteries is gradually shifting from traditional …

With the aggravation of environmental problems caused by the long-term dependence of
shipping traffic on heavy fossil fuels, it is an irreversible development trend for electrified …

In artificial neural network (ANN) learning, empirical risk can be expressed by training error,
while structural risk can be expressed by network complexity. Learning from data is often …

The low temperature environment poses a significant challenge to the application of electric
vehicles (EVs). At low temperatures, the dynamic characteristics inside the battery become …

With the increase in battery pack scale and strict requirements for weight and volume, full
deployment of sensors is costly and difficult to achieve, and sensor fault may lead to data …

The estimation of State of Charge (SOC) in lithium-ion batteries serves as the foundation for
other state estimations in Electric Vehicle (EV) battery management systems. Accurate SOC …

摘要电子元器件的非接触输运是实现其全自动化生产的瓶颈之一. 伯努利夹持器作为一种非接触
式气动夹持装置被广泛应用于工业中物体的抓取, 定位和运输, 而适用于mm …

The state of charge (SOC) is a core parameter in the battery management system for LMFP
batteries. Accurate SOC estimation is crucial for ensuring the safety and reliability of energy …

Metaheuristic algorithms are commonly used in solving complex and NP-hard optimization
problems in various fields. These algorithms have become popular because of their ability to …

The increasing complexity of power distribution systems, coupled with the growing stress on
power production and the proliferation of nonlinear loads, poses significant challenges to …