A fast-charging policy is widely employed to alleviate the inconvenience caused by the extended charging time of electric vehicles. However, fast charging exacerbates battery degradation and shortens battery lifespan....
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A fast-charging policy is widely employed to alleviate the inconvenience caused by the extended charging time of electric vehicles. However, fast charging exacerbates battery degradation and shortens battery lifespan. In addition, there is still a lack of tailored health estimations for fast-charging batteries;most existing methods are applicable at lower charging rates. This paper proposes a novel method for estimating the health of lithium-ion batteries, which is tailored for multi-stage constant current-constant voltage fast-charging policies. Initially, short charging segments are extracted by monitoring current switches,followed by deriving voltage sequences using interpolation techniques. Subsequently, a graph generation layer is used to transform the voltage sequence into graphical data. Furthermore, the integration of a graph convolution network with a long short-term memory network enables the extraction of information related to inter-node message transmission, capturing the key local and temporal features during the battery degradation process. Finally, this method is confirmed by utilizing aging data from 185 cells and 81 distinct fast-charging policies. The 4-minute charging duration achieves a balance between high accuracy in estimating battery state of health and low data requirements, with mean absolute errors and root mean square errors of 0.34% and 0.66%, respectively.
Modern medicine relies on implantable medical devices (IMDs). Communication between IMDs and external devices is crucial but suffers from increased power consumption due to signal attenuation within biological tissues...
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This study investigated transcutaneous capacitive coupling wireless power transfer (TCC-WPT) for implantable medical devices, aiming to improve patients' QoL. Utilizing numerical electromagnetic field simulations ...
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Neural networks (NN) have been successfully applied to approximate various types of complex control laws, resulting in low-complexity NN -based controllers that are fast to evaluate. However, when approximating contro...
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In recent years, the thermal management of electronic devices has become important due to the increasing performance and miniaturization of electronic devices. Therefore, accurate thermal contact resistance measuremen...
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Hydrogen-oxygen proton exchange membrane fuel cells (HO-PEMFCs) have the advantages of high energy density, quick startup, low emissions, and low noise during operation Therefore, it is suitable to serve as a power so...
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1 Introduction Traditional industrial systems,where physical systems,i.e.,robots and machines,replaced manual labor mostly,are often known as human-physical system(HPS)[1].Cyber system,a major outcome of the digitaliz...
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1 Introduction Traditional industrial systems,where physical systems,i.e.,robots and machines,replaced manual labor mostly,are often known as human-physical system(HPS)[1].Cyber system,a major outcome of the digitalization revolution,is increasingly adopted in HPS and continuously evolving with the development of advanced manufacturing technologies,leading to the human-cyber-physical system(HCPS)[2].
High-speed electric machines have been developed for decades thanks to their high efficiency and power density. The problem with the development of high speed electrical machines is the long and iterative design proce...
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Reinforcement learning (RL) has seen significant research and application results but often requires large amounts of training data. This paper proposes two data-efficient off-policy RL methods that use parametrized Q...
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Regularization of control policies using entropy can be instrumental in adjusting predictability levels of real-world systems. Applications benefiting from such approaches range from cybersecurity, which aims at maxim...
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