2篇
您的检索式：作者名="Shuowei Li"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Designing all-solid-state Z-Scheme 2D g-C_3N_4/Bi_2WO_6 for improved photocatalysis and photocatalytic mechanism insight显示文摘Bi_2WO_6 was modified by two-dimensional g-C_3N_4(2D g-C_3N_4)via a hydrothermal method.The structure,morphology,optical and electronic properties were investigated by multiple techniques,including X-ray diffraction(XRD),X-ray photoelectron spectroscopy spectra(XPS),Fourier transform infrared spectroscopy(FT-IR),scanning electron microscopy(SEM),transmission electron microscopy(TEM),Ultravioletvisible diffuse reflection spectroscopy(DRS),photocurrent and electrochemical impedance spectroscopy(EIS),electron spin resonance(ESR),respectively.Rhodamine B(Rh B)was used as the target organic pollutant to research the photocatalytic performance of as-prepared composites.The Bi_2WO_6/2D g-C_3N_4exhibited a remarkable improvement compared with the pure Bi_2WO_6.The enhanced photocatalytic activity was because the photogenerated electrons and holes can quickly separate by Z-Scheme passageway in composites.The photocatalytic mechanism was also researched in detail through ESR analysis. | Mao Mao Shuowei Zhao Zhigang Chen Xiaojie She Jianjian Yi Kaixiang Xia Hui Xu Minqiang He Huaming Li | 2018 | Green Energy & Environment2018，3，3： | 1 |
| 2 | Fault diagnosis for lithium-ion batteries in electric vehicles based on signal decomposition and two-dimensional feature clustering显示文摘Battery fault diagnosis is essential for ensuring the reliability and safety of electric vehicles(EVs).The existing battery fault diagnosis methods are difficult to detect faults at an early stage based on the real-world vehicle data since lithium-ion battery systems are usually accompanied by inconsistencies,which are difficult to distinguish from faults.A fault diagnosis method based on signal decomposition and two-dimensional feature clustering is introduced in this paper.Symplectic geometry mode decomposition(SGMD)is introduced to obtain the components characterizing battery states,and distance-based similarity measures with the normalized extended average voltage and dynamic time warping distances are established to evaluate the state of batteries.The 2-dimensional feature clustering based on DBSCAN is developed to reduce the number of feature thresholds and differentiate flaw cells from the battery pack with only one parameter under a wide range of values.The proposed method can achieve fault diagnosis and voltage anomaly identification as early as 43 days ahead of the thermal runaway.And the results of four electric vehicles and the comparison with other traditional methods validated the proposed method with strong robustness,high reliability,and long time scale warning,and the method is easy to implement online. | Shuowei Li Caiping Zhang Jingcai Du Xinwei Cong Linjing Zhang Yan Jiang Leyi Wang | 2022 | Green Energy and Intelligent Transportation2022，1，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员