Beijing Information Science & Technology University

Tsinghua University

Likun Wang

Lei Qin

Qing Xu

Jianqiang Wang

Jiawei Wang

Keqiang Li

Shengbo Li

Chao Zhong

Xunjia Zheng

Heye Huang

Junbo Jia

Ziqing Gu

An underwater wireless charging method and device using acoustic waves for covering the entire depth of sea is disclosed. Within 10 meters below the water-level, unmanned undersea vehicles (UUV) are charged from a mother ship. Between 10 meters and 100 meters below the water-level, a sound wave is directly sent from the mother ship to the underwater sensor to be charged. At the depth of more than 100 meters below the water-level, an underwater UUV is adopted to in situ charge the underwater sensor node at close range. The transmitting transducer converts electrical energy to sound energy through the inverse piezoelectric effect. The sound wave is then sent by the transducer to a hydrophone that transforms sound energy to electrical energy via the piezoelectric effect. The load can thus be charged. Three types of wireless charging can be realized by the station for different underwater application scenarios, so as to satisfy the wireless charging for covering the entire depth of sea.

Acoustic wave-based full-sea-depth-covering undersea wireless charging method and device

A method for calibrating a driving risk identification model includes: S. establishing a vehicle platform by installing an information acquisition device on a test vehicle; S. acquiring synchronized test data related to the test vehicle and driving scenarios; S. extracting moments when the drivers start to press the accelerator pedal, start to release the accelerator pedal, start to press the brake pedal in the driving scenarios, and start to release the brake pedal, so as to define risk level values respectively corresponding to the moments; S. obtaining a risk identification curve of the drivers in different driving scenarios, wherein the risk identification curve represents the drivers' judgment of the risk level over time; S. using the risk identification curve to calibrate the driving risk identification model.

Driving risk identification model calibration method and system

A shear vibration-based piezoelectric composite material and a preparation method thereof are disclosed. The piezoelectric composite material includes a piezoelectric material and the passive material. The piezoelectric material includes a piezoelectric material polarized along the x-axis positive and a piezoelectric material negatively polarized along the x-axis. The piezoelectric materials in the two polarization directions are alternately arranged along the x-axis direction. The passive material includes a filling layer, a transition layer, and a planar layer. The filling layer is disposed between every two adjacent piezoelectric materials. The planar layer is located outer two surfaces perpendicular to the z-axis of the piezoelectric material. The planar layer on one side is fixedly connected to the filling layer in the odd-numbered position via the transition layer. The planar layer on the other side is fixedly connected to the filling layer in the even-numbered position via the transition layer. The piezoelectric composite material can be used to prepare an underwater acoustic transducer, a hydrophone, piezoelectric energy harvesters, and the like. The invention innovatively converts shear vibrations into the thickness vibrations of the upper and lower surfaces of the composite material, thereby improving the performance of the composite material.

Shear vibration-based piezoelectric composite material and preparation method thereof

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Beijing, China

Likun Wang