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773 results on '"Chen, Huipeng"'

36. Coordinated Control of Differential Drive-Assist Steering and Direct Yaw Moment Control for Distributed-Drive Electric Vehicles.

Author

Zhu, Shaopeng, Lu, Junfei, Zhu, Ling, Chen, Huipeng, Gao, Jian, and Xie, Wei

Abstract

Direct yaw moment control (DYC) and differential drive-assist steering (DDAS) for distributed-drive vehicles are both realized by allocating the in-wheel motor torque. To address the interference caused by overlapping control objectives, this paper proposes a multilayer control strategy that integrates DYC and DDAS, consisting of an upper controller, a coordinated decision layer, and a torque distribution layer. The upper controller, designed based on the vehicle's dynamic characteristics, incorporates an adaptive fuzzy control DYC system and a dual PID control DDAS system. The coordinated decision layer is developed utilizing a phase-plane dynamic weighting method, delineating region boundaries by applying the double-line and limit cycle methods. The torque distribution strategy is formulated considering motor peak torque and road adhesion conditions. Multi-condition joint simulation experiments indicate that the proposed multilayer control strategy, integrating the advantages of DYC and DDAS, reduces peak steering wheel torque by approximately 10%, peak yaw rate by around 25%, peak sideslip angle by roughly 29%, and peak sideslip angle rate by about 19%, significantly improving driving stability and maneuvering flexibility. [ABSTRACT FROM AUTHOR]

Published
2024
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38. Point Calculation Detection System Based on In Suit Convolution Transistor for Clinical Diagnosis of Heart Disease.

Author

Cheng, Enping, Zhang, Xianghong, Wu, Jianxin, Chen, Hao, Liu, Di, Fan, Yuyang, Lian, Minrui, Guo, Tailiang, and Chen, Huipeng

Subjects
PATTERN recognition systems, ELECTRIC field effects, CONVOLUTIONAL neural networks, SIGNAL processing, TIMING circuits
Abstract

Electrocardiograph signals reflect the current state of the heart and have great significance to the clinical diagnosis of the heart. Convolutional neural networks perform excellently in electrocardiograph pattern recognition. However, CNNs processing ECG signals need to convert them from 1D to 2D, leading to additional circuit and time costs in hardware. Here, a convolution organic transistor (COT) is proposed for monitoring the ECG with CNNs. Based on the surface electric field effect and trap effect, COT can directly process 1D ECG data without complex preprocessing. It can complete the convolution calculation of ECG signals ≈20 000 times per second in theory and reduce the number of devices by 83% compared to conventional arrays. Further, actual ECG signals are measured and input into the COT, which can initially recognize the type of ECG abnormality. Finally, a point calculation detection system is established with 96.2% recognition accuracy in the five‐heartbeat classification task by combining the 1D CNN. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Stretchable and stable neuromorphic tactile system.

Author

Liu, Yaqian, Wang, Hui, Lin, Jiaming, Ye, Weixi, Rao, Zhichao, Lu, Wenjie, Huang, Bingle, and Chen, Huipeng

Abstract

Artificial neuromorphic tactile systems based on tactile sensors and artificial neurons can simulate biological perception systems and achieve the efficient transmission, processing and utilization of information. However, limited by the materials and structures of devices, it is difficult for artificial neuromorphic tactile systems to have stable perception abilities such as biological functions, especially when the devices are bending or stretching. In this work, we propose a performance-stable artificial tactile neuron, which integrates a stretch-insensitive triboelectric nanogenerator (TENG) with an artificial neuron in a single device. The stable contact triboelectric output could stimulate a neuron and affect its firing time. Based on this principle, we established a 64 × 64 neuromorphic tactile matrix, which processed the triboelectric signal generated by touch through the integrate-and-fire neuron and simulated the pressure trajectory and texture of tactile perception based on the firing time classification. This provides an effective strategy for the future simulation of biological skin perception and fast classification and recognition of information. [ABSTRACT FROM AUTHOR]

Published
2024
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