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7th International Symposium on System and Software Reliability, ISSSR 2021

作者： Qiu, Yueyou Fang, Junchu Zhu, Zhilong Ministry of Education College of Electrical Engineering Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Wuhu China

ISBN: (纸本)9781665434317

Anti-lock braking system (ABS) can prevent the situation of front and rear wheels locked. However, the car having only ABS is not enough. For example, the distribution of braking force in the early stage of the car braking, and the car in the wet road starting acceleration. In the situation, the car requires ABS and other control systems of the car work together. In this paper, the electronic braking force distribution device (EBD) is integrated into the ABS to form the ABS/EBD braking system based on CAN bus. It consists of speed sensor, CAN bus, control unit and braking force distribution device. The system is used to improve the directional stability of braking before the ABS system starts. By measuring the slip rate of four wheels, the degree of locking is judged, so that the slip rate of four wheels is close, so that all wheels can be locked at the same time as much as possible. Compared with other braking force distribution systems, the system is characterized by the use of CAN bus as the carrier, which effectively improves the system's response ability and computing ability. It is also convenient to combine with other electronic systems on the car to form the intelligent network of the car. © 2021 IEEE.

关键词： Wheels

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An Optimized Design of an Electric Vehicle Wireless Charging Coupling Coil 4

An Optimized Design of an Electric Vehicle Wireless Charging...

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2021 4th International Conference on Mechanical, Electrical and Material Application, MEMA 2021

作者： Xie, Wei Chen, Qi-Gong Lei, Shou-Zhong Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Anhui Polytechnic University Anhui Province Wuhu241000 China

With the development of electric vehicle wireless charging technology, the transmission power and transmission efficiency of electric vehicle wireless charging system have become the focus of current research. The transmission power and efficiency of wireless charging system largely depend on the energy loss of two resonant coupling coils. The energy loss is mainly related to the structural parameters of the coupling coil and the coupling coefficient of the two coils. On this basis, the structure of the coupling coil is designed and optimized by using the finite element analysis software Maxwell, and a new combined transmitting coil structure is designed. Experiments and verification show that the coil design meets the requirements of transmission efficiency, which can provide a reference for the design of wireless charging coil of electric vehicle in the future. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Vehicle transmissions

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SOC estimation of lithium battery based on double modified ampere-hour integral method 37

SOC estimation of lithium battery based on double modified a...

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37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022

作者： Chen, Dong Gao, Wengen Zhang, Chen Chen, Liang High-end Equip. Advanced Perception and Intelligent Control School of Electrical Engineering Anhui Polytechnic University Ministry of Education Heavy Laboratory WuHu241000 China

ISBN: (纸本)9781665465366

When the ampere-hour integral method estimates the battery SOC, the initial value of the SOC in the definition is difficult to determine and the cumulative error caused by the open-loop operation often makes the estimation result inaccurate, which is not conducive to the driver's judgment of the actual remaining battery power, and the safety Adverse effects are coming. This paper uses the open circuit voltage method to modify the initial value of SOC by studying the characteristics of the SOC-OCV curve. And using the partial correlation coefficient to add different weights to the factors that affect the actual capacity of the battery to modify the actual capacity of the battery, thereby eliminating the ampere-hour integral Method due to the cumulative error caused by open-loop calculation. Experimental simulation shows that the ampere-hour integral method modified twice can accurately estimate the SOC of lithium battery, and the estimation accuracy is within 1.6%, which basically solves the problems of the initial SOC value inaccuracy of ampere-hour integral method and the accumulated error caused by the open-loop operation. © 2022 IEEE.

关键词： Lithium batteries

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Three-Dimensional Scene Encryption Algorithm Based on Phase Iteration Algorithm of the Angular-Spectral Domain

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1074-1080页

作者： Chao Han Yuzhen Shen the School of Electrical Engineering Anhui Polytechnic Universityand also with the Key Laboratory of Advanced Perception and Intelligent Control of High-end EquipmentMinistry of EducationWuhu 241000China

In order to increase the capacity of encrypted information and reduce the loss of information transmission, a three-dimensional(3 D) scene encryption algorithm based on the phase iteration of the angular spectrum domain is proposed in this paper. The algorithm, which adopts the layer-oriented method, generates the computer generated hologram by encoding the three-dimensional scene. Then the computer generated hologram is encoded into three pure phase functions by adopting the phase iterative algorithm based on angular spectrum domain,and the encryption process is completed. The three-dimensional scene encryption can improve the capacity of the information,and the three-phase iterative algorithm can guarantee the security of the encryption information. The numerical simulation results show that the algorithm proposed in this paper realized the encryption and decryption of three-dimensional scenes. At the same time, it can ensure the safety of the encrypted information and increase the capacity of the encrypted information.

关键词： Angular spectrum diffraction information capacity phase iteration three-dimensional scene encryption

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Finite-horizon H∞State Estimation for Discrete-Time Memristive Neural Networks with Time-Varying Delays and Fading Channels: A Dynamic Event-Triggered Approach

Finite-horizon H∞State Estimation for Discrete-Time Memrist...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Zhu, Jiali Liu, Hongjian Tao, Huimin Tan, Hailong Ministry of Education Anhui Polytechnic University School of Mathematics-Physics and Finance Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Wuhu China

ISBN: (纸本)9781665412872

In this paper, we consider the H∞ finite-horizon state estimation issue for a class of discrete-time memristive neural networks (DMNNs) with time-varying delays and multiple fading channels. A set of correlated random variables are used to study the correlated fading channels. Specifically, the channel coefficients are assumed to be scalar white noise processes satisfying certain probability distribution laws. At the same time, in order to reduce unnecessary resource consumption in the communication channel between the sensor and remote estimator, a dynamic event-triggered transmission strategy is introduced. Our goal is to construct a set of dynamic event-triggered H∞ estimators to ensure that the DMNNs reaches the specified interference attenuation level over a finite time-horizon. With the combination of the Lyapunov-Krasovskii function and stochastic analysis method, sufficient conditions are obtained for the expected estimator. Then, the estimator gains are calculated by solving a set of convex optimization problems. Finally, an example is given to verify the effectiveness and usefulness of the developed state estimation scheme. © 2021 IEEE.

关键词： Fading channels

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Virtual Sample Generation Methods and Application in Few-Shot Object Detection for Industrial Scenarios

Virtual Sample Generation Methods and Application in Few-Sho...

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Chinese Automation Congress (CAC)

作者： Xiuwen Tao Guoyang Wan Ming Jiang Jian Zhang Qianqian Wang Qin He Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Polytechnic University School of Electrical Engineering Anhui Polytechnic University Wuhu China

Due to the long-term relatively fixed state of industrial installations, the diversity of industrial data is low, with high repetitiveness and uneven distribution, which makes industrial few-shot object detection still challenging. Therefore, from the perspective of handling the dataset, this paper proposes a virtual sample generation method based on virtual reality. Firstly, by using a virtual engine, the target workpiece model is created to directly simulate the states of the workpieces captured by the visual system in various environments. Secondly, random algorithms are added and improved to simulate workpieces with different materials and degrees of wear, distributed in random positions with different poses and types in the visual system, thereby generating virtual samples containing workpieces. Finally, virtual samples are introduced for experimental testing in the target detection network. The proposed method is tested in both YOLOv5 and YOLOv7 and compared with datasets without virtual samples, resulting in an improvement of 3.06% and 2.23% in mAP values, respectively. The experimental results demonstrate that the proposed method effectively improves the issue of industrial small-sample object detection.

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PM-UNet: Lightweight network for lung image segmentation

PM-UNet: Lightweight network for lung image segmentation

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Lina Qiao Wengen Gao Liang Chen Ling Jiang High-End Equipment Advanced Perception and Intelligent Control Ministry of Education Heavy Laboratory School of Electrical Engineering Anhui Polytechnic University WuHu China

In the field of image segmentation, it has been a research topic to pursue the lightweight of the model as much as possible without affecting the segmentation accuracy. The traditional U-Net is the classical segmentation model, but the number of parameters and computation required by the model are too large. To address this drawback, a lightweight network PM-UNet is proposed for lung image segmentation. Firstly, the ordinary 3×3 convolution used in the conventional U-Net is replaced by the new Inverted Residual Depthwise Separable convolution block to lighten the U-Net model. Also, to further compress the model, the four upsampling and downsampling networks of the lightweight U-Net are cut in half to simplify the network model. And atrous spatial pyramid pooling is used to expand the convolutional receptive field and add feature information of different scales. The attention gate can strengthen the information fusion effect of high-level and low-level information in the skip connection. The segmentation experiments were validated by using the LUNA competition lung image dataset, with the improved network model requiring only 2.2% and 14.4% of the number of parameters and computation of the traditional U-Net network, respectively. The experimental results of the network model achieved Accuracy of 0.991 and IOU of 0.958 on the test set, which is 0.6% improvement in Accuracy and 2.6% improvement in evaluation metric IOU compared to the conventional U-Net, and were tested against mainstream and recent segmentation networks. These results demonstrate that PM-UNet, which is improved on the basis of U-Net, has better segmentation effect on medical images.

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Power Allocation Strategy of Multivariate Hybrid Energy Storage System Suitable for Microgrid

Power Allocation Strategy of Multivariate Hybrid Energy Stor...

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Chinese control and Decision Conference, CCDC

作者： Feifan He Wengen Gao Mengxing Pan Lina Qiao High-End Equipment Advanced Perception and Intelligent Control Ministry of Education Heavy Laboratory School of Electrical Engineering Anhui Polytechnic University WuHu China

Considering that hybrid energy storage system is regarded as one of the important components of microgrid, it is of great significance to study its power allocation strategy. The power fluctuation of microgrid is decomposed into three different components: random component, pulse component and continuous component. Accordingly, a multivariate hybrid energy storage system composed of supercapacitor, lithium iron phosphate battery and all-vanadium redox flow battery was used to stabilize the power fluctuation in microgrid; Two frequency dividing points of power fluctuation were obtained by wavelet transform, which were decomposed into three frequency components by a low-pass filter and a high-pass filter. Combined with system constraints, the power allocation strategy of multivariate hybrid energy storage system was designed. Compared with the traditional energy storage system, the simulation results showed that the multivariate hybrid energy storage system could effectively reduce the charging and discharging power as well as charging and discharging times of supercapacitors and lithium batteries, maintain the SOC fluctuation between 30% and 70%, and possess a more reasonable working range, thus prolonging the service life of energy storage components.

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Lightweight super-resolution networks with global and local residual characteristics

Lightweight super-resolution networks with global and local ...

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2022 International Symposium on intelligent Robotics and Systems, ISoIRS 2022

作者： Wang, Yunlong Xiong, Lei Wang, Fengsui Xu, Yue School of Electrical Engineering Anhui Polytechnic University Anhui Wuhu241000 China Key Laboratory of Testing Technology and Energy Saving Devices Anhui Province Wuhu241000 China Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Anhui Wuhu241000 China

ISBN: (纸本)9781665455213

At present, there is a problem of complexity and calculation of the image super-resolution algorithm network. To improve this problem, we propose a lightweight super-resolution network that blends global and local features. First, shallow image features are extracted using a convolutional block, and secondly, deep features are extracted by multiple cascading residual feature distillation blocks GLRB, where in order to achieve a good trade-off between model performance and network parameter quantity, local features are learned by enhancing the feature selection module ESA and the balanced dual-attention module to improve model performance. Then, the extracted residual features are fused, and the reconstructed image is obtained by sub-pixel convolution sampling. The experimental results under multiple standard test data sets show that the reconstructed image performance PSNR is improved by 0.25 dB to 32.23, and the number of model parameters is 470.21 K. Compared with DRCN, CARN, IMDN, RFDN and other algorithms, the proposed algorithm has better model lightweight and image reconstruction quality. © 2022 IEEE.

关键词： Distillation

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Research on traffic sign detection algorithm in complex weather

Research on traffic sign detection algorithm in complex weat...

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2022 International Workshop on Automation, control, and Communication Engineering, IWACCE 2022

作者： Liu, Rui Xu, Xiaoguang Hao, Xuyao Zhang, Xin Ding, Ruming School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Anhui Polytechnic University Anhui Wuhu241000 China Anhui Zuobiao Intelligent Technology Co. LTD. Anhui Wuhu24100 China

ISBN: (纸本)9781510660915

Under complex weather conditions, the vehicle vision system has low recognition accuracy for traffic signs, and there are problems such as missed detection and false detection. An improved YOLOX-S traffic sign detection model is proposed. Firstly, a detection layer is added to the YOLOX-S network, so that the model can effectively detect the minimum target and improve the prediction ability of the model. Then the attention mechanism module is added to the YOLOX-S feature fusion network to strengthen the feature extraction function of the network. Finally, the data enhancement mechanism is introduced to the model, so that the detection of the model in severe weather such as haze and rain and snow has strong robustness. The detection model was tested on the Chinese Traffic Sign Detection Benchmark dataset (CCTSDB). The results show that the mAP @ 0.5 of the improved algorithm is 2.67 % higher than that of the original YOLOX-S algorithm, and the mAP @ 0.5: 0.95 is 4.58 % higher than that of the original YOLOX-S algorithm. The model meets the requirements of real-time detection. © 2022 SPIE. All rights reserved.

关键词： Traffic signs

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