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Method and system for testing the working characteristics of vehicle fuel injector

Recent Patents on Mechanical Engineering 2021年第1期14卷 63-74页

作者： Liu, Bin Li, Yanhao Han, Fangfang Qiao, Qian Li, Jianwen Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin300384 China School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin300384 China

Background: The vehicle fuel injector directly affects the power performance, emission characteristics and economic efficiency of the engine. At present, several testing standards are stipu-lated on accurate measurement of the working characteristics of fuel injectors. Objective: The purpose of this study is to provide an efficient patent about the method and system for testing the working characteristics of a vehicle fuel injector. Methods: Two key techniques are significant to establish a standard test environment. The patent about the pressure control approach and the injector driving method was proposed. The adaptive fuzzy PID approach was applied to control pressure. An adaptive multi-functional driver was designed and developed for both the voltage-driven and current-driven port fuel injectors. Results: The experiments on the two key technologies were conducted. During the dynamic flow test, the settling time using the system was 1ms. For the static flow test, the settling time was 1 s. The maximum changing rate of pressure fluctuation was 1%. Then, the system was verified by test on the flow characteristics and dynamic response of the voltage-driven and current-driven injectors. The linear deviation of each dynamic flow curve was between ± 3% to ± 6%. Furthermore, the deviation of the dynamic flow curves from the repeated test was small. The maximum deviation of the static flow results was less than 4% and the dynamic response of the injector varied with the change of the pressure. Conclusion: The system meets the requirements of the related standards. The experimental results prove that the system is stable and reliable. © 2021 Bentham Science Publishers.

关键词： Dynamic response

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Global Path Planning of Unmanned Surface Vehicles Based on Deep Q Network

Global Path Planning of Unmanned Surface Vehicles Based on D...

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第43届中国控制会议

作者： Shuhao Li Yuehui Ji Junjie Liu Zhongli Bai Jiajun Hu Qiang Gao Tianjin Key Laboratory of Control Theory and Application for Complex Systems Maritime College Tianjin University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The paper proposes an autonomous global path planning algorithm for unmanned surface vehicles(USV) in complex sea areas based on Deep Q Network(DQN).This algorithm integrates the artificial potential field method with the DQN algorithm to design action space and a new greedy *** also introduces a reward function based on potential energy and a penalty item for threat *** results demonstrate that compared to the traditional DQN algorithm,the algorithm proposed in this paper reduces training time by 35.27%,shortens path length by 8.71%,and decreases convergence iterations by 56.36%.Compared to the other three algorithms,such as Q-learning,the paths planned by the algorithm in this paper are more reasonable,smooth,and *** research results validate the practicality and effectiveness of the proposed algorithm,which has significant practical implications for the development of autonomous global path planning technology for USV.

关键词： Path planning Unmanned surface vehicles Deep Q network Artificial potential field Grid method

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Online Reentry Trajectory Optimization for Hypersonic Vehicles Using Radau Pseudospectral Sequential Convex Programming

Online Reentry Trajectory Optimization for Hypersonic Vehicl...

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第43届中国控制会议

作者： Zhifei Song Junjie Liu Yuehui Ji Haobo Zhang Junchi Wang Qiang Gao Tianjin Key Laboratory of Control Theory and Application for Complex Systems Maritime College Tianjin University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In this paper,an online trajectory optimization scheme is proposed to address the uncertainties and mission changes in hypersonic vehicle reentry trajectory *** combining Radau pseudospectral method and sequential convex programming(SCP),the discretization accuracy and solution speed of the trajectory optimization algorithm are ***,the downrange angle is used as the independent variable in the equations of motion to implement the free time trajectory optimization *** initial trajectory generation method is proposed,which makes the trajectory's terminal state close to the terminal position and thus reduces the number of algorithm optimization ***,the compensation and regularization terms are used,respectively,to maintain the feasibility of the trajectory optimization problem and to improve the convergence rate of the *** the end,the proper trajectory optimization period is set,and the interior-point method is used to solve the reentry trajectory optimization *** simulations demonstrate the validity of the algorithm and online reentry trajectory optimization scheme proposed in this paper.

关键词： Radau pseudospectral method Hypersonic vehicle Sequential convex programming Online reentry trajectory optimization

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Chaos Suppression of Power System Based on Finite-time Adaptive Sliding Mode control 20

Chaos Suppression of Power System Based on Finite-time Adapt...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Wang, Hongjun Li, Shuyi Zhao, Hui Yue, Youjun Tianjin University of Technology Key Laboratory of Control Theory and Application for Complex Systems in Tianjin Binshui Xidao Extension 391 Tianjin300384 China Tianjin Agricultural University College of Engineering and Technology 22 Jinjing Road Tianjin300384 China

ISBN: (纸本)9798350320831

Under certain conditions, the power system will produce chaotic oscillation, which may impact the safety and stability of the power grid. Under the action of inductive load, the power system will generate a certain amount of reactive power. Excessive reactive power will lead to the deviation of the voltage phase angle of the power system. Usually, reactive compensation equipment is used to absorb the reactive power in the power system and adjust the voltage phase angle. In this article, the dynamics analysis of chaotic oscillation of the second-order power system model (SOPSM) is firstly carried out, and a global adaptive sliding mode controller based on finite time is designed by comprehensively using backstepping, fixed-time controller and adaptive sliding mode control methods (ASM), which not only realizes the suppression of chaotic oscillation of the power system, but also reduces the computational burden and improves the convergence speed of the system, Finally, MATLAB/Simulink numerical simulation shows that the designed controller can quickly restore the power system from chaotic state to equilibrium state, thus verifying the effectiveness and efficiency of the controller. © 2023 IEEE.

关键词： Sliding mode control

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Research on Optical Power Attenuation Compensation Algorithm of φ-OTDR System 20

Research on Optical Power Attenuation Compensation Algorithm...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Liu, Yinhao Zhang, Baofeng Zhang, Zhili TianJin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems No. 391 Binshuixi Road Tianjin300384 China Intelligent Manufacturing Institute TianJin Sino-German University of Applied Sciences No. 2 Yashen Road Tianjin300350 China

ISBN: (纸本)9798350320831

The φ-OTDR technology is an optical fibre sensing method that enables real-time monitoring of fibre vibrations by using optical time domain reflection technology. However, during the process of transmitting signals through optical fibres, the issue of optical power attenuation arises, which ultimately results in a reduction of the long-distance signal recognition ability of the φ-OTDR system. This paper presents an innovative optical power attenuation compensation technique that utilizes the φ-OTDR system to address the challenge of signal attenuation in optical fibre. The proposed solution enhances the long-distance recognition ability of weak signals. To solve the attenuation issue, the polynomial fitting method is used. A comparison between the system's performance with and without a Raman amplifier is presented. To locate signals, mean square error and deviation from the average are utilized, while signal strength is determined by calculating the signal-to-noise ratio after fitting. This approach emphasizes precision in detecting relevant signals and optimizing system performance. The results show that the signal recognition ability of the φ-OTDR system improves significantly with the implementation of this compensation algorithm. © 2023 IEEE.

关键词： Optical fibers

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Numerical study on aero-optical imaging deviations of vehicles at different altitudes

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Optoelectronics Letters 2022年第2期18卷 97-102页

作者： XU Liang ZHANG Ziye WANG Tao WU Jianhui CHEN Xi Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems School of Electrical Engineering and AutomationTianjin University of TechnologyTianjin 300384China School of Intelligent Systems Engineering Sun Yat-sen UniversityGuangzhou 510006China China Academy of Launch Vehicle Technology Beijing 100076China

When the vehicle is flying in the atmosphere at high speed, the optical head and the atmosphere will have severe friction, thus forming a complex flow field, which makes the target image shift in the optical imaging system. The influence of altitude on aero-optical imaging deviation is studied in this paper. The geometric modeling and mesh generation of a typical blunt nosed high-speed vehicle were carried out, and the three-dimensional(3 D) flow field density was obtained by a large amount of computational fluid dynamic calculation. In order to complete the optical calculation, the backward ray tracing method and the backward ray tracing stop criterion were used. The results show that as the height increases, the imaging deviation decreases gradually, and the imaging deviation slope increases and tends to be flat and close to zero.

关键词： calculation deviation backward

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DH Detector: One-stage detection model with double-head detector and efficient convolution

DH Detector: One-stage detection model with double-head dete...

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IEEE International Conference on Mechatronics and Automation

作者： Ziyuan Feng Lei Sun School of Electrical Engineering and Automation Tianjin Key Laboratory for Control Theory and Complicated Industry Systems Tianjin University of Technology Tianjin China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

This article explores advanced techniques to build a network model, including the use of a double-head(DH) detector: one section of which is responsible for performing classification and the other for object prediction. This is followed by information stitching, which allows the model to learn more appropriate parameters. Subsequently, a CSP structure incorporating an attention mechanism is used to improve the feature extraction capabilities of the model. Finally, dynamic convolution is added to enhance the feature representation. Our model is trained from scratch on the COCO Dataset without taking a pre-trained model, the results of which are listed below. Based on 300 epochs of training, the mAP values for the four versions of DH Detector (s, m, l, x, the network model becomes larger in turn) are 40.8, 46.1, 48, and 49.8(100 epoch), respectively. The experiment results show that this method outperforms other competing methods in terms of both quantity and quality. In addition, the mAP of DH-s and DH-l reached 43.0 and 50.1 at an input image size of 960. A comparison of DH Detector with other algorithms is provided in Figure 1.

关键词： YOLO Training Solid modeling Attention mechanisms Convolution Computational modeling Detectors

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EBD-YOLO：a lightweight auxiliary driving detection algorithm based on YOLOv5

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Optoelectronics Letters 2025年

作者： SUN Lianshuai SHI Tao DING Yao LI Song Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems， School of Electrical Engineer-ing and Automation， Tianjin University of Technology College of Electrical Engineering， North China University of Science and Technology

A lightweight road-assistant detection algorithm， EBD-YOLO， based on YOLOv5s is proposed to address the problems of high model complexity， computation cost， and difficulty in deployment on resource-limited embedded terminals in existing assisted driving detection algorithms. First， lightweight Transformer model EfficientViT was used as the backbone feature extraction network of YOLOv5s model to reduce network parameters and calculation costs. Secondly， a Focal-GIoU Loss function is proposed for bounding box regression to accelerate model convergence and reduce loss. Thirdly， the feature pyramid structure is improved to a weighted bi-directional feature pyramid network (BiFPN) to enhance localization and semantic features. Then， a dynamic head framework is added to unify the attention mechanism with the object detection head to improve its performance. Finally， a Soft-CIoU＿NMS algorithm is proposed in the post-processing stage to enhance occluded targets' localization and detection ability and reduce the missed detection rate. We conducted experiments on the KITTI and BDD100K datasets for autonomous driving， and the results showed that the EBD-YOLO model reduced in size by 38.4% and 37.2%， respectively. In comparison， the computational cost was reduced by 48.1%. As measured by mAP@0.5， the detection accuracy improved by 0.5% and 5.8%， respectively， and mAP@0.5:0.95 improved by 2.8% and 7%， respectively. These improvements satisfied the requirements for deployment on embedded terminals in cars.

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Study on Decentralization of Spherical Amphibious Multi-robot control System Based on Smart Contract and Blockchain

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Journal of Bionic Engineering 2021年第6期18卷 1317-1330页

作者： Shuxiang Guo Sheng Cao Jian Guo Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of TechnologyBinshui Xidao Extension 391Tianjin300384China Intelligent Mechanical Systems Engineering Department Faculty of Engineering Kagawa UniversityTakamatsuKagawaJapan

With the development of intelligent bionic robots and the improvement of military application,a single robot cannot meet the requirements of the tasks of the current *** more complex tasks require not only that the robot be able to pass through the field barriers and the amphibious environment,but also that the robot be able to collaborate in a multi-robot ***,research on the multi-robot control system of spherical amphibious robots is very ***,the main research on amphibious robots is to improve the functions of a single robot,in the absence of the study of the multi-robot control *** systems primarily use a centralized control *** the transfer of central node can be achieved,there is still a problem of Byzantine fault tolerance in military applications,that is,when the amphibious multi-robot system is invaded by the *** central node may not only fail to accomplish the task,but also lose control of other robots,with severe *** solve the above problems,this paper proposed a decentralized method of spherical amphibious multi-robot control system based on blockchain ***,the point-to-point information network based on long range radio technology of low power wide area network was set up,we designed the blockchain system for embedded application environment and the decentralized hardware and software architecture of multi-robot control *** this basis,the consensus plugin,smart contract and decentralized multi-robot control algorithm were designed to achieve *** experimental results of consensus of spherical amphibious multi-robot showed the effectiveness of the decentralization.

关键词： Amphibious robot Blockchain Smart contract control system Decentralization

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Point-voxel dual transformer for LiDAR 3D object detection

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Optoelectronics Letters 2025年

作者： Tong Jigang Yang Fanhang Yang Sen Du Shengzhi Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot La-boratory， Tianjin University of Technology， 391 Binshui West Road Department of Electrical Engineering， Tshwane University of Technology

Deep learning for point clouds faces the challenge of their inherent unordered nature， which makes traditional CNN-like methods not directly applicable. However， due to the inherent permutation invariance， transformers provide solutions to unordered points problems faced in LiDAR-based object detection. In this paper， a two-stage LiDAR 3D object detection framework is presented， namely Point-Voxel Dual Transformer (PV-DT3D)， which is a transformer-based method. In the proposed PV-DT3D， point-voxel fusion features are used for proposal refinement. Specifically， in the PV-DT3D， keypoints are sampled from entire point cloud scene and used to encode representative scene features via a proposal-aware voxel set abstraction module. Subsequently， following the generation of proposals by the region proposal networks (RPN)， the internal encoded keypoints are fed into dual transformer encoder-decoder architecture. In 3D object detection， the proposed PV-DT3D is the first to take advantage of both pointwise transformer and channel-wise architecture to capture contextual information from the perspective of spatial and channel dimensions. Experiments conducted on the highly competitive KITTI 3D car detection leaderboard show that， the PV-DT3D achieves superior detection accuracy among state-of-the-art point-voxel-based methods.

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