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23rd European Microelectronics and Packaging Conference and Exhibition, EMPC 2021

作者： Yu, Chen Yang, Fei Liu, Johan Zhang, Yong SMIT Centre School of Mechatronics Engineering and Automation Shanghai University Shanghai China Electronics Materials and Systems Laboratory Department of Microtechnology and Nanoscience Chalmers University of Technology GothenburgSE-41296 Sweden

ISBN: (纸本)9780956808677

In recent years, laser-reduced graphene oxide (LRGO) has received widespread interest, however, the thermal properties of graphene films obtained by laser reduction of GO are rarely reported. In this paper, a pulsed laser was used to reduce the prepared GO films. The obtained LRGO films were characterized by scanning electron microscopy (SEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS). The thermal diffusivity of the LRGO was measured as 7.3 mm2/s, higher than that of GO measured as 5.9 mm2/s. The heating performance of LRGO was performed under different DC voltages and the results show that the temperature can reach up to 91 ℃ with a response time of 14 s under the voltage of 18 V. The excellent electrothermal performance of LRGO films indicate that the LRGO films are promising as heating elements for various application such as defoggers. © 2021 2021 23rd European Microelectronics and Packaging Conference and Exhibition, EMPC 2021. All rights reserved.

关键词： Thermodynamic properties

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Thermal Properties of Laser-induced Graphene Films Photothermally Scribed on Bare Polyimide Substrates 23

Thermal Properties of Laser-induced Graphene Films Photother...

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23rd European Microelectronics and Packaging Conference and Exhibition, EMPC 2021

作者： Yang, Fei Yu, Chen Liu, Johan Zhang, Yong SMIT Centre School of Mechatronics Engineering and Automation Shanghai University Shanghai201800 China Electronics Materials and Systems Laboratory Department of Microtechnology and Nanoscience Chalmers University of Technology GothenburgSE-41296 Sweden

ISBN: (纸本)9780956808677

In this work, laser-induced graphene (LIG)/polyimide (PI) films with good thermal properties were prepared by directly inducing graphene on the bare PI substrates by a computer numerical control (CNC) laser engraving machine. The obtained samples were characterized by scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy. The results showed that the laser energy density has a significant impact on the microstructures of the samples. Moreover, the thermal diffusivity of LIG/PI was increased from 0.5 mm2/s to 1.6 mm2/s, which is 3 times higher than bare PI. Finally, the electrothermal properties of the LIG films were investigated and the results showed that under a 12 V power supply, the equilibrium temperature of LIG films increases from 45℃ to 74℃ with the increase of laser energy density from 1.8 J/mm2 to 2.4 J/mm2. Our results indicate that this time-saving, low-cost, and environment-friendly method is promising for fabricating excellent graphene-based materials. © 2021 2021 23rd European Microelectronics and Packaging Conference and Exhibition, EMPC 2021. All rights reserved.

关键词： Polyimides

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Thermal Analysis of an Au/Pt/Ti-Based Microheater 23

Thermal Analysis of an Au/Pt/Ti-Based Microheater

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23rd European Microelectronics and Packaging Conference and Exhibition, EMPC 2021

作者： Zhang, Yong Yu, Chen Yang, Fei Liu, Johan SMIT Center School of Mechatronics Engineering and Automation Shanghai University Shanghai201800 China Electronics Materials and Systems Laboratory Department of Microtechnology and Nanoscience Chalmers University of Technology GothenburgSE-41296 Sweden

ISBN: (纸本)9780956808677

A thin film Gold/Platinum/Titanium (Au/Pt/Ti) - based microheater with pectination construction and a four-point probe was fabricated on a silica substrate. A standard lithography process was used to transfer the circuit pattern onto the substrate, and then Au/Pt/Ti was deposited on the substrate by an evaporator. Standard calibration was carried out at various temperatures, which can be obtained the relationship between the temperature and the resistance of the microheater, the results show that the Au/Pt/Ti-based microheater has a good linear relationship between the temperature and the resistance, indicating the microheater can also be used as a temperature sensor. Furthermore, the effects of different input powers, the geometry, and the thickness of the thin-film metals of the microheater were investigated and discussed. Finally, a finite element model was set up to see the temperature distribution of the microheater after the electric potential is applied. © 2021 2021 23rd European Microelectronics and Packaging Conference and Exhibition, EMPC 2021. All rights reserved.

关键词： Calibration

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Adaptive Neural Network Output Feedback Control of Auvs Using Integral Reinforcement Learning

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SSRN 2022年

作者： Li, Zhifu Wang, Ming Chen, Yang Quan Ma, Ge Zou, Tao School of Mechanical and Electrical Engineering Guangzhou University Guangzhou510006 China Mechatronics Embedded Systems and Automation Laboratory University of Colifornia MercedCA95343 United States

In this paper, an adaptive model-parameter-free integral reinforcement learning (RL) neural network (NN) control scheme is proposed for the trajectory tracking control of an autonomous underwater vehicle (AUV) with unmeasurable velocity vector and input saturation constraint. The proposed scheme consists of three NNs: actor, critic and observer, which are used to compensate for unknown dynamics, approximate long-term performance metrics and unmeasurable velocity vectors, respectively. To deal with the input saturation, an auxiliary variable system is utilized in the control law. Then, to solve the model-dependent problem, an adaptive law is designed to estimate the unknown model parameters. Furthermore, to solve the problem of slow response caused by unknown model parameters and input constraints, a multi-gradient direction (MGD) RL method is proposed, which uses the historical gradient update direction to fine-tune the overall update direction. The strict Lyapunov analysis guarantees that all signals of the system are SGUUB. Finally, the superiority of the proposed method is verified by comparative experiments. © 2022, The Authors. All rights reserved.

关键词： Autonomous underwater vehicles

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Adaptive Energy Management Strategy to Avoid Battery Temperature Peaks in Fuel Cell Electric Trucks

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IFAC-PapersOnLine 2022年第24期55卷 311-316页

作者： Alessandro Ferrara Matthias Hütter Christoph Hametner Institute of Mechanics and Mechatronics Division of Process Control and Automation TU Wien Vienna Austria AVL List GmbH Graz Austria Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems TU Wien Vienna Austria

Thermal management is essential in electric vehicles to preserve battery life. In particular, avoiding temperature peaks is critical to prevent accelerated degradation. The battery thermal management problem is crucial in fuel cell electric trucks due to the heavy vehicle weight, especially on mountain or hilly roads. Therefore, this paper proposes an energy management strategy that reduces battery degradation by limiting its usage at high temperatures to allow its cooldown and avoid peaks. The energy management strategy is adaptive because the main control parameters for the fuel cell/battery power-split are adjusted depending on the battery temperature. The comparison between adaptive and non-adaptive strategies proves the effectiveness of the proposed formulation in avoiding temperature peaks without hindering fuel consumption or fuel cell degradation. The robustness of the proposed energy management strategy is validated with simulations of several real-world driving cycles with various speed and elevation profiles.

关键词： Energy Management Heavy-Duty Fuel Cell Vehicle Adaptive Control Battery Temperature Fuel Cell Degradation Battery Thermal Management

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The Joint-Space Reconstruction of Human Fingers by using a Highly Under-Actuated Exoskeleton

The Joint-Space Reconstruction of Human Fingers by using a H...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Yuan Su Gaofeng Li Yongsheng Deng Ioannis Sarakoglou Nikos G. Tsagarakis Jiming Chen College of Control Science and Engineering Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province School of Mechanical Engineering and Automation Northeastern University Shenyang China Humanoids and Human Centered Mechatronics Research Line Istituto Italiano Di Technologia Genova Italy

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Hand motion tracking is essential in many fields, e.g., immersive virtual reality, teleoperation of robotic hand, and hand rehabilitation of stroke patient, as human hand plays a crucial role in our daily life. The highly under-actuated hand exoskeleton, which can track the 6-DoF motions of each fingertip via a highly under-actuated kinematic chain, exhibits many benefits in wearability and portability over other solutions. However, due to the non-anthropomorphic linkage, this hand exoskeleton also encounters difficulties in measuring human-finger’s joint angles. While the joint-space is important in many scenarios, such as teleoperating a robotic hand with anthropomorphic kinematics but with different size to human. Here we proposed a new method to reconstruct the human finger joints by using a highly under-actuated hand exoskeleton. Our key contribution is the arc-fitting algorithm, which is able to calibrate the misalignment between the exoskeleton’s and the human-finger’s base frames and estimate the length of human’s phalanxes, by using the fingertip’s circular motions. With knowing the aforementioned informations, the joint angles can be reconstructed in high precision based on the inverse kinematics models of human fingers. Furthermore, our proposed method is compared with a baseline method, in which the joint angles obtained by a motion capture system are served as ground-truth. The results demonstrate that our proposed method exhibits excellent performance in reconstructing finger’s joint configurations.

关键词： Couplings Tracking Exoskeletons Thumb Virtual reality Stroke (medical condition) Motion capture

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Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1752-1762页

作者： Xianglei Zhu Wen Hu Zejian Deng Jinwei Zhang Fengqing Hu Rui Zhou Keqiu Li Fei-Yue Wang the College of Intelligence and Computing Tianjin UniversityTianjin 300350 the China Automotive Technology and Research Center Co.Ltd. Tianjin 300300China the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China the Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L3G1Canada the School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China the Macao University of Science and Technology MacaoChina the Waytous Inc. Qingdao 266000China IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Accurately predicting the trajectories of surrounding vehicles and assessing the collision risks are essential to avoid side and rear-end collisions caused by *** improve the safety of autonomous vehicles in the mixed traffic,this study proposes a cut-in prediction and risk assessment method with considering the interactions of multiple traffic *** integration of the support vector machine and Gaussian mixture model(SVM-GMM)is developed to simultaneously predict cut-in behavior and *** dimension of the input features is reduced through Chebyshev fitting to improve the training efficiency as well as the online inference *** on the predicted trajectory of the cut-in vehicle and the responsive actions of the autonomous vehicles,two risk measurements are introduced to formulate the comprehensive interaction risk through the combination of Sigmoid function and Softmax ***,the comparative analysis is performed to validate the proposed method using the naturalistic driving *** results show that the proposed method can predict the trajectory with higher precision and effectively evaluate the risk level of a cut-in maneuver compared to the methods without considering interaction.

关键词： Cut-in behavior interaction-aware mixed traffic risk assessment trajectory prediction

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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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Eco-driving of fuel cell electric trucks: optimal speed planning combining dynamic programming and Pontryagin’s minimum principle

Eco-driving of fuel cell electric trucks: optimal speed plan...

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IEEE Conference on Vehicular Technology (VTC)

作者： Alessandro Ferrara Christoph Hametner Division of Process Control and Automation TU Wien Institute of Mechanics and Mechatronics Vienna Austria Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems TU Wien Vienna Austria

ISBN: (纸本)9781665454698

Eco-driving is an energy-aware driving style that improves the overall vehicle efficiency to reduce operating costs and extend the driving range. This paper focuses on the eco-driving of fuel cell electric trucks, optimizing the speed plan based on the route elevation, and studying the trade-off between driving time and range. In particular, the optimal speed plan is created by combining two methods from optimal control theory (dynamic programming and Pontryagin’s minimum principle) to include an energy management strategy for fuel consumption optimization. The speed plan created with the proposed method increases the vehicle range by 8% compared with a constant speed plan. Moreover, the study shows that the vehicle range can be extended up to 50% if the driving time is increased, which might be an essential solution to cope with the undeveloped hydrogen refueling infrastructure. The conclusion of this work indicates several directions to continue the research on the topic: for example, addressing robustness to traffic conditions and including component degradation mitigation targets in the optimization (e.g. SoC operating range and fuel cell voltage degradation).

关键词： Degradation Vehicular and wireless technologies Hydrogen Fuel cells Voltage Robustness Planning

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An Erasmus+ project: Interactive Course for Control Theory (ICCT) 8

An Erasmus+ project: Interactive Course for Control Theory (...

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47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021

作者： Podrzaj, Primoz Finzgar, Miha Pirnar, Zan Ljubic, Sandi Lanzetta, Michele Pollini, Lorenzo Venturini, Pietro Pizag, Bertalan Urbin, Agnes Korondi, Peter Graff, Jozsef Budai, Csaba University of Ljubljana Laboratory for Mechatronics Production Systems and Automation Faculty of Mechanical Engineering Ljubljana Slovenia University of Rijeka Faculty of Engineering Department of Computer Engineering Rijeka Croatia University of Pisa Department of Industrial Engineering Department of Information Engineering Pisa Italy Budapest University of Technology and Economics Faculty of Mechanical Engineering Department of Mechatronics Optics and Mechanical Engineering Informatics Budapest Hungary

ISBN: (纸本)9781665435543

The paper presents an overview and the main results of the Erasmus+ project titled Interactive Course for Control Theory-ICCT. The project was started by four European Universities when they identified by a survey that students find Control Theory more challenging to understand compared to other subjects. The project's main goal was to develop a platform, which would offer examples from the field of Control Theory in an interactive way-ICCT. Frequently asked questions (FAQ) and test exam questions were added as well. To support the course, an accompanying textbook was prepared. At this point, the course and the accompanying textbook are available in English and the languages of the partner universities;since both of them are publicly available, we assume they will be offered in other languages in future. The benefits of implementing our interactive course are already visible in better survey results and improved grades in Control Theory-related subjects. © 2021 IEEE.

关键词： Python

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