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arXiv 2021年

作者： Xu, Nan Tang, Zepeng Askari, Hassan Zhou, Jianfeng Khajepour, Amir The State Key Laboratory of Automotive Simulation and Control Jilin University Changchun Jilin130025 China The Department of Mechanical and Mechatronics Engineering University of Waterloo ONN2L3G1 Canada

Accurate estimation of the tire slip ratio is critical for vehicle safety, as it is necessary for vehicle control purposes. In this paper, an intelligent tire system is presented to develop a novel slip ratio estimation model using machine learning algorithms. The accelerations, generated by a triaxial accelerometer installed onto the inner liner of the tire, are varied when the tire rotates to update the contact patch. Meanwhile, the slip ratio reference value can be measured by the MTS Flat-Trac tire test platform. Then, by analyzing the variation between the accelerations and slip ratio, highly useful features are discovered, which are especially promising for assessing vertical acceleration. For these features, machine learning (ML) algorithms are trained to build the slip ratio estimation model, in which the ML algorithms include artificial neural networks (ANNs), gradient boosting machines (GBMs), random forests (RFs), and support vector machines (SVMs). Finally, the estimated NRMS errors are evaluated using 10-fold cross-validation (CV). The proposed estimation model is able to estimate the slip ratio continuously and stably using only the acceleration from the intelligent tire system, and the estimated slip ratio range can reach 30%. The estimation results have high robustness to vehicle velocity and load, where the best NRMS errors can reach 4.88%. In summary, the present study with the fusion of an intelligent tire system and machine learning paves the way for the accurate estimation of the tire slip ratio under different driving conditions, which create new opportunities for autonomous vehicles, intelligent tires, and tire slip ratio estimation. Copyright © 2021, The Authors. All rights reserved.

关键词： Tires

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A Bio-Tribocorrosion Comparison between Additively Manufactured and Forged Ti6al4v Parts

SSRN

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SSRN 2023年

作者： Matin, Sina Toorandaz, Sahar Nikpour, Saman Abdolvand, Hamidreza Toyserkani, Ehsan Hedberg, Yolanda S. Department of Chemistry Western University LondonONN6A 5B7 Canada Multi-Scale Additive Manufacturing Lab Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Mechanical and Materials Engineering Western University LondonONN6A 5B7 Canada Surface Science Western Western University LondonONN6G 0J3 Canada

Ti6Al4V has been used widely as a biomedical alloy and is increasingly manufactured by additive manufacturing due to customized shapes. As implant material, it is frequently exposed to both friction and corrosive environments. This study investigates the effect of the fabrication process (laser powder bed fusion and forging) on the tribocorrosion behavior of Ti6Al4V in various environments including diluted hydrochloric acid to simulate the acidic environment in a crevice (HCl), phosphate-buffered saline (pH 7.3) with 10 g/L bovine serum albumin (PBS+BSA), and PBS+BSA with 30 mM H2O2. While the presence of BSA hindered the repassivation (reforming of the protective passive surface oxide), the presence of H2O2 accelerated it. HCl resulted in a localized tribocorrosion process with pits. The highest plastic deformation rate was found in the PBS+BSA solution followed by HCl and PBS+BSA+H2O2. In addition, AM parts presented a higher microhardness and smaller grain sizes compared to forged materials. There was no influence of the manufacturing process on the coefficient of friction (COF) in HCl and PBS+BSA solutions, however, a significantly higher COF was found for forged samples in PBS+BSA+H2O2 than AM samples. In all, AM was beneficial to the tribocorrosion behavior of Ti6Al4V. © 2023, The Authors. All rights reserved.

关键词： Tribology

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Laser powder bed fusion of difficult-to-print γ′ Ni-based superalloys: A review of processing approaches, properties, and remaining challenges

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Additive Manufacturing 2025年 106卷

作者： Enrique, Pablo D. Minasyan, Tatevik Toyserkani, Ehsan Multi-Scale Additive Manufacturing Lab Department of Mechanical and Mechatronics Engineering University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada

Metal additive manufacturing (AM) promises a revolution with the potential to fabricate more complex, lighter, and higher performance components while simplifying supply chains and reducing material waste. However, many of the superalloys that are critical to applications requiring superior high-temperature properties are also challenging to process using fusion-based AM. The number of publications on this topic has grown significantly in the past five years, reflecting a growing interest within industry and academia. This article reviews and discusses the challenges associated with powder bed fusion - laser beam (PBF-LB) of γ′ Ni-based superalloys and recent approaches that have enabled their processing. This includes process parameter optimization, alloy modification, and heat treatment, all of which have been shown to produce material with reduced defect density. Additionally, the properties of γ′ Ni-based superalloys made with PBF-LB and conventional (cast and wrought) processes are compared and the reasons for the observed differences are discussed. Current and future research trends are provided based on the current outstanding challenges and prevailing theories in the literature, as well as an outlook on the adoption of PBF-LB γ′ Ni-based superalloys in industry. © 2025 The Authors

关键词： Superalloys

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A Novel Integrated Stability control Based on Differential Braking and Active Steering for Four-axle Trucks

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Chinese Journal of mechanical engineering 2019年第1期32卷 174-194页

作者： Buyang Zhang Changfu Zong Guoying Chen Yanjun Huang Ting Xu College of Automotive Engineering Jilin University Changchun 130022 China State Key Laboratory of Automotive Simulation and Control Jilin University Changchun 130022 China College of Mechanical and Mechatronics Engineering University of Waterloo ON N2L 3G1 Canada

Di erential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one control method to improve the other. Moreover, many experiments are needed to improve the robustness; therefore, these control methods are underutilized. This paper proposes an integrated control system specially designed for multi-axle vehicles, in which the desired lateral force and yaw moment of vehicles are determined by the sliding mode control algorithm. The output of the sliding mode control is distributed to the suitable wheels based on the abilities and potentials of the two control methods. Moreover, in this method, fewer experiments are needed, and the robustness and simultaneity are both guaranteed. To simplify the optimization system and to improve the computation speed, seven simple optimization subsystems are designed for the determination of control outputs on each wheel. The simulation results show that the proposed controller obviously enhances the stability of multi-axle trucks. The system improves 68% of the safe velocity, and its performance is much better than both di erential braking and active steering. This research proposes an integrated control system that can simultaneously invoke di erential braking and active steering of multi-axle vehicles to fully utilize the abilities and potentials of the two control methods.

关键词： Di erential braking Active steering Vertical tire force calculation Multi-axle truck Integrated control

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Cross-Subject EEG Linear Domain Adaption Based on Batch Normalization and Depthwise Convolutional Neural Network

SSRN

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SSRN 2023年

作者： Li, Guofa Ouyang, Delin Yang, Liu Li, Qingkun Tian, Kai Wu, Baiheng Guo, Gang College of Mechanical and Vehicle Engineering Chongqing University Chongqing400044 China Institute of Human Factors and Ergonomics College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan430063 China State Key Laboratory of Automotive Safety and Energy School of Vehicle and Mobility Tsinghua University Beijing100084 China Institute for Transport Studies University of Leeds LeedsLS1 9JT United Kingdom Department of ICT and Natural Science Norwegian University of Science and Technology Ålesund6009 Norway

Electroencephalogram (EEG)-based emotion recognition has been widely used in affective computing. However, the study on improving recognition accuracy across individuals is insufficient. In this study, a new linear domain adaption approach with experiment-level batch normalization and single-layer depthwise convolutional neural network is proposed. In particular, the experiment-level batch normalization and depthwise convolutional neural network can be integrated as a linear mapping with a scaling parameter and a translation parameter. By linear mapping, difference between subjects in different domain can be effectively diminished, and the mapping parameters can be used to further investigate EEG emotion mechanism. The domain adaption experiments are conducted with SJTU emotion EEG dataset and SJTU emotion EEG dataset-IV, which are divided into source domain and target domain to validate the recognition effect across individuals. Multiple traditional machine learning and deep learning classifiers are used to examine the effectiveness of our proposed approach. By mapping the EEG data from source domain to target domain, the increment of recognition accuracy is up to 61.11% when using the support vector machine classifier. The highest recognition accuracy 97.22% is achieved when using the logistic regression classifier. The scaling and translation parameters in the mapping procedure are then analyzed with statistical methods. It is found that EEG signal waves in the same emotion category are highly similar and EEG data have characteristics including integration of channels and hierarchy of frequency bands. In addition, our results indicate that emotion complexity and emotion sensitiveness of brain cortex regions can affect the correlations between channels. © 2023, The Authors. All rights reserved.

关键词： Emotion Recognition

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Parallel Distance: A New Paradigm of Measurement for Parallel Driving

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1169-1178页

作者： Teng Liu Hong Wang Bin Tian Yunfeng Ai Long Chen the Vehicle Intelligence Pioneers Inc. Qingdao 266109 the Department of Automotive Engineering Chongqing UniversityChongqing 400044China the Mechanical and Mechatronics Engineering Department Waterloo UniversityN2L 3G1Canada the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the School of Data and Computer Science Sun Yat-sen UniversityGuangzhou 510006China

In this paper, a new paradigm named parallel distance is presented to measure the data information in parallel driving system. As an example, the core variables in the parallel driving system are measured and evaluated in the parallel distance framework. First, the parallel driving 3.0 system included control and management platform, intelligent vehicle platform and remote-control platform is introduced. Then,Markov chain(MC) is utilized to model the transition probability matrix of control commands in these systems. Furthermore, to distinguish the control variables in artificial and physical driving conditions, different distance calculation methods are enumerated to specify the differences between the virtual and real signals. By doing this, the real system can be guided and the virtual system can be im-proved. Finally, simulation results exhibit the merits and multiple applications of the proposed parallel distance framework.

关键词： Artificial and physical system parallel distance parallel driving 3.0 parallel system rotational and accelerator signal

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Interaction-Aware Cut-in Behavior Prediction and Risk Assessment for Autonomous Driving

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IFAC-PapersOnLine 2020年第5期53卷 656-663页

作者： Jinwei Zhang Guofa Li Zejian Deng Huilong Yu Jan P. Huissoon Dongpu Cao Waterloo Cog Drive Lab Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON N2L 3G1 Canada

Cut-in behavior commonly occurs in both urban and highway driving. Rear-end collisions happen when the lag vehicles cannot predict this abnormal lane change behavior of the front vehicles and response in time. However, related studies on cut-in event prediction and risk assessment have rarely been presented in autonomous driving field. A phase-based design framework is proposed in this work to realize online prediction and risk estimation of the cut-in behavior considering interactions between the involved vehicles. After preprocessing and analyzing a naturalistic driving dataset, a cut-in behavior predictor and a risk estimator are devised based on Gaussian mixture model. Comparing with baseline approaches, both the predictor and estimator designed following the proposed framework achieve enhanced results, which can further improve the driving safety of autonomous vehicles when cut-in behavior occurs.

关键词： Autonomous vehicles Prediction methods Risk Driver behavior Interactive approaches

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A Nonlinear Model Predictive control Strategy for Water Sampling Using a UAV with a Slung Mechanism

A Nonlinear Model Predictive Control Strategy for Water Samp...

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Mediterranean Conference on control and Automation (MED)

作者： Fotis Panetsos George C. Karras Kostas J. Kyriakopoulos Odysseas Oikonomides Panayiotis Kolios Demetrios G. Eliades Christos Panayiotou Control Systems Lab School of Mechanical Engineering National Technical University of Athens 9 Heroon Polytechniou Str. Zografou Athens Greece Dept. of Informatics and Telecommunications University of Thessaly 3rd Km Old National Road Lamia-Athens Lamia Greece KIOS Research and Innovation Center of Excellence University of Cyprus 1 University Avenue Cyprus

In this work, a nonlinear Model Predictive control (NMPC) strategy is presented for stabilizing an Unmanned Aerial Vehicle (UAV) with a cable-suspended liquid collection device during water sampling from aquatic environments. Building upon our previous work, an NMPC scheme is developed which incorporates the disturbances acting on the multirotor and attains the accurate hovering of the vehicle while simultaneously state and input constraints are satisfied. Once the UAV is stabilized above the water surface, a custom electromechanical mechanism is activated to collect water samples. The performance of the proposed controller and the reliability of the sampling device are demonstrated through real-world experiments in a river with high water flow.

关键词：

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mechanical behavior of CuZrAl metallic glass scaffolds fabricated by selective laser melting

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Materials Letters 2023年 341卷

作者： Wu, Ming-Wei Ni, Kai Lei, Yang Xiong, Xin-Xing Chuang, Yi-Ting Lin, Quiao-En Wang, Pei Ramasamy, Parthiban Eckert, Jürgen Department of Materials and Mineral Resources Engineering National Taipei University of Technology No. 1 Sec. 3 Zhong-Xiao E. Rd. Taipei10608 Taiwan Additive Manufacturing Institute College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China Henan Key Laboratory of High Performance Carbon Fiber Reinforced Composites Carbon Matrix Composites Research Institute Henan Academy of Sciences Zhengzhou450046 China Erich Schmid Institute of Materials Science Austrian Academy of Sciences Jahnstraße 12 LeobenA-8700 Austria Department of Mechanical Engineering University of Dunaujvaros Tancsics M. u. 1/A DunaujvarosH-2400 Hungary Department of Materials Science Chair of Materials Physics Montanuniversität Leoben Jahnstraße 12 LeobenA-8700 Austria

Selective laser melting (SLM) was used to manufacture the CuZrAl metallic glass (MG) scaffolds containing body-centered cubic and face-centered cubic combined lattices (F2BCC) with straight and curved struts, and the effects of the lattice structures on the mechanical behavior were examined. The findings show that the curved struts significantly improve the compressive ductility by 122 % and the energy absorption by 106 %. The curved struts can effectively prevent catastrophic shear fracture and delay the fracture – mainly due to the relief of strain concentrations. The results from this work prove that it is possible to effectively improve the ductility and toughness of SLM MG components by designing a suitable lattice structure. © 2023 Elsevier B.V.

关键词： Metallic glass

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Modeling and analysis of mixed traffic networks with human-driven and autonomous vehicles

Research Square

引用

Research Square 2021年

作者： Xu, Qing Chen, Chaoyi Chang, Xueyang Cao, Dongpu Cai, Mengchi Wang, Jiawei Li, Keqiang Wang, Jianqiang School of Vehicle and Mobility Tsinghua University China Tsingcloud Co. Lmt. China CogDrive lab Department of Mechanical and Mechatronics Engineering University of Waterloo ONN2L 3G1 Canada

The emergence of connected and automated vehicles (CAV) indicates improved traffic mobility in future traffic transportation systems. This study addresses the research gap in macroscopic traffic modeling of mixed traffic networks where CAV and human-driven vehicles coexist. CAV behavior is explicitly included in the proposed traffic network model, and the vehicle number non-conservation problem is overcome by describing the approaching and departure vehicle number in discrete time. The proposed model is verified in typical CAV cooperation scenarios. The performance of CAV coordination is analyzed in road, intersection and network scenario. Total travel time of the vehicles in the network is proved to be reduced when coordination are applied. Simulation results validate the accuracy of the proposed model and the effectiveness of the proposed algorithm. © 2021, CC BY.

关键词： Travel time

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