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ST-LaneNet: Lane Line Detection Method Based on Swin Transformer and LaneNet

Chinese Journal of Mechanical Engineering 2024年第1期37卷 130-145页

作者： Yufeng Du Rongyun Zhang Peicheng Shi Linfeng Zhao Bin Zhang Yaming Liu School of Mechanical Engineering Anhui Polytechnic UniversityWuhu 241000China automotive New technology Anhui Engineering and technology research center Anhui Polytechnic UniversityWuhu 241000China School of automotive and Transportation Engineering Hefei University of TechnologyHefei 230009China

The advancement of autonomous driving heavily relies on the ability to accurate lane lines detection.As deep learning and computer vision technologies evolve,a variety of deep learning-based methods for lane line detection have been proposed by researchers in the field.However,owing to the simple appearance of lane lines and the lack of distinctive features,it is easy for other objects with similar local appearances to interfere with the process of detecting lane lines.The precision of lane line detection is limited by the unpredictable quantity and diversity of lane lines.To address the aforementioned challenges,we propose a novel deep learning approach for lane line detection.This method leverages the Swin Transformer in conjunction with LaneNet(called ST-LaneNet).The experience results showed that the true positive detection rate can reach 97.53%for easy lanes and 96.83%for difficult lanes(such as scenes with severe occlusion and extreme lighting conditions),which can better accomplish the objective of detecting lane lines.In 1000 detection samples,the average detection accuracy can reach 97.83%,the average inference time per image can reach 17.8 ms,and the average number of frames per second can reach 64.8 Hz.The programming scripts and associated models for this project can be accessed openly at the following GitHub repository:https://***/Duane 711/Lane-line-detec tion-ST-LaneNet.

关键词： Autonomous driving Lane line detection Deep learning Swin transformer

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Functional Optical Fiber Sensors Detecting Imperceptible Physical/Chemical Changes for Smart Batteries

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Nano-Micro Letters 2024年第8期16卷 268-308页

作者： Yiding Li Li Wang Youzhi Song Wenwei Wang Cheng Lin Xiangming He Institute of Nuclear and New Energy technology Tsinghua UniversityBeijing 100084People’s Republic of China National Engineering research center of Electric Vehicles Beijing Institute of Technology(BIT)Beijing 100081People’s Republic of China Shenzhen automotive research Institute of BIT(Shenzhen research Institute of National Engineering research center of Electric Vehicles) Shenzhen 518118People’s Republic of China

The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist.Now the battery is still a“black box”,thus requiring a deep understanding of its internal state.The battery should“sense its internal physical/chemical conditions”,which puts strict requirements on embedded sensing parts.This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed,focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition,electrolyte degradation,electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution.The paper contributes to understanding how to use optical fiber sensors to achieve“real”and“embedded”monitoring.Through the inherent advantages of the advanced optical fiber sensor,it helps clarify the battery internal state and reaction mechanism,aiding in the establishment of more detailed models.These advancements can promote the development of smart batteries,with significant importance lying in essentially promoting the improvement of system consistency.Furthermore,with the help of smart batteries in the future,the importance of consistency can be weakened or even eliminated.The application of advanced optical fiber sensors helps comprehensively improve the battery quality,reliability,and life.

关键词： Smart battery Advanced embedded optical fiber sensor Battery internal physical/chemical state Quality-reliability-life characteristic

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Improving the high cycle fatigue property of Ti6Al4V ELI alloy by optimizing the surface integrity through electric pulse combined with ultrasonic surface rolling process

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Journal of Materials Science & technology 2024年第3期170卷 103-121页

作者： Pengfei Sun Shengguan Qu Chenfeng Duan Xiongfeng Hu Xiaoqiang Li National Engineering research center of Near-Net-Shape Forming for Metallic Materials South China University of TechnologyGuangzhou 510640China School of Mechanical and automotive Engineering South China University of TechnologyGuangzhou 510640China

To improve the surface integrity and high cycle fatigue property of Ti6Al4V ELI alloy,the electric pulse has been introduced into the ultrasonic surface rolling process(USRP),which is called electric pulse-assisted ultrasonic surface rolling process(EUSRP).With the help of“electroplasticity”of the electric pulse,the thickness of the surface gradient deformation layer was about three times of the USRP specimens by adjusting the pulse current level.However,the surface hardness decreases due to the continuous effect of the pulse current and the“skin effect”during treatment.It is worth noting that the higher the applied pulse current,the more severe the softening.This paradox causes the fatigue performance of EUSRP specimens lower than that of USRP specimens.To break this paradox,the EUSRP treatment is followed by a USRP treatment.The EUSRP-2(with a pulse current of 200 A)+USRP specimens exhibit excellent surface hardness,a gradient deformation layer thickness of about 400μm,low surface roughness and high compressive residual compressive stress.Besides,the hardening mechanisms of the different surface strengthening specimens have been quantitatively analyzed in combination with microstructure analysis.The fatigue life of Ti6Al4V ELI alloy can be improved by about 25 times at 780 MPa using the EUSRP-2+USRP treatment,the main reason for the highest fatigue life is the deepest surface gradient layer and the deepest crack initiation site.The fatigue limit of the EUSRP-2+USRP specimens is not the highest because too much surface hardening causes compressive residual stress relaxation during cycling and the beneficial effect of compressive residual stress is eliminated.

关键词： Ti6Al4V ELI alloy Combined surface treatment Transmission electron microscopy Residual stress Fatigue performance

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Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 294-317页

作者： Hongqing Chu Xiaoxiang Na Huan Liu Yuhai Wang Zhuo Yang Lin Zhang Hong Chen School of automotive Studies Tongji UniversityShanghaiChina Department of Engineering University of CambridgeCambridgeUK State Key Laboratory of automotive Simulation and Control Jilin UniversityChangchunChina Qingdao automotive research Institute Jilin UniversityQingdaoChina Dongfeng Commercial Vehicle technology center Dongfeng Motor CorporationWuhanChina

Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.

关键词： Heavy-duty truck Predictive cruise control Model predictive control Pontryagin’s maximum principle Real-truck implementation

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Recent advances and future prospects on Ni_(3)S_(2)-Based electrocatalysts for efficient alkaline water electrolysis

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Green Energy & Environment 2024年第4期9卷 659-683页

作者： Shiwen Wang Zhen Geng Songhu Bi Yuwei Wang Zijian Gao Liming Jin Cunman Zhang Clean Energy automotive Engineering center School of Automotive StudiesTongji UniversityShanghai201804China

Green hydrogen(H_(2))produced by renewable energy powered alkaline water electrolysis is a promising alternative to fossil fuels due to its high energy density with zero-carbon emissions.However,efficient and economic H_(2) production by alkaline water electrolysis is hindered by the sluggish hydrogen evolution reaction(HER)and oxygen evolution reaction(OER).Therefore,it is imperative to design and fabricate high-active and low-cost non-precious metal catalysts to improve the HER and OER performance,which affects the energy efficiency of alkaline water electrolysis.Ni_(3)S_(2) with the heazlewoodite structure is a potential electrocatalyst with near-metal conductivity due to the Ni–Ni metal network.Here,the review comprehensively presents the recent progress of Ni_(3)S_(2)-based electrocatalysts for alkaline water electrocatalysis.Herein,the HER and OER mechanisms,performance evaluation criteria,preparation methods,and strategies for performance improvement of Ni_(3)S_(2)-based electrocatalysts are discussed.The challenges and perspectives are also analyzed.

关键词： Alkaline water electrolysis Hydrogen Electrocatalysts Ni_(3)S_(2)

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Perception Enhanced Deep Deterministic Policy Gradient for Autonomous Driving in Complex Scenarios

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 557-576页

作者： Lyuchao Liao Hankun Xiao Pengqi Xing Zhenhua Gan Youpeng He Jiajun Wang Fujian Provincial Key Laboratory of automotive Electronics and Electric Drive Fujian University of TechnologyFuzhou350118China Fujian Provincial Universities Engineering research center for Intelligent Driving technology Fuzhou350118China

Autonomous driving has witnessed rapid advancement;however,ensuring safe and efficient driving in intricate scenarios remains a critical challenge.In particular,traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles,susceptibility to traffic flow bottlenecks,and imperfect data in perceiving environmental information,rendering them a vital issue in the practical application of autonomous driving.To address the traffic challenges,this work focused on complex roundabouts with multi-lane and proposed a Perception EnhancedDeepDeterministic Policy Gradient(PE-DDPG)for AutonomousDriving in the Roundabouts.Specifically,themodel incorporates an enhanced variational autoencoder featuring an integrated spatial attention mechanism alongside the Deep Deterministic Policy Gradient framework,enhancing the vehicle’s capability to comprehend complex roundabout environments and make decisions.Furthermore,the PE-DDPG model combines a dynamic path optimization strategy for roundabout scenarios,effectively mitigating traffic bottlenecks and augmenting throughput efficiency.Extensive experiments were conducted with the collaborative simulation platform of CARLA and SUMO,and the experimental results show that the proposed PE-DDPG outperforms the baseline methods in terms of the convergence capacity of the training process,the smoothness of driving and the traffic efficiency with diverse traffic flow patterns and penetration rates of autonomous vehicles(AVs).Generally,the proposed PE-DDPGmodel could be employed for autonomous driving in complex scenarios with imperfect data.

关键词： Autonomous driving traffic roundabouts deep deterministic policy gradient spatial attention mechanisms

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Microstructure and mechanical properties stability of pre-hardening treatment in Al-Cu alloys for pre-hardening forming process

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International Journal of Minerals,Metallurgy and Materials 2024年第3期31卷 539-551页

作者： Liping Tang Pengfei Wei Zhili Hu Qiu Pang Hubei Longzhong laboratory Xiangyang 441000China Hubei Key Laboratory of Advanced technology for automotive Components School of Automotive EngineeringWuhan University of TechnologyWuhan 430070China Hubei Engineering research center for Green&Precision Material Forming Wuhan University of TechnologyWuhan 430070China Key Laboratory of Metallurgical Equipment and Control technology of Ministry of Education School of Machinery and AutomationWuhan University of Science and TechnologyWuhan 430081China

The stability of the microstructure and mechanical properties of the pre-hardened sheets during the pre-hardening forming(PHF)process directly determines the quality of the formed components.The microstructure stability of the pre-hardened sheets was in-vestigated by differential scanning calorimetry(DSC),transmission electron microscopy(TEM),and small angle X-ray scattering(SAXS),while the mechanical properties and formability were analyzed through uniaxial tensile tests and formability tests.The results in-dicate that the mechanical properties of the pre-hardened alloys exhibited negligible changes after experiencing 1-month natural aging(NA).The deviations of ultimate tensile strength(UTS),yield strength(YS),and sheet formability(Erichsen value)are all less than 2%.Also,after different NA time(from 48 h to 1 month)is applied to alloys before pre-hardening treatment,the pre-hardened alloys possess stable microstructure and mechanical properties as well.Interestingly,with the extension of NA time before pre-hardening treatment from 48 h to 1 month,the contribution of NA to the pre-hardening treatment is limited.Only a yield strength increment of 20 MPa is achieved,with no loss in elongation.The limited enhancement is mainly attributed to the fact that only a limited number of clusters are transformed into Guinier-Preston(GP)zones at the early stage of pre-hardening treatment,and the formation ofθ''phase inhibits the nucleation and growth of GP zones as the precipitated phase evolves.

关键词： Al-Cu alloy pre-hardened alloy natural aging mechanical properties microstructure

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Lattice Boltzmann simulation study of anode degradation in solid oxide fuel cells during the initial aging process

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International Journal of Minerals,Metallurgy and Materials 2024年第2期31卷 405-411页

作者： Shixue Liu Zhijing Liu Shuxing Zhang Hao Wu Hydrogen Energy Industrial technology Innovation center China Nuclear Power Technology Research InstituteShenzhen 518031China Shenzhen Engineering research center for Hydrogen Safety Shenzhen 518031China

For present solid oxide fuel cells(SOFCs),rapid performance degradation is observed in the initial aging process,and the dis-cussion of the degradation mechanism necessitates quantitative analysis.Herein,focused ion beam-scanning electron microscopy was em-ployed to characterize and reconstruct the ceramic microstructures of SOFC anodes.The lattice Boltzmann method(LBM)simulation of multiphysical and electrochemical processes in the reconstructed models was performed.Two samples collected from industrial-size cells were characterized,including a reduced reference cell and a cell with an initial aging process.Statistical parameters of the reconstructed microstructures revealed a significant decrease in the active triple-phase boundary and Ni connectivity in the aged cell compared with the reference cell.The LBM simulation revealed that activity degradation is dominant compared with microstructural degradation during the initial aging process,and the electrochemical reactions spread to the support layer in the aged cell.The microstructural and activity de-gradations are attributed to Ni migration and coarsening.

关键词： solid oxide fuel cell anode degradation focused ion beam-scanning electron microscopy lattice Boltzmann method

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A Deep Learning-Enabled Skin-Inspired Pressure Sensor for Complicated Recognition Tasks with Ultralong Life

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research 2024年第1期2023卷 443-454页

作者： Yingxi Xie Xiaohua Wu Xiangbao Huang Qinghua Liang Shiping Deng Zeji Wu Yunpeng Yao Longsheng Lu School of Mechanical&automotive Engineering South China University of TechnologyGuangzhouChina

Flexible full-textile pressure sensor is able to integrate with clothing directly,which has drawn extensive attention from scholars recently.But the realization of flexible full-textile pressure sensor with high sensitivity,wide detection range,and long working life remains challenge.Complex recognition tasks necessitate intricate sensor arrays that require extensive data processing and are susceptible to damage.The human skin is capable of interpreting tactile signals,such as sliding,by encoding pressure changes and performing complex perceptual tasks.Inspired by the skin,we have developed a simple dip-and-dry approach to fabricate a full-textile pressure sensor with signal transmission layers,protective layers,and sensing layers.The sensor achieves high sensitivity(2.16 kPa^(−1)),ultrawide detection range(0 to 155.485 kPa),impressive mechanical stability of 1 million loading/unloading cycles without fatigue,and low material cost.The signal transmission layers that collect local signals enable real-world complicated task recognition through one single sensor.We developed an artificial Internet of Things system utilizing a single sensor,which successfully achieved high accuracy in 4 tasks,including handwriting digit recognition and human activity recognition.The results demonstrate that skin-inspired full-textile sensor paves a promising route toward the development of electronic textiles with important potential in real-world applications,including human–machine interaction and human activity detection.

关键词： Deep Skin utilizing

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Influence of syngas components and ash particles on the radiative heat transfer in a radiant syngas cooler

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Chinese Journal of Chemical Engineering 2024年第4期68卷 203-215页

作者： Chen Han Youmin Situ Huaxing Zhu Jianliang Xu Zhenghua Dai Guangsuo Yu Haifeng Liu National Energy Coal Gasification technology research and Development center East China University of Science and TechnologyShanghai 200237China Shanghai Engineering research center of Coal Gasification East China University of Science and TechnologyShanghai 200237China

Radiant syngas cooler(RSC)is widely used as a waste heat recovery equipment in industrial gasification.In this work,an RSC with radiation screens is established and the impact of gaseous radiative property models,gas components,and ash particles on heat transfer is investigated by the numerical simulation method.Considering the syngas components and the pressure environment of the RSC,a modified weighted-sum-of-gray-gases model was developed.The modified model shows high accuracy in validation.In computational fluid dynamics simulation,the calculated steam production is only 0.63%in error with the industrial data.Compared with Smith's model,the temperature decay along the axial direction calculated by the modified model is faster.Syngas components are of great significance to heat recovery capacity,especially when the absorbing gas fraction is less than 10%.After considering the influence of particles,the outlet temperature and the proportion of radiative heat transfer are less affected,but the difference in steam output reaches 2.7 t·h^(-1).The particle deposition on the wall greatly reduces the heat recovery performance of an RSC.

关键词： Radiant syngas cooler Weighted-sum-of-gray-gases model Numerical simulation Particle radiation

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