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A Study of the Effect of the Miller Cycle on the Combustion of a Supercharged Marine Diesel Engine

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Energy engineering 2024年第5期121卷 1363-1380页

作者： Lingjie Zhao Cong Li mechanical and automotive engineering school Shanghai University of Engineering ScienceShanghai201600China

The Miller cycle is a program that effectively reduces NOx emissions from marine diesel engines by lowering the maximum combustion temperature in the cylinder,thereby reducing NOx emissions.To effectively investigate the impact of Miller cycle optimum combustion performance and emission capability under high load conditions,this study will perform a one-dimensional simulation of the performance of a marine diesel engine,as well as a threedimensional simulation of the combustion in the cylinder.A 6-cylinder four-stroke single-stage supercharged diesel engine is taken as the research object.The chassis dynamometer and other related equipment are used to build the test system,carry out the diesel engine bench test,and collect experimental data.The simulation results are compared with the test results,and the error is less than 5%.In this study,the authors will use simulation software to simulate several Miller cycle scenarios designed for early inlet valve closure and analyze the impact of the Miller cycle on combustion and emissions at 100%load conditions.By comparing the flow field distribution of the engine at 1500 r/min condition,it was found that proper EIVC can prolong the ignition latency period and homogeneous fuel-air mixture combustion acceleration,but it can reduce pressure and temperature within the piston chamber and NOx emission.However,the Miller cycle reduces end-of-compression temperatures,which increases combustion duration and exhaust temperatures,making it difficult to improve fuel economy at the optimum fuel consumption point,and closing the intake valves prematurely leads to excessive fuel expenditure.Furthermore,temperature and heat release rate within the piston chamber,NOx,and SOOT generation were significantly enhanced.

关键词： Miller cycle EIVC combustion NOx emissions marine diesel

On the electric behaviour of conductive grease inside the contact zone

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Friction 2024年第4期12卷 683-697页

作者： Yuxin ZHOU Jinjie LIU Xinming LI He CHONG Bo HAN Qinghua BAI SKF(Shanghai)automotive Technologies Co. Ltd.Shanghai 201814China school of mechanical and automotive engineering Qingdao University of TechnologyQingdao 266250China

Conductive grease has been considered as a potential solution in addressing electric erosion issue inside motor bearings.Understanding the conductive grease performance,especially the electric and tribological behaviour is crucial for its application.This paper combines bulk grease characterization and contact film study considering both electrical and tribological loading conditions.The results show that the electric performance for the selected conductive grease sample is electric field dependent,including both frequency and voltage amplitude.Its film impedance inside the contact area is closely related to the external electric field,running condition,and lubrication regime.The following film impedance calculation tells that not only bulk grease electric parameters,but the contact parameter,lubricant film contour and lubrication condition should be considered when performing the overall bearing electrical modelling.

关键词： Electric erosion lubricant conductivity grease film impedance

Revolution and challenges in machining processing aimed at carbon reduction

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Frontiers of mechanical engineering 2024年第1期19卷 1-3页

作者： Changhe LI school of mechanical and automotive engineering Qingdao University of TechnologyQingdao 266520China

The widespread use of cutting fluids during machining can effectively reduce machining temperatures,thereby solving the problem of part burns at the boundary of high thermal coupling.Cutting fluids have been extensively used in the manufacturing industry for hundreds of years;thus,the global annual consumption of cutting fluids exceeds 4 million tons.However,most of these cutting fluids are mineral oil-based emulsions,which are not environmentally friendly and renewable,which makes their use a huge challenge for sustainable manufacturing.

关键词： hundreds thereby machining

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

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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

Wearable multilead ECG sensing systems using on-skin stretchable and breathable dry adhesives

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Bio-Design and Manufacturing 2024年第2期7卷 167-180页

作者： Yingxi Xie Longsheng Lu Wentao Wang Huan Ma school of mechanical and automotive engineering South China University of TechnologyGuangzhou 510641China College of automotive and mechanical engineering Changsha University of Science and TechnologyChangsha 410114China Guangdong Cardiovascular Institute Guangdong Provincial People’s HospitalGuangzhou 510080China

Electrocardiogram(ECG)monitoring is used to diagnose cardiovascular diseases,for which wearable electronics have attracted much attention due to their lightweight,comfort,and long-term use.This study developed a wearablemultilead ECG sensing system with on-skin stretchable and conductive silver(Ag)-coated fiber/silicone(AgCF-S)dry adhesives.Tangential and normal adhesion to pigskin(0.43 and 0.20 N/cm2,respectively)was optimized by the active control of fiber density and mixing ratio,resulting in close contact in the electrode–skin interface.The breathableAgCF-S dry electrodewas nonallergenic after continuous fit for 24 h and can be reused/cleaned(>100 times)without loss of adhesion.The AgCF encapsulated inside silicone elastomers was overlapped to construct a dynamic network under repeated stretching(10%strain)and bending(90°)deformations,enabling small intrinsic impedance(0.3,0.1 Hz)and contact impedance variation(0.7 k)in high-frequency vibration(70 Hz).All hard/soft modules of the multilead ECG system were integrated into lightweight clothing and equipped with wireless transmission for signal visualization.By synchronous acquisition of I–III,aVR,aVL,aVF,and V4 lead data,the multilead ECG sensing system was suitable for various scenarios,such as exercise,rest,and sleep,with extremely high signal-to-noise ratios.

关键词： Multilead electrocardiogram Dry electrodes Wearable electronics Wireless transmission

Effect of Pre-strain on Microstructure and Stamping Performance of High-strength Low-alloy Steel

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Journal of Wuhan University of Technology(Materials Science) 2024年第3期39卷 774-780页

作者：刘坡 WEN Zhicheng LIU Zheng 许峰 school of mechanical engineering Guilin University of Aerospace TechnologyGuilin 541004China school of automotive Engineer-ing Changshu Institute of TechnologyChangshu 215500China

In this study,pre-strain ranging from 0 to 0.12 was applied through uniaxial tension on high-strength low-alloy(HSLA)specimens with four kinds of grain size.Effect of pre-strain and grain size on me-chanical property was investigated through tensile tests.Microstructures of the pre-strained and tensile tested samples were analyzed,respectively.The 30.8°v-bending and following flattening,as well as Erichson cupping tests,were performed on the pre-strained samples.Results show the elongation ratio of grain and dislocation density increases with pre-strain.Yielding platform is removed when pre-strain is larger than 0.06 while yielding plateau period decreases with pre-strain less than 0.06 due to reduction of pinning effect.The 30.8°v-bending and the following flattening tests are successfully accomplished on all the pre-strained samples with different grain size.Decrease in grain size,along with increase in pre-strain,causes increase in strength and decrease in elongation rate as well as cupping value.Pre-strain causes very slight effect on bending ability,much less than that on mechanical property and cupping test value.Reciprocal impact of the pre-strain and grain size on HSLA steel deformability is inconspicuous.

关键词： strain hardening dislocation texture bending erichson cupping test

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse Reinforcement Learning Theory

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engineering 2024年第2期33卷 133-145页

作者： Jian Wu Yang Yan Yulong Liu Yahui Liu school of mechanical and automotive engineering Liaocheng UniversityLiaocheng 252000China 2 school of Vehicle and Mobility Tsinghua UniversityBeijing 100084China

The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.

关键词： Obstacle avoidance trajectory planning Inverse reinforcement theory Anthropomorphic Adaptive driving scenarios

Generalized polynomial chaos expansion by reanalysis using static condensation based on substructuring

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 819-836页

作者： D.LEE S.CHANG J.LEE Department of automotive engineering Hanyang UniversitySeoul 04763Republic of Korea school of mechanical engineering Chungnam National UniversityDaejeon 34134Republic of Korea Department of mechanical Robotics and Energy EngineeringDongguk UniversitySeoul 04620Republic of Korea

This paper presents a new computational method for forward uncertainty quantification(UQ)analyses on large-scale structural systems in the presence of arbitrary and dependent random inputs.The method consists of a generalized polynomial chaos expansion(GPCE)for statistical moment and reliability analyses associated with the stochastic output and a static reanalysis method to generate the input-output data set.In the reanalysis,we employ substructuring for a structure to isolate its local regions that vary due to random inputs.This allows for avoiding repeated computations of invariant substructures while generating the input-output data set.Combining substructuring with static condensation further improves the computational efficiency of the reanalysis without losing accuracy.Consequently,the GPCE with the static reanalysis method can achieve significant computational saving,thus mitigating the curse of dimensionality to some degree for UQ under high-dimensional inputs.The numerical results obtained from a simple structure indicate that the proposed method for UQ produces accurate solutions more efficiently than the GPCE using full finite element analyses(FEAs).We also demonstrate the efficiency and scalability of the proposed method by executing UQ for a large-scale wing-box structure under ten-dimensional(all-dependent)random inputs.

关键词： forward uncertainty quantification(UQ) generalized polynomial chaos expansion(GPCE) static reanalysis method static condensation substructuring

Multi-Scale Design and Optimization of Composite Material Structure for Heavy-Duty Truck Protection Device

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Computer Modeling in engineering & Sciences 2024年第5期139卷 1961-1980页

作者： Yanhui Zhang Lianhua Ma Hailiang Su Jirong Qin Zhining Chen Kaibiao Deng school of mechanical and automotive engineering Guangxi University of Science and TechnologyLiuzhou545006China Commercial Vehicle Technology Center Dongfeng Liuzhou Automobile Co.Ltd.Liuzhou545005China school of mechanical and automotive engineering South China University of TechnologyGuangzhou510641China

In this paper,to present a lightweight-developed front underrun protection device(FUPD)for heavy-duty trucks,plain weave carbon fiber reinforced plastic(CFRP)is used instead of the original high-strength steel.First,the mechanical and structural properties of plain carbon fiber composite anti-collision beams are comparatively analyzed from a multi-scale perspective.For studying the design capability of carbon fiber composite materials,we investigate the effects of TC-33 carbon fiber diameter(D),fiber yarn width(W)and height(H),and fiber yarn density(N)on the front underrun protective beam of carbon fiber compositematerials.Based on the investigation,a material-structure matching strategy suitable for the front underrun protective beam of heavy-duty trucks is proposed.Next,the composite material structure is optimized by applying size optimization and stack sequence optimization methods to obtain the higher performance carbon fiber composite front underrun protection beam of commercial vehicles.The results show that the fiber yarn height(H)has the greatest influence on the protective beam,and theH1matching scheme for the front underrun protective beamwith a carbon fiber composite structure exhibits superior performance.The proposed method achieves a weight reduction of 55.21% while still meeting regulatory requirements,which demonstrates its remarkable weight reduction effect.

关键词： Structural optimization front underrun protection device carbon fiber reinforced plastic multi-scale model lightweight design