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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 *** cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road *** this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty *** 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 *** 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 *** programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed ***,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed *** results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing ***,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

Trench gate GaN IGBT with controlled hole injection efficiency

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The Journal of China Universities of Posts and Telecommunications 2024年第2期31卷 10-16页

作者： Huang Yi Li Yueyue Gao Sheng Wang Qi liu Bin Han Genquan School of Optoelectronic Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China School of Electronic Science and Engineering Nanjing UniversityNanjing 210008China School of Microelectronics Xidian UniversityXi’an 710126China

In this paper,a novel trench gate gallium nitride(GaN)insulated gate bipolar transistor(GaN IGBT),in which the collector is divided into multiple regions to control the hole injection efficiency,is designed and theoretically *** incorporation of a P+/P-multi-region alternating structure in the collector region mitigates hole injection within the collector *** the device is in forward conduction,the conductivity modulation effect results in a reduced storage of carriers in the drift *** a result,the number of carriers requiring extraction during device turn-off is minimized,leading to a faster turn-off *** results illustrate that the GaN IGBT with controlled hole injection efficiency(CEH GaN IGBT)exhibits markedly enhanced performance compared to conventional GaN IGBT,showing a remarkable 42.2%reduction in turn-off time and a notable 28.5%decrease in turn-off loss.

关键词： gallium nitride insulated gate bipolar transistor(GaN IGBT) hole injection trench gate turn-off loss

Improved deep residual shrinkage network for a multi-cylinder heavy-duty engine fault detection with single channel surface vibration

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Energy and AI 2024年第2期16卷 277-288页

作者： Xiaolong Zhu Junhong Zhang Xinwei Wang Hui Wang Yedong song Guobin Pei Xin Gou Linlong Deng Jiewei Lin State Key Laboratory of Engines Tianjin UniversityTianjin 300350China Tianjin Renai College Tianjin 301636China Weichai Power Co. Ltd.Weifang 261061China

The health monitoring and fault diagnosis of heavy-duty engines are increasingly important for energy storage ecosystem. During operation, vibration characters corresponding to the specific fault need to be extracted from the overall system vibration. Faulty characteristics emanating from one single cylinder are also mixed with those from other cylinders. Besides, the change of working condition brings strong nonlinearities in surface vibration. To solve these problems, an improved deep residual shrinkage network (IDRSN) is developed for detecting diverse engine faults at various degrees using single channel surface vibration signal. Within IDRSN, a wide convolution kernel is utilized in first convolution layer to capture the long-term fault-related impacts and eliminate the short-time random impact. The residual network module is adopted to enhance the focus the relevant components of vibration signals. Mini-batch training strategy is used to improve the model stability. Meanwhile, Gradient-weighted class activation map is adopted to assess the consistency between the learned knowledge and the fault-related information. The IDRSN is implemented to diagnosing a diesel engine under various faults, faulty degrees and operating speeds. Comparisons with existing models are analyzed in terms of hyper-parameters, training samples, noise resistance, and visualization. Results demonstrate the proposed IDRSN's superior performance on fault diagnosis accuracy, stability, anti-noise performance, and anti-interference performance. An average accuracy rate of 98.38 % was achieved by the proposed IDRSN, in comparison to 96.64 % and 93.56 % achieved by the DRSN and the wide-kernel deep convolutional neural network respectively. These results highlight the proposed IDRSN's superiority in diagnosing multiple faults under various working conditions, offering a low-cost, highly effective, and applicable approach for complex fault diagnosis tasks.

关键词： Improved deep residual shrinkage network Fault diagnosis Engine Vibration signal Multiple working conditions Deep learning

Heparin-binding protein as a predictor of mortality in patients with diabetes mellitus and community-acquired pneumonia in intensive care unit:a propensity score matched study

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World Journal of Emergency Medicine 2024年第4期15卷 263-272页

作者： Yuhan Sun Baoqing Sun Zhigang Ren Mingshan Xue Changju Zhu Qi liu Translational Medicine Center Department of Emergency Medicinethe First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory Healththe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510230China Department of Infectious Disease the First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China Henan Medical Key Laboratory of Emergency and Trauma Research Department of Emergency Medicinethe First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China

BACKGROUND:Patients with diabetes mellitus(DM)are vulnerable to community-acquired pneumonia(CAP),which have a high mortality *** aimed to investigate the value of heparin-binding protein(HBP)as a prognostic marker of mortality in patients with DM and ***:This retrospective study included CAP patients who were tested for HBP at intensive care unit(ICU)admission from January 2019 to April *** were allocated to the DM or non-DM group and paired with propensity score *** characteristics and clinical outcomes up to 90 days were *** primary outcome was the 10-day *** operating characteristic(ROC)curves,Kaplan-Meier analysis,and Cox regression were used for statistical ***:Among 152 enrolled patients,60 pairs were successfully *** was no significant difference in 10-day mortality,while more patients in the DM group died within 28 d(P=0.024)and 90 d(P=0.008).In the DM group,HBP levels at ICU admission were higher in 10-day non-survivors than in 10-day survivors(median 182.21[IQR:55.43-300]ng/ml *** 66.40[IQR:34.13-107.85]ng/mL,P=0.019),and HBP levels could predict the 10-day mortality with an area under the ROC curve of *** cut-off value,sensitivity,and specificity were 160.6 ng/mL,66.7%,and 90.2%,*** Cox regression analysis indicated that HBP was an independent prognostic factor for 10-day(HR 7.196,95%CI:1.596-32.455,P=0.01),28-day(HR 4.381,95%CI:1.449-13.245,P=0.009),and 90-day mortality(HR 4.581,95%CI:1.637-12.819,P=0.004)in patients with ***:Plasma HBP at ICU admission was associated with the 10-day,28-day,and 90-day mortality,and might be a prognostic factor in patients with DM and CAP.

关键词： Community-acquired pneumonia Diabetes mellitus Heparin-binding protein Propensity score match

Effect of sodium starch octenyl succinate-based Pickering emulsion on the physicochemical properties of hairtail myofibrillar protein gel subjected to multiple freeze-thaw cycles

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Food Science and Human Wellness 2024年第2期13卷 1018-1028页

作者： Huinan Wang Jiaxin Zhang Xinran liu Jinxiang Wang Xuepeng Li Jianrong Li Key Laboratory of Food Nutrition and Safety Ministry of EducationCollege of Food Science and EngineeringTianjin University of Science and TechnologyTianjin 300457China College of Food Science and Technology Bohai UniversityNational R&D Branch Center of Surimi and Surimi Products ProcessingJinzhou 121013China

A Pickering emulsion based on sodium starch octenyl succinate(SSOS)was prepared and its effects on the physicochemical properties of hairtail myofibrillar protein gels(MPGs)subjected to multiple freeze-thaw(F-T)cycles were *** whiteness,water-holding capacity,storage modulus(G')and texture properties of the MPGs were significantly improved by adding 1%-2%Pickering emulsion(P<0.05).Meanwhile,Raman spectral analysis demonstrated that Pickering emulsion promoted the transformation of secondary structure,enhanced hydrogen bonds and hydrophobic interactions,and promoted the transition of disulfide bond conformation from g-g-g to g-g-t and *** an emulsion concentration of 2%,theα-helix content decreased by 10.37%,while theβ-sheet content increased by 7.94%,compared to the *** F-T cycles,the structure of the MPGs was destroyed,with an increase in hardness and a decrease in whiteness and water-holding capacity,however,the quality degradation of MPGs was reduced with 1%-2%Pickering *** findings demonstrated that SSOS-Pickering emulsions,as potential fat substitutes,can enhance the gel properties and the F-T stability of MPGs.

关键词： Pickering emulsion Myofibrillar protein Gel properties Freeze-thaw stability Intermolecular interactions

High-speed penetration of ogive-nose projectiles into thick concrete targets:Tests and a projectile nose evolution model

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Defence Technology（防务技术） 2024年第2期32卷 553-571页

作者： Xu Li Yan liu Junbo Yan Zhenqing Shi Hongfu Wang Yingliang Xu Fenglei Huang State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing100081China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120China China Research and Development Academy of Machinery Equipment Beijing100089China

The majority of the projectiles used in the hypersonic penetration study are solid flat-nosed cylindrical projectiles with a diameter of less than 20 *** study aims to fill the gap in the experimental and analytical study of the evolution of the nose shape of larger hollow projectiles under hypersonic *** the hypersonic penetration test,eight ogive-nose AerMet100 steel projectiles with a diameter of 40 mm were launched to hit concrete targets with impact velocities that ranged from 1351 to 1877 m/*** erosion of the projectiles was observed during high-speed penetration of heterogeneous targets,and apparent localized mushrooming occurred in the front nose of recovered *** examining the damage to projectiles,a linear relationship was found between the relative length reduction rate and the initial kinetic energy of projectiles in different penetration ***,microscopic analysis revealed the forming mechanism of the localized mushrooming phenomenon for eroding penetration,i.e.,material spall erosion abrasion mechanism,material flow and redistribution abrasion mechanism and localized radial upsetting deformation ***,a model of highspeed penetration that included erosion was established on the basis of a model of the evolution of the projectile nose that considers radial upsetting;the model was validated by test data from the literature and the present *** upon the impact velocity,v0,the projectile nose may behave as undistorted,radially distorted or *** to the effects of abrasion of the projectile and enhancement of radial upsetting on the duration and amplitude of the secondary rising segment in the pulse shape of projectile deceleration,the predicted DOP had an upper limit.

关键词： High-speed penetration Concrete target Erosion Projectile nose evolution model

ST-LSTM-SA:A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

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Advances in Atmospheric Sciences 2024年第7期41卷 1364-1378页

作者： Hanxiao YUAN Yang liu Qiuhua TANG Jie LI Guanxu CHEN Wuxu CAI First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China Key Laboratory of Oceanic Surveying and Mapping Ministry of Natural ResourcesQingdao 266061China

The scarcity of in-situ ocean observations poses a challenge for real-time information acquisition in the *** the crucial hydroacoustic environmental parameters,ocean sound velocity exhibits significant spatial and temporal variability and it is highly relevant to oceanic *** this study,we propose a new data-driven approach,leveraging deep learning techniques,for the prediction of sound velocity fields(SVFs).Our novel spatiotemporal prediction model,STLSTM-SA,combines Spatiotemporal Long Short-Term Memory(ST-LSTM) with a self-attention mechanism to enable accurate and real-time prediction of *** circumvent the limited amount of observational data,we employ transfer learning by first training the model using reanalysis datasets,followed by fine-tuning it using in-situ analysis data to obtain the final prediction *** utilizing the historical 12-month SVFs as input,our model predicts the SVFs for the subsequent three *** compare the performance of five models:Artificial Neural Networks(ANN),Long ShortTerm Memory(LSTM),Convolutional LSTM(ConvLSTM),ST-LSTM,and our proposed ST-LSTM-SA model in a test experiment spanning 2019 to *** results demonstrate that the ST-LSTM-SA model significantly improves the prediction accuracy and stability of sound velocity in both temporal and spatial *** ST-LSTM-SA model not only accurately predicts the ocean sound velocity field(SVF),but also provides valuable insights for spatiotemporal prediction of other oceanic environmental variables.

关键词： sound velocity field spatiotemporal prediction deep learning self-allention

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注意力机制的混合卷积高光谱图像分类方法

光谱学与光谱分析 2024年第10期44卷 2916-2922页

作者：刘玉娟刘颜达闫振张智勇曹益铭宋莹吉林大学仪器科学与电气工程学院吉林长春130061 吉林大学国家地球物理探测仪器工程技术研究中心吉林长春130061 吉林大学地球信息探测仪器教育部重点实验室吉林长春130061 哈尔滨工业大学仪器科学与工程学院黑龙江哈尔滨150006

高光谱图像以其高分辨率的空间和光谱信息在军事、航空航天及民用等遥感领域均有重要应用,具有重要的研究意义。深度学习具有学习能力强、覆盖范围广及可移植性强的优势,成为目前高精度高光谱图像分类技术研究的热点。其中卷积神经网络(... 详细信息

高光谱图像以其高分辨率的空间和光谱信息在军事、航空航天及民用等遥感领域均有重要应用,具有重要的研究意义。深度学习具有学习能力强、覆盖范围广及可移植性强的优势,成为目前高精度高光谱图像分类技术研究的热点。其中卷积神经网络(CNN)因强大的特征提取能力广泛应用于高光谱图像分类方法研究中,取得了有效的研究成果,但该类方法通常单独基于2D-CNN或3D-CNN进行,针对高光谱图像的单一特征,一是不能充分利用高光谱数据本身完整的特征信息;二是虽然相应提取网络局部特征优化性好,但是整体泛化能力不足,在深度挖掘HSI的空间和光谱信息方面存在局限性。鉴于此,提出了基于注意力机制的混合卷积神经网络模型(HybridSN_AM),使用主成分分析法对高光谱图像进行降维,采用卷积神经网络作为分类模型的主体,通过注意力机制筛选出更有区分度的特征,使模型能够提取到更精确、更核心的空间-光谱信息,实现高光谱图像的高精度分类。对Indian Pines(IP)、University of Pavia(UP)和Salinas(SA)三个数据集进行了应用实验,结果表明,基于该模型的目标图像总体分类精度、平均分类精度和Kappa系数均高于98.14%、97.17%、97.87%。与常规HybridSN模型对比表明,HybridSN_AM模型在三个数据集上的分类精度分别提升了0.89%、0.07%和0.73%。有效解决了高光谱图像空间-光谱特征提取与融合的难题,提高HSI分类的精度,具有较强的泛化能力,充分验证了注意力机制结合混合卷积神经网络在高光谱图像分类中的有效性和可行性,对高光谱图像分类技术的发展及应用具有重要的科学价值。

关键词：高光谱图像分类注意力机制卷积神经网络多特征融合主成分分析

Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第3期16卷 895-908页

作者： Hongbo Zhao Shaojun Li Xiaoyu Zang Xinyi liu Lin Zhang Jiaolong Ren School of Civil Engineering and Geomatics Shandong University of TechnologyZibo255000China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan430071China

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical *** inverse analysis is commonly utilized to determine the physico-mechanical ***,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological *** this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic *** ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical *** programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical *** results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under ***,a slope case was employed to demonstrate the performance of the developed *** results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

关键词： Geological engineering Geotechnical engineering Inverse analysis Uncertainty quantification Probabilistic programming