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A reduced combustion mechanism of ammonia/diesel optimized with multi-objective genetic algorithm

Defence Technology（防务技术） 2024年第4期34卷 187-200页

作者： Wanchen Sun Shaodian Lin Hao Zhang Liang Guo Wenpeng Zeng Genan Zhu Mengqi Jiang State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130025China

For the deep understanding on combustion of ammonia/diesel,this study develops a reduced mechanism of ammonia/diesel with 227 species and 937 *** sub-mechanism on ammonia/interactions of N-based and C-based species(N—C)/NOx is optimized using the Non-dominated Sorting Genetic Algorithm II(NSGA-II)with 200 *** optimized mechanism(named as 937b)is validated against combustion characteristics of ammonia/methane(which is used to examine the accuracy of N—C interactions)and ammonia/diesel *** ignition delay times(IDTs),the laminar flame speeds and most of key intermediate species during the combustion of ammonia/methane blends can be accurately simulated by 937b under a wide range of *** for ammonia/diesel blends with various diesel energy fractions,reasonable predictions on the IDTs under pressures from 1.0 MPa to5.0 MPa as well as the laminar flame speeds are also achieved by *** particular,with regard to the IDT simulations of ammonia/diesel blends,937b makes progress in both aspects of overall accuracy and computational efficiency,compared to a detailed ammonia/diesel *** kinetic analysis reveals that the reaction pathway of ammonia during the combustion of ammonia/diesel blend mainly differs in the tendencies of oxygen additions to NH_2 and NH with different equivalence ratios.

关键词： Ammonia Diesel Combustion Kinetic mechanism Multi-objective optimization

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Human-Machine Shared Lateral control Strategy for Intelligent Vehicles Based on Human Driver Risk Perception Reliability

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Automotive Innovation 2024年第1期7卷 102-120页

作者： Dongjian Song Bing Zhu Jian Zhao Jiayi Han State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China

Intelligent vehicle(Ⅳ)technology has developed rapidly in recent ***,achieving fully unmanned driving still presents numerous challenges,which means that human drivers will continue to play a vital role in vehicle operation for the foreseeable ***-machine shared driving,involving cooperation between a human driver and an automated driving system(AVS),has been widely regarded as a necessary stage for the development of *** onⅣdriving safety,this study proposed a human-machine shared lateral control strategy(HSLCS)based on the reliability of driver risk *** HSLCS starts by identifying the effective areas of driver risk perception based on eye *** establishes an anisotropic driving risk field,which serves as the foundation for the AVS to assess risk *** upon the cumulative and diminishing effects of risk perception,the proposed approach leverages the driver's risk perception effective area and converts the risk field into a representation aligned with the driver's ***,it quantifies the reliability of the driver's risk perception by using area-matching ***,based on the driver’s risk perception reliability and dif-ferences in lateral driving operation between the human driver and the AVS,the dynamic distribution of driving authority is achieved through a fuzzy rule-based system,and the human-machine shared lateral control is completed by using model predictive *** HSLCS was tested across various scenarios on a driver-in-the-loop test *** results show that the HSLCS can realize the synergy and complementarity of human and machine intelligence,effectively ensuring the safety ofⅣoperation.

关键词： Intelligent vehicle Human-machine shared driving Risk perception Driving authority distribution

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A Hierarchical LSTM-Based Vehicle Trajectory Prediction Method Considering Interaction Information

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Automotive Innovation 2024年第1期7卷 71-81页

作者： Haitao Min Xiaoyong Xiong Pengyu Wang Zhaopu Zhang State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130012China

Trajectory prediction is an essential component in autonomous driving systems,as it can forecast the future movements of surrounding vehicles,thereby enhancing the decision-making and planning capabilities of autonomous driving *** models relying on constant acceleration and constant velocity often experience a reduction in prediction accu-racy as the forecasted timeframe *** limitation makes it challenging to meet the demands for medium to long-term trajectory ***,data-driven models,particularly those based on Long Short-Term Memory(LSTM)neural networks,have demonstrated superior performance in medium to long-term trajectory ***,this study introduces a hierarchical LSTM-based method for vehicle trajectory *** the difficulty of using a single LSTM model to predict trajectories for all driving intentions,the trajectory prediction task is decomposed into three sequential steps:driving intention prediction,lane change time prediction,and trajectory ***,given that the driving intent and trajectory of a vehicle are always subject to the influence of the surrounding traffic flow,the predictive model proposed in this paper incorporates the interactional information of neighboring vehicle movements into the model *** proposed method is trained and validated on the real vehicle trajectory dataset Next Generation *** results show that the proposed hierarchical LSTM method has a lower prediction error compared to the integral LSTM model.

关键词： Autonomous vehicles Trajectory prediction Long Short-Term Memory Driving intention prediction

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Design of energy-saving driving strategy based on proximal policy optimization considering urban transport information

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control Theory and Technology 2025年第1期23卷 74-90页

作者： Qifang Liu Dazhen Sun Haowen Chen Dongzi Li Ping Wang Department of Control Science and Engineering Jilin UniversityChangchun130022JilinChina State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun130022JilinChina

Eco-driving has always been an ongoing *** urban driving conditions,traffic regulations,other vehicle behaviors,and special driving scenarios will have a major impact on the energy consumption of autonomous *** a representative algorithm of artificial intelligence,reinforcement learning has the ability to perform well under complex *** paper uses deep reinforcement learning algorithms to design the economical driving strategies of autonomous vehicles in three driving scenarios:driving at signalized intersection under free traffic flow,car-following on ramps,and driving at signalized intersection considering queue *** the above three driving scenarios,the driving strategy proposed in this paper achieves economical driving performance while satisfying the driving scenario requirements.

关键词： Eco-driving strategy Reinforcement learning Signalized intersection Car-following

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Hierarchical Parking Path Planning Based on Optimal Parking Positions

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Automotive Innovation 2023年第2期6卷 220-230页

作者： Yaogang Zhang Guoying Chen Hongyu Hu Zhenhai Gao State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchunJilinChina

Automated valet parking(AVP)has attracted the attention of industry and academia in recent ***,there are still many challenges to be solved,including shortest path search,optimal time efficiency,and applicability of algorithm in complex *** this paper,a hierarchical AVP path planner is proposed,which divides a complete AVP path planning into the guided layer and the planning layer from the perspective of global *** guided layer is mainly used to divide a complex AVP path planning into several simple path plannings,which makes the hybrid A*algorithm more applicable in a complex parking *** planning layer mainly adopts different optimization methods for driving and parking path *** proposed method is verified by a large number of simulations which include the verification of the optimal parking position,the performance of the planner for perpendicular parking,and the scalability of the planner for parallel parking and inclined *** simulation results reveal that the efficiency of the algorithm is increased by more than 20 times,and the average path length is also shortened by more than 20%.Furthermore,the planner overcomes the problem that the hybrid A*algorithm is not applicable in complex parking scenarios.

关键词： Automated valet parking Path planning Hybrid A Visibility graph Shortest path

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Kinetically and thermodynamically expediting elementary steps via high-valence Cr-incorporated of nickel selenide for water electrolysis

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Nano Research 2024年第3期17卷 1199-1208页

作者： Huafeng Fan Dongxu Jiao Jinchang Fan Dewen Wang Bilal Zaman Wei Zhang Lei Zhang Weitao Zheng Xiaoqiang Cui State Key Laboratory of Automotive Simulation and Control School of Materials Science and EngineeringKey Laboratory of Automobile Materials of MOEJilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy MaterialsElectron Microscopy CenterJilin UniversityChangchun 130012China College of Chemistry Jilin UniversityChangchun 130012China

Designing high-performance electrocatalysts toward hydrogen evolution reaction(HER)and oxygen evolution reaction(OER)is essential to reduce the activation barrier and optimize free adsorption energy of reactive ***,we report that incorporating high-valence Cr into NiSe_(2)(Cr_(x)Ni_(1-x)Se_(2))kinetically and thermodynamically expedites elementary steps of both HER and *** as-prepared Cr_(0.05)Ni_(0.95)Se_(2) catalyst displays excellent HER and OER activities,with low overpotentials of 89 and 272 mV at the current density of 10 mA·cm^(-2)(j10),respectively,and remains stable during operation for 30 h.A low cell voltage of only 1.59 V is required to drive j10 in alkaline *** situ Raman spectroscopy reveals that Cr incorporation facilitates the formation of NiOOH active species during the OER ***,theoretical explorations demonstrate that high-valence Cr incorporation efficiently accelerates water dissociation kinetics and improves H*adsorption during HER process,lowering the activation barrier of OER and optimizing the adsorption energy of oxygen-based intermediate,thus kinetically and thermodynamically enhancing the intrinsic performance of NiSe_(2) for over water *** strategy provides a new horizon to design transition metal based electrocatalysts in the clean energy field.

关键词： nickel selenide electrocatalytic water splitting high-valence Cr density functional theory(DFT)calculation

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Open-source dataset for traffic light and countdown display detection in urban environment

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Science China(Information Sciences) 2025年第5期68卷 407-408页

作者： Shuchun WAN Haitao DING Jianwei ZHANG Yunfeng HU Hong CHEN State Key Laboratory of Automotive Simulation and Control Jilin University Department of Control Science and Engineering Jilin University College of Electronic and Information Engineering Tongji University

Here we introduce an open-source dataset for traffic light and countdown display detection,which includes three subsets:a subset of traffic light data,a subset of traffic light and countdown display data,and a subset ...

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Micro-structure evolution, precipitation behavior and strengthening mechanism of Ni-Cr-Mo system steel fabricated via laser powder bed fusion and subsequent quenching control

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Chinese Journal of Aeronautics 2025年第3期38卷 560-592页

作者： Qing WANG Deyin KONG Shihui ZHOU Xingran LI Zhihui ZHANG The Key Laboratory of Bionic Engineering(Ministry of Education) Jilin UniversityChangchun 130025China Weihai Institute for Bionic Jilin UniversityWeihai 264402China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130025China

High-performance 24CrNiMo steel was fabricated using Laser Powder Bed Fusion (LPBF). Subsequent quenching treatment was applied and the influence of quenching temperatures on micro-structure evolution and properties was systematically characterised and analysed. The micro-structure of the as-built steel consisted of two parts. The first part comprised martensite with twins combined with ω-Fe nano-particles, and the second part consisted of lower bainite in the molten pool, as well as upper bainite, granular bainite and tempered martensite in the heat-affected zone. With the quenching temperatures varying from 800℃ to 950℃, the micro-structure gradually transformed from acicular ferrite + martensite to tempered martensite +θ-Fe3C carbides, and the grain size exhibited noticeable growth. Moreover, quenching treatments could eliminate the anisotropy and inhomogeneity of the micro-structure. The rod-shaped nanosized η-Fe2C and θ-Fe3C precipitates were clearly observed, which were converted from ω-Fe and distributed at multiple angles in the lath. The size and number of nano-precipitates, triggered by the high self-tempering degree of martensite, gradually increased. The relationships among grain size, the twins, dislocation density and nano-precipitation and the dramatically improved performance of quenched samples were analysed using strengthening mechanisms. After quenching at 850℃, the as-built 24CrNiMo steel attained ultra-high mechanical properties including hardness, Ultimate Tensile Strength (UTS), Elongation (El) and impact energy with values of 480.9 HV_(1), 1611.4 MPa, 9.8% and 42.8 J, respectively. Meanwhile, both the wear and thermal fatigue resistance increased by approximately 40%. This study demonstrated that LPBF-fabricated 24CrNiMo steel, with matching good performances, can be achieved using a subsequent one-step quenching process.

关键词： Laser powder bed fusion 24CrNIMo steel Quenching control Micro-structure evolution Precipitate Comprehensive properties Strengthening mechanisms

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Carbon Energy 2025年第2期7卷 121-130页

作者： Tianyi Xu Dongxu Jiao Jinchang Fan Yilong Dong Zhaoyong Jin Lei Zhang Wei Zhang Jingxiang Zhao Weitao Zheng Xiaoqiang Cui State Key Laboratory of Automotive Simulation and Control Key Laboratory of Automobile MaterialsMinistry of EducationSchool of Materials Science and EngineeringJilin UniversityChangchunChina College of Chemistry Jilin UniversityChangchunChina Key Laboratory of Photonic and Electronic Bandgap Materials Ministry of EducationCollege of Chemistry and Chemical EngineeringHarbin Normal UniversityHarbinChina

Strain effects have garnered significant attention in catalytic applications due to their ability to modulate the electronic structure and surface adsorption properties of *** this study,we propose a novel approach called“similar stacking”for stress modulation,achieved through the loading of Co_(2)P on Ni_(2)P(Ni_(2)P/Co_(2)P).Theoretical simulations reveal that the compressive strain induced by Co_(2)P influences orbital overlap and electron transfer with hydrogen ***,the number of stacked layers can be adjusted by varying the precursor soaking time,which further modulates the strain range and hydrogen *** a 2-h soaking condition,the strain effect proves favorable for efficient hydrogen *** characterizations using X-ray diffraction,high-angel annular dark-field scanning transmission election microscope(HAADF-STEM),and X-ray absorption near-edge structure spectroscopy successfully demonstrate lattice contraction of Co_(2)P and bond length shortening of ***,our catalyst shows an ultrahigh current density of 1 A cm^(-2) at an overpotential of only 388 mV,surpassing that of commercial Pt/C,while maintaining long-term *** material design strategy of similar stacking opens up new avenues of strain modulation and the deeper development of electrocatalysts.

关键词： compressive strain heterogeneous phosphide hydrogen evolution reaction similar stacking

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Vehicle state and Bias Estimation Based on Unscented Kalman Filter with Vehicle Hybrid Kinematics and Dynamics Models

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Automotive Innovation 2023年第4期6卷 571-585页

作者： Shouren Zhong Yang Zhao Linhe Ge Zitong Shan Fangwu Ma State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China

In recent years,vehicle state estimation methods incorporating different vehicle models have received extensive *** the vehicle is disturbed by external forces not considered in traditional vehicle models(for example,a certain slope,or wind resistance different from theoretical calculation),the problem of model mismatch will occur,which leads to the inaccurate estimation of the vehicle *** solve this problem,an Unscented Kalman Filter(UKF)algorithm is used to fuse inertial navigation data with the vehicle hybrid model in this *** hybrid model introduces a switching strategy that fuses the vehicle kinematics and the dynamics models while augmenting biases that need to be estimated in the vehicle *** switching strategy resolves the integration divergence problem of vehicle dynamics models at low speeds and the inaccurate estimation of vehicle kinematics models at high *** experiments demonstrate that the proposed method can accurately estimate biases induced by external forces,enhancing the accuracy and confidence of states by eliminating errors caused by these *** robustness of the method is validated in vehicle verification platform experiments,where errors in vehicle lateral speed and yaw rate are reduced by 9.7 cm/s and 0.012°/s,respectively,under large curvature maneuvers,and 9.6 cm/s and 0.004°/s under quarter-turn *** proposed method significantly improves lateral speed and vehicle position accuracies.

关键词： Vehicle state estimation Vehicle hybrid models Unscented Kalman filter Integration stability

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