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Investigation on the Mechanical Properties and Shape Memory Effect of Landing Buffer Structure Based on Ni Ti Alloy Printing

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Chinese Journal of Mechanical Engineering 2023年第4期36卷 415-424页

作者： Zhenglei Yu Renlong Xin Zezhou Xu Yining Zhu Xiaolong Zhang Shijie Hao Zhihui Zhang Ping Liang State Key Laboratory of Automotive Simulation and Control Jilin University Key Lab of Bionic Engineering Ministry of Education Jilin University Agriculture College Yanbian University State Key Laboratory of Heavy Oil Processing China University of Petroleum

With the deepening of human research on deep space exploration, our research on the soft landing methods of landers has gradually deepened. Adding a buffer and energy-absorbing structure to the leg structure of the lander has become an effective design solution. Based on the energy-absorbing structure of the leg of the interstellar lander, this paper studies the appearance characteristics of the predatory feet of the Odontodactylus scyllarus. The predatory feet of the Odontodactylus scyllarus can not only hit the prey highly when preying, but also can easily withstand the huge counter-impact force. The predatory feet structure of the Odontodactylus scyllarus, like a symmetrical cone, shows excellent rigidity and energy absorption capacity. Inspired by this discovery, we used SLM technology to design and manufacture two nickel-titanium samples, which respectively show high elasticity, shape memory, and get better energy absorption capacity. This research provides an effective way to design and manufacture highmechanical energy-absorbing buffer structures using bionic 3D printing technology and nickel-titanium alloys.

关键词： Bionic protective structure Odontodactylus scyllarus NiTi alloy 3D printing Numerical simulation Recoverability

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An enhanced eco-driving strategy based on reinforcement learning for connected electric vehicles:cooperative velocity and lane-changing control

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Journal of Intelligent and Connected Vehicles 2022年第3期5卷 316-332页

作者： Haitao Ding Wei Li Nan Xu Jianwei Zhang State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchunChina

Purpose–This study aims to propose an enhanced eco-driving strategy based on reinforcement learning(RL)to alleviate the mileage anxiety of electric vehicles(EVs)in the connected ***/methodology/approach–In this paper,an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space(EEDC-HRL)is proposed for connected *** EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential ***,this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving ***–To illustrate the performance for the EEDC-HRL,the controlled EV was trained and tested in various traffic flow *** experimental results demonstrate that the proposed technique can effectively improve energy efficiency,without sacrificing travel efficiency,comfort,safety and lane-changing performance in different traffic flow ***/value–In light of the aforementioned discussion,the contributions of this paper are *** enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space(EEDC-HRL)is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs.A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

关键词： Ecological driving Electric vehicles Reinforcement learning in hybrid action space Velocity and lane-changing control Reward function

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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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Estimating NOx Sensor Ammonia Cross-Sensitivity Factor Using a Data-Driven Approach in SCR Systems 7

Estimating NOx Sensor Ammonia Cross-Sensitivity Factor Using...

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7th CAA International Conference on Vehicular control and Intelligence, CVCI 2023

作者： Wang, Ning Gong, Xun Hu, Yunfeng Sun, Yao State Key Laboratory of Automotive Simulation and Control College of Artificial Intelligence Jilin University Changchun China State Key Laboratory of Automotive Simulation and Control College of Telecommunications Engineering Jilin University Changchun China State Key Laboratory of Automotive Simulation and Control College of Automotive Engineering Jilin University Changchun China

ISBN: (纸本)9798350340488

Selective Catalytic Reduction (SCR) is a module used in the aftertreatment system to mitigate the nitrogen oxides (NOx) emissions, and it can be affected by cross-sensitivity, resulting in a decrease in control performance and even controller failure. A commonly adopted approach is estimating the cross-sensitivity factor to correct the downstream NOx concentration, but the current estimation strategies often incur relatively high costs. In this paper, we propose a novel and more cost-effective method based on data-driven for estimating the cross-sensitivity factor. Specifically, we design a network architecture based on Long Short-Term Memory (LSTM) and attention mechanism. LSTM is utilized to capture the non-linear relationship between input features, historical information, and the cross-sensitivity factor. The introduced attention mechanism allows the model to focus more on important information, thereby further improving the estimation accuracy. This method eliminates the need for complex mechanism modeling and parameter calibration, and reduces the computational burden during online operation, resulting in significant time and computational resource *** simulation experiments conducted transient bench data validate the excellent performance of the designed cross-sensitivity factor estimator, as evidenced by comparative analysis with three alternative methods, and demonstrate the rationality of feature selection through the feature ablation analysis. © 2023 IEEE.

关键词： aftertreatment attention cross-sensitivity factor Long Short-Term Memory

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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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Frame Optimization Design Based on Improved Grey Relational Analysis

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Journal of Shanghai Jiaotong university(Science) 2024年第6期29卷 1071-1080页

作者： WANG Shuang WANG Dengfeng NING Zhanjin HU Zhongjian Department of Emergency Rescue China Fire and Rescue InstituteBeijing 102202China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China

For effectively improving the overall performance of fire truck frame structure,and solving the complexity of previous methods in the frame optimization design process,the traditional grey relational grade ranking needs to be ***,the first-order modal test was conducted to verify the validity of the initial frame ***,based on this model,a high-strength steel frame was designed to reduce deformation,maximum stress,and frame mass,and increase the fatigue life and the frequencies of the first bending modal and first torsional *** groups of sample points were generated through Hammersley ***,improved grey relational analysis with principal component analysis was proposed to realize the optimal design of the frame ***,the optimal combination of design parameters for the frame was obtained using the proposed ***,the optimized frame structure is found by comparing the models before and after optimization,and the mass is reduced by 14.8%.Moreover,the computational cost can be reduced by 135%when the proposed method is compared with the previous ***,the proposed method can effectively improve the performance of the frame and improve the computational efficiency.

关键词： fire truck frame structure optimization design improved grey relational analysis principal component analysis

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Precise Compound control of Loading Force for Electric Load Simulator of Electric Power Steering Test Bench

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Chinese Journal of Mechanical Engineering 2022年第1期35卷 255-265页

作者： Changhua Dai Guoying Chen Changfu Zong Buyang Zhang College of Automotive Engineering Jilin UniversityChangchun 130022China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China

Electric load simulator(ELS) systems are employed for electric power steering(EPS) test benches to load rack force by precise control. Precise ELS control is strongly influenced by nonlinear factors. When the steering motor rapidly rotates, extra force is directly superimposed on the original static loading error, which becomes one of the main sources of the final error. It is key to achieve ELS precise loading control for the entire EPS test bench. Therefore, a three-part compound control algorithm is proposed to improve the loading accuracy. First, a fuzzy proportional–integral plus feedforward controller with force feedback is presented. Second, a friction compensation algorithm is established to reduce the influence of friction. Then, the relationships between each quantity and the extra force are analyzed when the steering motor rapidly rotates, and a net torque feedforward compensation algorithm is proposed to eliminate the extra force. The compound control algorithm was verified through simulations and experiments. The results show that the tracking performance of the compound control algorithm satisfies the demands of engineering practice, and the extra force in the ELS system can be suppressed by the net torque corresponding to the actuator’s acceleration.

关键词： Electric load simulator Electric power steering Extra force Compound control

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Construction of Multi-Scale Aging Indicators Based on the Aging Mechanism of Fuel Cells

Construction of Multi-Scale Aging Indicators Based on the Ag...

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2024 Vehicle Powertrain Diversification Technology Forum, VPD 2024

作者： Lin, Yipeng Min, Haitao Sheng, Xia Zhang, Zhaopu Sun, Weiyi Jilin University State Key Laboratory of Automotive Simulat China China FAW Corporation Limited General Research and Developm China State Key Laboratory of Automotive Simulation and Control China

State of health (SOH) estimation is essential to ensure safety and reliability in the operation of Proton Exchange Membrane Fuel Cells (PEMFCs). The aging of fuel cells results from the deterioration of multiple internal components, and the aging degree of some key components even directly determines the end of cell life. Due to the complexity of the internal reactions in fuel cell, many internal parameters cannot be measured or recorded during aging tests. In addition, external characteristics do not reflect the internal changes in the cell. Therefore, establishing a multi-scale metric based on fuel cell components is very important for fuel cell life research. During the aging process of a fuel cell, the contributions of different components to the overall aging vary significantly. Additionally, the allocation of indicator parameters presents a challenge in multi-scale modeling. To address these issues, this paper proposes a method to construct multi-scale indicators for fuel cells. Firstly, based on the operational mechanisms of fuel cells, a 3-D Computational Fluid Dynamics (CFD) model of the fuel cell is developed using COMSOL Multiphysics 6.2 to simulate the working environment of the fuel cell. In addition, based on existing research, the aging mechanisms of various fuel cell components are analyzed, and aging models are established. The aging of selected components is then simulated in MATLAB R2023a based on the component aging mechanism model. Moreover, a co-simulation platform based on COMSOL and MATLAB is established to facilitate parameter interaction and iteration between the two models, thereby obtaining the aging data of the cell. Finally, the data is analyzed to select parameters and allocate coefficients for the multi-scale aging indicators. The multi-scale aging indicator can provide an effective approach to characterizing the aging state of fuel cells. © 2025 SAE International.

关键词： MATLAB

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Towards Safe Autonomous Driving:Decision Making with Observation‑Robust Reinforcement Learning

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automotive Innovation 2023年第4期6卷 509-520页

作者： Xiangkun He Chen Lv State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchunChina School of Mechanical and Aerospace Engineering Nanyang Technological University639798 NanyangSingapore

Most real-world situations involve unavoidable measurement noises or perception errors which result in unsafe decision making or even casualty in autonomous *** address these issues and further improve safety,automated driving is required to be capable of handling perception ***,this paper presents an observation-robust reinforcement learning against observational uncertainties to realize safe decision making for autonomous ***,an adversarial agent is trained online to generate optimal adversarial attacks on observations,which attempts to amplify the average variation distance on perturbed *** addition,an observation-robust actor-critic approach is developed to enable the agent to learn the optimal policies and ensure that the changes of the policies perturbed by optimal adversarial attacks remain within a certain ***,the safe decision making scheme is evaluated on a lane change task under complex highway traffic *** results show that the developed approach can ensure autonomous driving performance,as well as the policy robustness against adversarial attacks on observations.

关键词： Autonomous vehicle Robust reinforcement learning Safe decision making Adversarial attack

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BPNN Based Energy Management Strategy for Pure Electric Vehicles 7

BPNN Based Energy Management Strategy for Pure Electric Vehi...

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7th CAA International Conference on Vehicular control and Intelligence, CVCI 2023

作者： Zhang, Shilong Wang, Fei Lu, Henghui Yang, Shen State Key Laboratory of Automotive Simulation and Control Jilin University Changchun China

ISBN: (纸本)9798350340488

In order to enhance the real-time performance of model predictive control (MPC) based energy management strategy (EMS), this paper proposes a real-time automotive energy management strategy based on backpropagation neural network (BPNN) approximation of MPC controller. Firstly, establish a pure electric vehicle (PEV) simulation model, then design a BP neural network, and the joint simulation model is established to predict the speed, the energy management is finally realized by combining the energy consumption evaluation model. Compared with the EMS based on MPC controller, the energy-saving control effect is marginally diminished, and the real-time performance of vehicle speed track prediction is greatly improved. The proposed EMS can optimize the driver's speed trajectory and control vehicle movement in real-time, resulting in better comprehensive energy-saving control effects compared to traditional MPC. © 2023 IEEE.

关键词： Backpropagation neural network Electric vehicles Energy management strategy Model predictive control Velocity prediction

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