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Potential Field-Based Cooperative Adaptive Cruising Control for Longitudinal Following and Lane Changing of Vehicle Platooning

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SSRN 2023年

作者： Zhang, Zhentao Li, Xueyun Su, Chuqi Liu, Xun Xiong, Xin Wang, Yiping Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology Wuhan430070 China Hubei Technology Research Center of New Energy and Intelligent Connected Vehicle Engineering Wuhan University of Technology Wuhan430070 China Wuhan University of Technology China

Abstract: When the vehicle platooning enters the highway, the platooning often needs to perform continuous lane changing. The simultaneous occurrence of lateral and longitudinal following behavior makes it challenging for the vehicle platooning to maintain stability. To address the challenges of lateral and longitudinal stability in vehicle platooning, a control method based on Artificial Potential Field (APF) is proposed. The control method combines a non-linear gravitational potential field with a repulsive potential field. Moreover, a virtual trailing potential field is applied behind the follower vehicle to reduce the accumulation of longitudinal errors in the platoon. For the two-dimensional plane scenario, a vehicle lateral and longitudinal coupling controller based on the potential field force vector is designed. By introducing the virtual leading vehicle, the phenomenon of the follower vehicle early steering is avoided. The proposed potential field-based controller is validated in New Europe Drive Cycle (NEDC) working condition scenario and two-lane lane changing scenario. Compared with the common model predictive control method, the results indicate that the proposed control method can effectively improve the control accuracy of the longitudinal follow-up, and generate more compact lane change trajectories. © 2023, The Authors. All rights reserved.

关键词： Controllers

An Extented Single Particle Method for Lithium-ion Batteries

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An Extented Single Particle Method for Lithium-ion Batteries

Power Electronics and Application Symposium (PEAS), IEEE International

作者： Haiqin Song Jianqiang Kang Qian Wang Jing V. Wang Guorong Zhu Chunhu Qian Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan China College of Automation Wuhan University of Technology Wuhan China Energy Storage Department Flextech Company Wuhan China

In order to reduce the computational complexity of the electrochemical modelling of lithium-ion batteries and improve the computational speed, this paper proposes a simplification method for the modelling of lithium-ion batteries. Based on the existed single particle model of lithium-ion battery, this article simplifies the solid-liquid diffusion process and proposes an extended single particle model. Simulation based on COMSOL is performed to verify the proposed model. Compared with the full order electrochemical model, the calculation speed of the proposed method under 1C discharge rate only takes 0.6054 seconds, which is only 10.9% of P2D. In addition, the mean square error under constant current condition is 2.95 mV only, and the dynamic condition error is 10.12 mV. The results verify the superiority of the proposed model in calculation speed with enough accuracy.

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Investigation of Diesel Particulate Filter Performance Under Typical Failure Conditions

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SSRN 2024年

作者： Yan, Fuwu Cai, Zhizhou Li, Zhenguo Zhu, Lei Chen, Peng Zheng, Shijie Wu, Yan Li, Yuxuan Hu, Jie Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology Wuhan430070 China Hubei Research Center for New Energy & Intelligent Connected Vehicle Wuhan University of Technology Wuhan430070 China National Engineering Laboratory for Mobile Source Emission Control Technology China Automotive Technology & Research Center Tianjin300300 China Kailong High Technology Company Limited Wuxi214174 China

Diesel particulate filter (DPF) is one of the most effective particulate reduction components in diesel engine aftertreatment systems. However, prolonged utilization of a DPF might result in a deterioration in performance or even failure, such as ash-clogging, melting, breakage, and catalyst deactivation. It is crucial to conduct research on DPF performance degradation across a series of partially failed conditions. In this study, the morphology and chemical composition of the ash in the DPF samples were characterized. The effects of degree-varying clogging and unplugged-breakage failure on exhaust characteristics as well as DPF temperature, filtration and pressure drop characteristics were investigated. A canonical correlation analysis (CCA) was finally conducted considering the sensitivity differences between DPF performance parameters and failure index parameters. The results indicate that the DPF temperature difference and filtration efficiency are mainly related to the ash loading and breakage index, while the pressure difference is most affected by the exhaust mass flow rate. Increasing the DPF inlet temperature declines the pressure drop and slightly increases the filtration efficiency and DPF temperature difference, but these effects are not significant. These findings contribute to the prediction of DPF performance in partially failed states and the development of DPF failure diagnosis methods. © 2024, The Authors. All rights reserved.

关键词： Drops

Morphology, Microstructure and Mechanical Property of Laser Brazing of Galvanized Steel in a Flange Butted Configuration

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SSRN 2024年

作者： Yan, Fei Zhang, Mengtao Chen, Hongsheng Ouyang, Gang Peng, Sanwen Chen, Hao Huang, Bingyu Zhang, Dingrui Yang, Guangyuan Xiang, Xinyi Zhang, Qian Wang, Chunming Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China School of Computer Science and Technology Hubei University of Science and Technology Xianning437100 China School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Wuhan University of Technology China Huazhong University of Science and Technology China

In this study, hot-dip galvanized steel sheet was joined in a flange butted configuration using laser brazing with CuSi3 filler metal. An orthogonal test involving four factors and five levels was experimentally designed to ascertain the optimal parameters and analyze the impact of welding factors on weld characteristics. The morphology, microstructure and mechanical property of laser brazed joints were carefully investigated using an optical microscope, scanning electron microscope equipped with energy spectrum analysis and other methodologies. The results showed that a joint with good forming quality was successfully achieved under the optimized brazing parameters. Welding speed was the most important factor affecting weld cross-section difference in the width, followed by defocusing amount, laser power and feeding speed. The microstructure near the fusion line was transformed from fine equiaxed grains to coarse columnar grains due to the fast cooling rate of the molten pool during solidification. The formation of wedge-shaped structures played a pinning role, which greatly enhanced the binding force at the interface. It has been also found that the occurrence of the composition segregation in the brazed joint increased the cracking susceptibility, thereby lowering the load capacity of the joint. The tensile strength of improved joints was obviously higher than that of the base metal. It was mainly credited to good surface forming and pinning effect of wedge-shaped structures under the optimized conditions. © 2024, The Authors. All rights reserved.

关键词： Welds

A Simplified Electrochemical Model for Lithium-Ion Batteries Based on Ensemble Learning

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SSRN 2023年

作者： Zhu, Guorong Kong, Chun Wang, Jing V. Chen, Weihua Wang, Qian Kang, Jianqiang School of Automation Wuhan University of Technology Wuhan430070 China Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan430070 China College of Chemistry Green Catalysis Center Zhengzhou University Zhengzhou450001 China

The mass transfer in lithium-ion batteries is a low-frequency dynamic that affects the voltage and performance of lithium-ion batteries. To find an effective way to describe the mass transfer in lithium-ion batteries, a simplified electrochemical lithium-ion battery model based on ensemble learning is proposed. The proposed model simplifies lithium-ion transfer in electrode particles with ensemble learning which ensembles discrete-time realization algorithm (DRA), fractional-order Padé approximation model (FOM), and three parameters parabolic (TPM). The lithium-ion transfer in the electrolyte is simplified by the first-order inertial element (FIE). The results show that the proposed model achieves not only accurate lithium-ion concentration prediction in solid and electrolyte phase but also precise voltage prediction with low computational complexity. © 2023, The Authors. All rights reserved.

关键词： Lithium-ion batteries

Research on Deformation Law and Forming Accuracy of Dieless Single Point Incremental Forming Based on Machine Vision

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SSRN 2022年

作者： Li, Yan Pang, Qiu Hu, Zhi-Li Hubei Key Laboratory of Advanced Technology of Automobile Components Wuhan University of Technology Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology 430070 China Hubei Research Center for New Energy & Intelligent Connected Vehicle Wuhan University of Technology Wuhan430070 China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China

Dieless single point incremental forming is very suitable for individual and small batch processing, due to its advantages of high flexibility and low cost. However, it has always been difficult to control the surface quality and geometric accuracy of the part. In this paper, a dieless single point incremental forming device based on machine vision is designed to study the deformation law of parts and the evolution law of forming accuracy under different process parameters. The results show that the defects of wrinkle, fracture, discontinuous outer contour and poor geometric accuracy are easy to appear in the dieless single point incremental forming. A high accuracy multi-pass single point incremental forming model based on machine vision is established. In this model, the contour data of the part is obtained online, and the relationship between the toolpath and the actual contour is fitted by neural network in the multi-pass forming, then the forming toolpath is automatically optimized. By combining with the ring washer to constrain the deformation of the material, problems of discontinuous outer contour and poor geometric accuracy of the part are solved. Finally, the deviation is controlled within 0.5mm, and high efficiency and high accuracy incremental forming is achieved. © 2022, The Authors. All rights reserved.

关键词： Surface properties

Influence of the Engine Drop-to-Idle Process on Regeneration Temperature, Filtration and Morphology Characteristics of Diesel Particulate Filters

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SSRN 2023年

作者： Cai, Zhizhou Yan, Fuwu Hu, Jie Wu, Hanming Liao, Jianxiong Wu, Yan Zheng, Shijie Li, Zhenguo Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of Technology Wuhan430070 China Hubei Research Center for New Energy & Intelligent Connected Vehicle Wuhan University of Technology Wuhan430070 China National Engineering Laboratory for Mobile Source Emission Control Technology China Automotive Technology & Research Center Tianjin300300 China

As emission regulations become increasingly stringent, the durability of diesel aftertreatment system is another concern in addition to the excellent purification capacity. Under extreme circumstances, the engine may drop to idle (DTI) sharply and if active regeneration occurs during this period, there is a risk of DPF cracking and melting due to the huge accumulation of soot combustion heat. In this study, regeneration performances, including temperature and transient emission characteristics of cordierite DPF during a DTI process were investigated. The temperature distribution is highly nonuniform, with the peak temperature appearing in the middle ring of the DPF monolith's rear end. As the soot load reached 7 g/L, extensive DPF cracks can be observed and the PN emission dramatically exceeded the regulatory limit. In addition, the evolution of a porous wall's macro morphology and micro pore structure was examined. Numerous microcracks were formed and the wall surface became rougher and more irregular. The substrate's bulk density, average pore diameter, and permeability decreased whilst its total pore volume, total pore area, tortuosity, and porosity increased. The findings contribute to a better comprehension of DPF designs, regeneration strategies and durability improvements. © 2023, The Authors. All rights reserved.

关键词： Morphology

In situ synthesis of a porous high-Mn and high-Al steel by a novel two-step pore-forming technique in vacuum sintering

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Journal of Materials Science & technology 2020年第4期39卷 82-88页

作者： Chuanbing Zhuang Zhigang Xu Shangyu Huang Yu Xia Chuanbin Wang Qiang Shen Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of TechnologyWuhan 430070China Hubei Collaborative Innovation Center for Automotive Components Technology Wuhan University of TechnologyWuhan 430070China School of Materials Science and Engineering Wuhan University of TechnologyWuhan 430070China State Key Lab of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Hubei Engineering Research Center for Green Precision Materials Forming Wuhan University of TechnologyWuhan 430070China

In this work, a novel in-situ two-step pore-forming process in vacuum sintering(ITPVS) technique combining low-temperature processing to produce open pores through the interdiffusion among the intrinsic components in the base steel, and subsequent high-temperature processing to further improve the porosities by the sublimation of Mn via previously formed open pores, was proposed to produce a lab-scale porous Fe Mn Al steel. For the first time, a high-Mn and high-Al steel with open and overall porosities of ~59.6 vol.% and ~63.7 vol.%(percent in volume, vol.%) was synthesized by isothermal holding of the quaternary elemental Fe/Mn/Al/C powder mixture at 640℃ for 1 h and the subsequent sintering at 1200℃ for 1 h. Elemental Al partly incorporated into/reacted with α-Fe and α-Mn after sintering at640℃ for 1 h, leading to the overall and open porosities promoting by ~26.6 vol.% and ~25.6 vol.%. After sintering at 1200℃, Fe Mn Al steel with increased porosities mainly comprising of austenite and α-Fe obtained. The compression strength and corresponding strain of the 1200℃-sintered porous specimen without crack on the surface was ~75 MPa and ~25%. The ITPVS technique takes advantage of using the intrinsic components like Al, Mn and Fe in steels to produce porous structure. This is beneficial to avoiding the contamination of the Fe Mn Al steel matrix caused by the employment of the foreign pore-forming agents.

关键词： Porous metal High manganese steel Two-stage sintering Reaction-diffusion Sublimation method

Driving Behavior Recognition Based on EEG Data from a Driver Taking over Experiment on a Simulated Autonomous Vehicle 4

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Driving Behavior Recognition Based on EEG Data from a Driver...

2020 4th International Workshop on advanced Algorithms and Control Engineering, IWAACE 2020

作者： Zou, Bin Xiao, Zhenming Liu, Mutian Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Wuhan China

Driving behavior recognition is a critical part of the driver safety system. Most of the popular researches have utilized the driver's questionnaire data and driving data to recognize driving behavior. But few studies have used physiological data to recognize different driving behaviors, such as EEG data. In this paper, a new method was presented to recognize different driving behaviors based on EEG data. The driving data and EEG data were collected when participants took over the autonomous vehicle. Through K-means, the driving data were classified into two groups, and the classification results were utilized as inputs to generate a k-Nearest-Neighbor model to recognize driving behavior groups via EEG data. The results showed that the average recognition accuracy was 80.6%, and the highest recognition accuracy was 84.2%, indicating that there is an obvious relation between EEG data and driver taking over behavior. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Nearest neighbor search