2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)最新文献_第5页

Energy Management of HEV in Platoon Operation with Constant Headway Policy 恒车头策略下混合动力汽车排操作的能量管理

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338605

Xinyue Wang, Jiangyan Zhang, Rubo Zhang

引用次数: 1

Analysis and Prevention of Chain Collision in Traditional and Connected Vehicular Platoon 传统与互联车辆排链碰撞分析与预防

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338496

Kan Wang, Haoran Liu, Jie Zeng, Chengyong Niu, Fei Cao, J. Ji

引用次数: 1

Optimal Eco-driving Control for Plug-in Hybrid Electric Vehicles Based on Neural Network 基于神经网络的插电式混合动力汽车最优生态驾驶控制

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338559

Jie Li, Z. Lei, ZhiHang Chen, Zheng Chen, Yonggang Liu

{"title":"Optimal Eco-driving Control for Plug-in Hybrid Electric Vehicles Based on Neural Network","authors":"Jie Li, Z. Lei, ZhiHang Chen, Zheng Chen, Yonggang Liu","doi":"10.1109/CVCI51460.2020.9338559","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338559","url":null,"abstract":"with the development of intelligent and connected vehicles, a novel approach for energy-saving, i.e. eco-driving control, has attracted much attention from relative researchers. The combination of eco-driving control and plug-in hybrid electric vehicles provide an opportunity to achieve further energy-saving for transportation. In this paper, an optimal eco-driving control strategy is proposed for plug-in hybrid electric vehicles based on the neural network. In order to mitigate the huge computational cost of velocity optimization and powertrain control, an efficient hierarchical optimal control strategy is proposed. An artificial neural network is constructed for the modeling of optimal energy cost. This optimal energy cost model is applied as objective function in the solving of the optimal eco-driving problem. The simulation results show that the proposed method can improve fuel economy by 4.29-12.71%, compared with conventional eco-driving control strategy. The neural network based optimal energy cost model significantly heightens the computational efficiency, with small sacrifice for fuel economy compared to optimal bench mark.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129685529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Distributed Algorithm Based on Local Centrality for Dynamic Social Network Re-construction in Multi-Agent Systems 基于局部中心性的分布式多智能体系统动态社会网络重构算法

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338641

Bing Xie, Xingju Lu

{"title":"A Distributed Algorithm Based on Local Centrality for Dynamic Social Network Re-construction in Multi-Agent Systems","authors":"Bing Xie, Xingju Lu","doi":"10.1109/CVCI51460.2020.9338641","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338641","url":null,"abstract":"In this paper, we focus on a self-adaptive network reconstruction problem in a distributed multi-agent system. In this system, the relationship among agents forms a complex network, in which each agent plays two roles, task execution and communication. As agents move, the topology of the relationship changes, which could reduce the system's performance. To guarantee the performance, we design a local centrality for evaluating the vitality of nodes in the network, and propose a distributed re-construction algorithm (DRA) based on the local centrality for re-constructing the dynamic network. To test the efficiency of DRA, we integrate DRA into our former proposed dynamic task allocation algorithm to form a new dynamic task allocation algorithm. The experiment shows that our new improved algorithm performs more efficiently when compared to other dynamic task allocation algorithms. The results illustrate the efficiency of reconstructed dynamic complex networks, which also indicates that the local centrality preforms efficient. Finally, we replace the local centrality with degree centrality and LocalRank in DRA and execute a series of experiments for performance evaluation. The results demonstrate the high efficiency of LC.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130766392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization of channel dimensions and gas diffusion layer thickness based on mass transfer characteristics of proton exchange membrane fuel cell 基于质子交换膜燃料电池传质特性的通道尺寸和气体扩散层厚度优化

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338549

Zhina Wang, Yujie Ding, Liangfei Xu, Zunyan Hu, Huize Liu, Jianqiu Li, Yishu Zhang, M. Ouyang

{"title":"Optimization of channel dimensions and gas diffusion layer thickness based on mass transfer characteristics of proton exchange membrane fuel cell","authors":"Zhina Wang, Yujie Ding, Liangfei Xu, Zunyan Hu, Huize Liu, Jianqiu Li, Yishu Zhang, M. Ouyang","doi":"10.1109/CVCI51460.2020.9338549","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338549","url":null,"abstract":"To improve the volume power density of proton exchange membrane fuel cell (PEMFC), a design of graphite bipolar plate straight channel characterized by narrow ribs is studied in this article. A three-dimensional multiphase model of PEMFC is employed to analyze the effects of the geometric parameters on the mass transfer characteristics and power density. The results show that smaller channel width and channel depth can enhance water removal and gas transport, which could increase the fuel cell performance. However, the influence of gas diffusion layer (GDL) thickness on fuel cell performance is not monotonous which means that there is an optimal value. The overall dimensions are optimized with volume power density as objective function. The best performance is obtained when the channel width, channel depth and GDL thickness are 0.1, 0.2 and 0.05 mm, respectively. Compared with the conventional channel design, the volume power density of optimal channel is significantly increased by 211.32% at 0.6 V.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132053186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling and simulation of coordinated driving and braking control for fuel cell hybrid electric vehicle 燃料电池混合动力汽车驱动与制动协调控制建模与仿真

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338542

Hang Li, Jianqiu Li, Jiayi Hu, Jingkang Li, Zunyan Hu, Liangfei Xu, M. Ouyang

{"title":"Modeling and simulation of coordinated driving and braking control for fuel cell hybrid electric vehicle","authors":"Hang Li, Jianqiu Li, Jiayi Hu, Jingkang Li, Zunyan Hu, Liangfei Xu, M. Ouyang","doi":"10.1109/CVCI51460.2020.9338542","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338542","url":null,"abstract":"The fuel cell hybrid electric vehicle (FCHEV) is a new type of vehicle with the advantages of high efficiency and environmental protection. As the government and society pay more and more attention to environmental and energy issues, the development of FCHEV has entered an important stage. The control algorithm of FCHEV is a key technology of new energy vehicles and requires research. This research mainly focuses on the power system modeling and the longitudinal dynamics control and simulation of FCHEV. Based on the tire model, a new slip ratio estimation strategy was proposed. The target drive torque control algorithm and the anti-slip control algorithm adopt the feedforward control and Proportional-integral feedback control. The hydraulic braking force and the regenerative braking force were distributed to ensure that the motor exerts the maximum regenerative braking capability, while the braking force distribution meets the requirements of the ECE braking regulations. On the MATLAB/Simulink software platform, a FCHEV power system model and a coordinated driving and braking control model were established. Through simulations in different working conditions, this paper proved the performance of the new slip ratio estimation algorithm and the feasibility of the dynamics control algorithm.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133568426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fast Dynamic Response Control for Bidirectional Single-stage Isolated Matrix Converter 双向单级隔离矩阵变换器的快速动态响应控制

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338646

Xiangjie Li, Bin Duan, Jinqiu Song, Yifeng Li, Dongxiang Wan, Chenghui Zhang

引用次数: 1

Research on the Control Method of Auto AMT Variable Parameter Shift Process 自动AMT变参数换挡过程控制方法研究

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338565

Haonan Zhang, Youkun Zhang, Jianhua Wang, Zhifei Xue

引用次数: 0

Technical assessment and feasibility validation of liquid hydrogen storage and supply system for heavy-duty fuel cell truck 重型燃料电池卡车液氢储供系统技术评估与可行性验证

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338639

Qing Wang, Jianqiu Li, Y. Bu, Liangfei Xu, Yujie Ding, Zunyan Hu, Ruimin Liu, Yunfei Xu, Zhidong Qin

引用次数: 7

Research on the metaphorical mapping method between the design concept of intelligent Internet connected vehicle and multi-sensory design elements 智能网联汽车设计理念与多感官设计要素的隐喻映射方法研究

2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338519

Bangbei Tang, Yingzhang Wu, Xiaolin Tang, Wenyu He, Shengnan Chen, Wenrui Feng

引用次数: 0