基本信息

徐坤  男  博导  中国科学院深圳先进技术研究院
电子邮件: kun.xu@siat.ac.cn
通信地址: 广东省深圳市南山区桃源街道学苑大道1068号
邮政编码: 518055

研究领域与研究方向

研究领域:智能车(UGV/UAV) ;无人系统; 智能驾驶; 新能源汽车; 储能系统

研究方向:1. 环境感知 ;SLAM ;状态感知 ; 2. 规划决策 ;运动控制; 3. 多智能体协同; 4. 能量管理 ;电池管理

 




招生信息

       欢迎有志从事智能车辆、机器人及其他智能系统方向的热爱科研的学生加入课题组!    

  • -主要面向 智能控制、人工智能、电子信息、计算机、机械电子、车辆工程等相关专业的学生招收控制、电子信息、计算机等专业硕士生

  • -报考方式:保送生、公考生

  • -招生专业: 控制科学与工程,电子信息,模式识别与智能系统,计算机应用技术,电子科学与技术(联陪项目)


论文与著作

JOURNAL PAPERS
  1. Hu, Y., Xu, H., Jiang, Z., Zheng, X., Zhang, J., Fan, W., ... & Xu, K. (2023). Supplementary Learning Control for Energy Management Strategy of Hybrid Electric Vehicles at Scale. IEEE Transactions on Vehicular Technology.

  2. Zheng, C., Li, W., Li, W., Xu, K., Peng, L., & Cha, S. W. (2022). A deep reinforcement learning-based energy management strategy for fuel cell hybrid buses. International Journal of Precision Engineering and Manufacturing-Green Technology9(3), 885-897.

  3. Li, W., Li, H., Xu, K., Huang, Z., Li, K., & Du, H. (2021). Estimation of vehicle dynamic parameters based on the two-stage estimation method. Sensors21(11), 3711.

  4. Li, W., Li, H., Huang, C., Xu, K., Sun, T., & Du, H. (2021, August). Observer-based coordinated control for blended braking system with actuator delay. In Actuators (Vol. 10, No. 8, p. 193). MDPI.

  5. Zahid T, Xu K, Li W M, Li C M, Li H Z. State of charge estimation for electric vehicle power battery using advanced machine learning algorithm under diversified drive cycles [J]. Energy, 2018, 162:871-882.

  6. Hu Y, Li W, Xu K, Zahid T, Qin F, Li C. Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning [J]. Applied Sciences-Basel, 2018, 8 (2), 187.

  7. Qin F, Xu G, Hu Y, Xu K, Li W. Stochastic Optimal Control of Parallel Hybrid Electric Vehicles [J]. Energies, 2017, 10(2): 214.

  8. Xu G, Xu K, Zheng C, Zhang X, Zahid T. Fully Electrified Regenerative Braking Control for Deep Energy Recovery and Maintaining Safety of Electric Vehicles [J]. IEEE Transactions on Vehicular Technology, 2016, 65(3): 1186-1198.

  9. Xu G, Xu K, Zheng C, Zahid T. Optimal Operation Point Detection Based on Force Transmitting Behavior for Wheel Slip Prevention of Electric Vehicles [J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(2): 481-490.

  10. Zheng C, Xu G, Xu K, Pan Z, Liang Q. An energy management approach of hybrid vehicles using traffic preview information for energy saving [J]. Energy Conversion and Management, 2015, 105: 462-470.

  11. Xu K, Xu G, Zheng C. Novel Determination of Wheel-Rail Adhesion Stability for Electric Locomotives [J]. International Journal of Precision Engineering and Manufacturing, 2015, 16(4): 653-660.

  12. Xu K, Xu G-Q, Zheng C-H. Analysis of torque transmitting behavior and wheel slip prevention control during regenerative braking for high speed EMU trains [J]. Acta Mechanica Sinica, 2016, 32(2): 244-251.

  13. Zahid T, Xu K, Li W. Machine learning an alternate technique to estimate the state of charge of energy storage devices [J]. Electronics Letters, 2017, 53(25): 1665-1666.

  14. Xu G, Xu K, Li W. Novel estimation of tyre-road friction coefficient and slip ratio using electrical parameters of traction motor for electric vehicles [J]. International Journal of Vehicle Autonomous Systems, 2013, 11(2/3): 261.

  15. Xu G, Li W, Xu K, Song Z. An Intelligent Regenerative Braking Strategy for Electric Vehicles [J]. Energies, 2011, 4(9): 1461-1477.

  16. 吕迪徐坤*, 李慧云,融合类人驾驶行为的无人驾驶深度强化学习方法[J]. 集成技术, 2020(5).

  17. 徐坤骆媛媛杨影,分布式电驱动车辆状态感知与控制研究综述[J]. 机械工程学报, 2019(22).

  18.  徐国卿王玉琴杨影, & 徐坤*. 复杂动态路面的电动轮附着状态识别与稳定控制策略研究机械工程学报, 55(22),2019

  19. 张艳辉, 徐坤, 郑春花, 冯伟, 徐国卿. 智能电动汽车信息感知技术研究进展,仪器仪表学报 [J]. 2017, 38 (04): 794-805.

  20. 杨家红, 刘元元, 单晋婷, 徐坤, 陈越立. 应用融合框架的压缩感知信号重构方法,小型微型计算机系统 [J]. 2014, 35(08): 1885-1890.

  21. 徐国卿, 徐坤, 张琦, 郑春花, 梁嘉宁, 周翊民. 论电动汽车的发展趋势(英文) ,集成技术 [J]. 2014, 3(01): 1-17.

  22. 徐国卿, 徐坤, 李卫民. 电动汽车动力学控制研究进展,集成技术 [J]. 2012, 1(01): 6-14.

CONFERENCE PAPERS:
  1. Deng Y, Xu K, Hu Y, et al. Learning Effectively from Intervention for Visual-based Autonomous Driving[C]//2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2022: 01-06.

  2. Liu D, Xu K, Cui Y, et al. Learning-based Motion Control of Autonomous Vehicles Considering Varying Adhesion Road Surfaces[C]//2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2022: 4259-4264.

  3. Xu K, Huang Z, Xu G. Regenerative Braking with Direct Adhesion Control for Distributed Drive Electric Vehicles[C]//2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021: 1664-1669.

  4. Xiao, W. , J Zou, Li, H. , & Xu, K*. . (2019). Smooth Trajectory Tracking Using Longitudinal Distance Constraint for A 4WS4WD Unmanned Ground Vehicle *. 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE.

  5. Sun, H. , Li, H. , Li, Y. , Song, Z. , & Xu, K*. . (2019). Accelerating the Validation of Motion Control for a 4WD4WS Ground Vehicle Using a Hierarchical Controller Hardware-in-the-loop System. 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE.

  6. Xu K, Xu G, Zheng C, et al. A novel adhesion stability detection methodology and slip prevention control strategies for wheeled ground vehicles [C], IEEE International Conference on Robotics & Biomimetics. IEEE, 2015.

  7. Zhou Y, Xu G, Qin F, Xu K, Wang G, Ou Y, Lin G, Zhang Q. The prospect of smart cars: Intelligent structure and human-machine interaction [C]. Proceedings of the 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2013: 1899-1904.

  8.  Chen J, Xu G, Xu K, Li W. Traction control for electric vehicles: A novel control scheme [C]. Proceedings of the 2012 IEEE International Conference on Information and Automation, 2012: 367-372.

  9. Kun X, Guoqing X, Weimin L, Linni J, Zhibin S. Anti-skid for Electric Vehicles based on sliding mode control with novel structure [C]. Proceedings of the 2011 IEEE International Conference on Information and Automation, 2011: 650-655.

  10. Qian H, Xu G, Yan J, Lam T L, Xu Y, Xu K, Energy Management for Four-Wheel Independent Driving Vehicle [M]. IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems. 2010: 5532-5537.

学术著作:
  1. 电动汽车—能量转换与动力控制, 科学出版社, 2016



专利与获奖

授权中国发明专利:
  1. 一种融合类人驾驶行为的无人驾驶深度强化学习方法, ZL202010548665.1

  2. 一种数据驱动的电驱动车辆附着稳定识别方法及装置, ZL201911260714.5

  3. 利用前车信息的智能电驱动车辆再生制动控制方法, ZL202111510360.2

  4. 一种四轮独立转向-独立驱动车辆轨迹跟踪方法和系统,ZL201911134776.1

  5. 一种判断牵引状态下的车辆工作状态的方法和系统,ZL201410783813.2

  6. 一种湿地行驶作业装置的行驶控制方法, ZL201711309627.5

  7. 一种总线可靠性测试方法及系统,ZL201310593926.1

  8. 一种电动汽车路面自适应转矩控制系统,ZL201010237762.5

  9. 一种电动汽车的滑移率检测方法及检测系统,ZL201010562956.2

  10. 汽车能量控制方法、装置及终端设备,ZL201711372559.7

  11. 牵引力控制检测系统,ZL201310598152.1

授权美国专利:
  1. Slip rate detection method and detection system for electric vehicle,US13/990125

学术荣誉奖项:
  1. 中国仪器仪表学会科学技术奖一等奖, 一等奖,2015
  2. IEEE ICIA 2012 最佳自动化论文奖,2012

科研活动

持续致力于智能无人系统与新能源领域的先进感知与智能控制研究。与团队研究提出了面向安全和节能的电动车辆环境和道路附着感知、运动控制方法和系统,开发了同构/异构(无人机-无人车)多无人系统定位与联合建图导航系统,分布式独立驱动独立转向运动控制系统,自重构拼接式协同UGV,无人车-无人机协同自主增强方法,新能源汽车纯电/混合动力整车控制系统、电池管理系统、两档自动变速控制系统、移动搜救机器人控制系统等多个先进控制系统。是IEEE会员、中国自动化学会会员、深圳市人工智能学会会员,已在各种期刊和会议上发表SCI/EI论文40多篇,其中包括IEEE-TVT、IEEE-TITS、Energy等一作或通讯的JCR一区期刊。合作出版专著两部(章)。获美国专利授权1项,中国发明专利授权11项,软件著作权3项,部分成果已实现产业化。主持国家自然科学基金(NSFC)基金两项,主持深圳市基础研究重点项目两项,主持企业横向研发课题多项;参与国家重点研发计划、中科院知识创新工程重大及重要项目、NSFC等十多项。曾获得中国仪器仪表学会科学技术奖、IEEE 国际学术会议最佳论文奖等。担任多个国际学术期刊和会议的审稿人。

邮箱: kun.xu@siat.ac.cn