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

       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）等

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 Technology, 9(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. Sensors, 21(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,等. 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,等. 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

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

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