Kang Li


Kang Li

Title:Chair of Smart   Energy Systems

School of   Electronic and Electrical Engineering

Research   directions:development of   advanced control and artificial intelligence technologies in the energy field


office phone:+44 (0)113   3432045


Professor Kang Li received DSc degree from Queen’s University Belfast in 2015, and PhD Degree in Control Theory and Applications from Shanghai Jiaotong University in 1995. Between 1995 and 2002, he worked at Shanghai Jiaotong University, Delft University of Technology and Queen’s University Belfast as a research fellow. From 2002 to 2018, he was a Lecturer, Senior Lecturer (2007), Reader (2009) and Professor (2011) with the School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast. Professor Li currently holds the Chair of Smart Energy Systems at the School of Electronic and Electrical Engineering, University of Leeds.

Prof Li’s research interest lies on the development of advanced control and artificial intelligence technologies in the energy field, contributing to the national and global effort for future 100% clean energy transition. He has made original contributions in the areas of control, artificial neural networks, energy storage, smart grid, and multivector energy systems. His work on the development of minimal-invasive low-cost cloud-based energy monitoring and analytic platform (Point Energy Technology) has been successfully used in different industrial sectors, winning InstMC ICI prize 2015, INVENT 2016 award, and finalist of Sustainable Energy Awards 2016 from Sustainable Energy Authority of Ireland. His research has been funded by research councils (EP/R030243/1, EP/P004636/1, EP/L001063/1, EP/G059489/1, EP/G042594/1, EP/F021070/1, EP/C004884/1, GR/S85191/01), industry and other resources, totalling over £7M. He has published over 160 international journal papers and edited 17 international conference proceedings in his area and has won over 10 national and international prizes and awards. He has engaged in international collaborations on energy research funded by EPSRC, Royal Society, Royal Academy of Engineering, BEIS, and British Council, winning Springer Nature ‘China New Development Award’ in recognition of the ‘exceptional contributions to the delivery of the UN Sustainable Development Goals’ in 2019. Prof Li chairs the IEEE UK and Ireland Control and Communication (Ireland) Joint Chapter, was the secretary of IEEE UK and Ireland Section (2008-2011). He is an executive editor of Transactions of Institute of Measurement and Control, Associate Editor of IFAC Journal Control Engineering Practice, Neurocomputing, Cognitive Computation, and a few other journals. He was the co-chair of ICSEE and LSMS conference series, committee chair or co-chair of over 20 conferences and workshops and has been invited to give over 70 plenaries and seminars worldwide.


1. Li Zhang, Kang Li, Dajun Du, Yuanjun Guo, Minrui Fei, Zhile Yang. ‘A sparse learning machine for real-time SOC estimation of Li-ion batteries’, IEEE Access, accepted 29 July 2020

2. Bruno Rente, Matthias Fabian, Miodrag Vidakovic, Xuan Liu, Xiang Li, Kang Li, Tong Sun, and Kenneth T. V. Grattan, ‘Lithium-Ion battery state-of-charge estimator based on FBG-based strain sensor and employing machine learning’, IEEE Sensors Journal, accepted 14 August 2020, 10.1109/JSEN.2020.3016080.

3. Jun Cao, Dan Harrold, Zhong Fan, Thomas Morstyn, David Healey, and Kang Li, Deep Reinforcement Learning Based Energy Storage Arbitrage With Accurate Lithium-ion Battery Degradation Model, accepted by IEEE Transactions on Smart Grid, accepted 03/04/2020.

4. Shawn Li, Kang Li, Evan Xiao, Chi Kong Wong, ‘Joint SoC and SoH Estimation for Zinc-Nickel Single Flow Batteries’, IEEE Transactions on Industrial Electronics, DOI: 10.1109/TIE.2019.2949534, 2019.

5. Yanxia Wang, Kang Li*, Shaojun Gan, and Che Cameron. ‘Missing Data Imputation with OLS-based Autoencoder for Intelligent Manufacturing’. IEEE Transactions on Industry Applications, Accepted 16 August 2019, 10.1109/TIA.2019.2940585, 55 (6), 7219-7229, 2019.

6. Huifeng Zhang, Dong Yue, Chunxia Dou, Kang Li, Xiangpeng Xie. ‘Event-Triggered Multiagent Optimization for Two-Layered Model of Hybrid Energy System With Price Bidding-Based Demand Response’. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 10.1109/TCYB.2019.2931706, 2019.

7. Huifeng Zhang, Dong Yue, Wenbin Yue, Kang Li, Mingjia Yin. ‘MOEA/D based probabilistic PBI approach for risk-based optimal operation of hybrid energy systems with intermittent power uncertainty’. IEEE Transactions on Systems, Man, and Cybernetics: Systems, accepted on July 19, 2019. 10.1109/TSMC.2019.2931636.

8. Dongsheng Yang, Yongheng Pang, Bowen Zhou, Kang Li. ‘Fault Diagnosis for Energy Internet Using Correlation Processing Based Convolutional Neural Networks’. IEEE Transactions on Systems, Man, and Cybernetics: Systems, accepted on May 25, 2019. Volume: 49, Issue:8, Page(s): 1739-1748, 2019.

9. Yajie Yu ; Hui Cao ; Zhuzhu Wang ; Yuqiao Li ; Kang Li ; Shengquan Xie, ‘Texture-and-Shape Based Active Contour Model for Insulator Segmentation’, IEEE Access, Vol.7, 78706 – 78714, June 2019.

10. Kailong Liu, Changfu Zou, Kang Li, Torsten Wik, Charging Pattern Optimization for Lithium-Ion Batteries with An Electrothermal-Aging Model, IEEE Transactions on Industrial Informatics, Vol. 14, No. 2, 5463 – 5474, 2018.

11. Juan Yan, Kang Li, Erwei Bai, Xiaodong Zhao, Yusheng Xue, Aoife Foley, ‘Analytical Iterative Multi-Step Interval Forecasts of Wind Generation Based on TLGP’, IEEE Transactions on Sustainable Energy, Volume: 10 , Issue: 2 , April 2019 , Page(s): 625 - 636

12. Shaojun Gan, Shan Liang, Kang Li, Jing Deng, Tingli Cheng, ‘Trajectory length prediction for intelligent traffic signalling: a data driven approach,’ IEEE Transactions on Intelligent Transportation Systems, Vol. 19, No. 2, 426 – 435, 2017. DOI: 10.1109/TITS.2017.2700209.

13. Cheng Zhang, Kang Li, Jing Deng, Shiji Song, ‘Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model’, IEEE Transactions on Industrial Electronics, Vol 64, No. 1, pp 654-663, 2017, DOI: 10.1109/TIE.2016.2610398.

14. Dajun Du, Rui Chen, Minrui Fei and Kang Li, ‘A novel networked online recursive identification method for multivariable systems with incomplete measurement information’. IEEE Transactions on Signal and Information Processing over Networks, Vol. 3, No. 4, 2017, pp. 744 – 759. DOI: 10.1109/TSIPN.2017.2662621.

15. Xiandong Xu, Kang Li, Hongjie Jia, Xiaodan Yu, Jing Deng, Yunfei Mu, ‘Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines.’ IEEE Transactions on Smart Grid, 2016, 2016, 9(2): 1387 – 1396.

16. Shaojun Gan, Shan Liang, Kang Li, Jing Deng, Tingli Cheng, ‘Long-term ship speed prediction for intelligent traffic signalling’, IEEE Transactions on Intelligent Transportation Systems, Vol. 18, No. 1, pp. 82-91, 2016.

17. Juan Yan, Kang Li, Erwei Bai, Jing Deng, Aoife Foley, ‘Hybrid Probabilistic Wind Power Forecasting Using Temporally Local Gaussian Process’, IEEE Transactions on Sustainable Energy, Vol 7, No. 1, pp. 87-95, 2016. 10.1109/TSTE.2015.2472963.

18. Yuanjun Guo, Kang Li, David Laverty, Yusheng Xue, ‘Synchrophasor-Based Islanding Detection for Distributed Generation Systems Using Systematic Principal Component Analysis Approaches’. IEEE Transactions on Power Delivery, Vol. 30, No. 6, pp. 2544-2552, 2015. 10.1109/TPWRD.2015.2435158

19. X. Liu, D.M. Laverty, R.J. Best, Kang Li, D.J. Morrow, S. McLoone, ‘Principal Component Analysis of Wide Area Phasor Measurements for Islanding Detection – A Geometric View’, IEEE Transactions on Power Delivery, Vol. 30, No. 2, pp. 976-985, 2015.


20. Wenxiao Zhao, Han-Fu Chen, Er-Wei Bai, and Kang Li, ‘Kernel-Based Local Order Estimation of Nonlinear Nonparametric Systems’, Automatica, Vol. 51, 2015, pp 243–254.

21. Long Zhang, Kang Li, Forward and backward Least Angle Regression’, Automatica, 2015, Vol.53, pp. 94–102.

22. Y. Li, K. Li, X. Liu, Y. Wang, L. Zhang, ‘Lithium-ion battery capacity estimation—A pruned convolutional neural network approach assisted with transfer learning’, Applied Energy, Vol. 285, 116410, 2021.

23. Y. Li, K. Li, X. Liu, L. Zhang, ‘Fast battery capacity estimation using convolutional neural networks’, Transactions of Institute of Measurement and Control, 2020, 10.1177/0142331220966425.

24. K Liu, Z Wei, Z Yang, K Li, ‘Mass load prediction for lithium-ion battery electrode clean production: a machine learning approach’, Journal of Cleaner Production, 125159, 2020.

25. L Zhang, M Zheng, D Du, Y Li, M Fei, Y Guo, K Li. ‘State-of-Charge Estimation of Lithium-Ion Battery Pack Based on Improved RBF Neural Networks’, Complexity, 2020

26. Peiliang Sun, Kang Li, Yongfei Li, Li Zhang, ‘DC Voltage Control for MMC based Railway Power Supply Integrated with Renewable Generation’, accepted by IET Renewable Power Generation, 2020.

27. Yongfei Li, Kang Li, Li Zhang, Yong Li, ‘A Novel Double-layer DC/AC Railway Power Supply System with Renewable Integration’, accepted by IET Renewable Power Generation, 2020.

28. Chen Xing, Kang Li, Li Zhang, Wei Li, ‘Optimal Compensation Control of Railway Co-phase Traction Power Supply Integrated with Renewable Energy Based on NSGA-II’, accepted IET Renewable Power Generation, 26 Auguust, 2020.

29. Mingjia Yin, Kang Li, A Review on Artificial Intelligence in High-Speed Rail, acceped Transportation Safety and Environment, April 2020.

30. Peiliang Sun, Kang Li, Chen Xing, Wei Li, ‘A Partial Compensation Scheme for MMC-based Railway Cophase Power Supply’, Transportation Safety and Environment., 2 (4), 305-317, 2020.

31. Xuan Liu, Kang Li, ‘Energy Storage Devices in Electrified Railway Systems - A Review’, Transportation Safety and Environment, accepted on 3 June 2020.

32. Changqing Liu, Kang Li, Xuan Liu, Youqing Wang, ‘Distributed unknown input and state estimation for nonlinear multi-agent systems with applications to battery management’. CSEE Journal of Power and Energy Systems, accepted 15 May 2020.

33. Shawn Li, Kang Li, Evan Xiao, Jianhua Zhang, Min Zheng, ‘Real-time peak power prediction for zinc nickel single

flow batteries’, Journal of Power Sources, 448, 227346, accepted 22 October 2019, doi.org/10.1016/j.jpowsour.2019.227346.

34. Shawn Li, Kang Li, Evan Xiao, Jianhua Zhang, Peter Fischer, Rui Xiong, ‘A Novel Model Predictive Control Scheme Based Observer for Working Conditions and Reconditioning Monitoring of Zinc-Nickel Single Flow Batteries’, Journal of Power Sources, Acceped on 8 Oct 2019. Vol. 445, 1 January 2020, 227282.

35. Yanxia Wang, Kang Li, Shaojun Gan, Che Cameron, ‘Analysis of energy saving potentials in intelligent manufacturing: A case study of bakery plants’, Energy, Vol. 172, 2019, pp 477-486.

36. Zhile Yang, Kang Li, Yuanjun Guo, Shengzhong Feng, Qun Niu, Yusheng Xue, Aoife Foley, ‘A binary symmetric based hybrid meta-heuristic method for solving mixed integer unit commitment problem integrating with significant plug-in electric vehicles’, Energy, 2019, Vol. 170, 2019, Pp 889-905.

37. Zhile Yang; Kang Li; Yuanjun Guo; Haiping Ma; Min Zheng, “Compact Real-valued Teaching-Learning Based Optimization with the Applications to Neural Network Training”, Knowledge-Based Systems, Vol. 159, 1 November 2018, Pp. 51-62, https://doi.org/10.1016/j.knosys.2018.06.004.

38. Juai WU, Yusheng XUE, Dongliang XIE, Kang LI, Fushuan WEN, Junhua ZHAO, Guangya YANG, Qiuwei WU. ‘Multi-agent modeling and analysis of EV users’ travel willingness based on an integrated causal/statistical/behavioral model’, Journal of Modern Power Systems and Clean Energy, Vol. 6, No. 6, pp 1255–1263, https://doi.org/10.1007/s40565-018-0408-2.

39. C Jiang, Yusheng XUE, J Huang, Feng XUE, Fushuan WEN, Kang LI, Guangya YANG, Qiuwei WU. ‘Aggregated impact of allowance allocation and power dispatching on emission reduction’, Journal of Modern Power Systems and Clean Energy, 2017, 5 (6), 936-946.

40. L. Li, Y. Liu, Z. Yang, X. Yang, K. Li, ‘A mean-square error constrained approach to robust stochastic iterative learning control, IET Control Theory & Applications, Vol. 12, No. 1, pp 38-44, 2018.


1) 2019-2023, High Speed Rail Institute, CI of RPIF funding (£13M), 1 TRU project, 3 REAL Alliance projects, totalling £5.6M.

2) 2020, “Powering HGVs on England’s Future Electric Roads – Safety and Maintenance Assessment of Electrical Power Supply Systems”, funded by Highway England Ltd (RG.ELEC.122933), £86,949+vat, as PI.

3) 2019, £115,200, “A holistic approach for power system monitoring to support DSO transition”, funded by Scottish Power Transmission Ltd, as PI, RG.ELEC.120539.

4) 2019, £18,000, ‘UK-China Innovation and knowledge Exploitation Forum’, funded by Global Partnership Fund, UK Science & Innovation Network, FCO, as PI.

5) 05.2018-04.2021, EPSRC GCRF project EP/R030243/1, ‘Creating Resilient Sustainable Microgrids through Hybrid Renewable Energy Systems’, £1,259,750, as CI.

6) 2018, £7,000, ‘UK-China knowledge consortium on energy and manufacturing’, funded by Global Partnership Fund, UK Science & Innovation Network, FCO, as PI.

7) 2017-2020, PhD studentship with Wrightbus, QUB William Wright Technology Centre, project title: ‘Advanced battery management technologies for heavy duty vehicle applications’, as PI, £90K.

8) 2017, FUSION Programme, All-Island Knowledge Transfer Initiative, in collaboration with Aubren Ltd for developing modern control systems, £23,250, as PI, project code: FU5054.

9) 2017.2-2021.2, “UK Consortium for the collaboration with Chinese Excellence League (E9) Group of Universities”, UK-China Knowledge Economy Education Partnership, Department of Business, Energy & Industrial Strategy, British Council, £700,000, as lead applicant and project CI. P-CHN-180053

10) 10/2016-02/2017, EPSRC Impact Acceleration Fund, £9.95K, ‘Energy Monitoring Device’, as PI.

11) 10/2016-03/2017, EPSRC Global Challenge Research Fund (GCRF) Award, £20K, ‘A holistic approach for shaping low carbon energy future in collaboration with China’, as PI.

12) 12/2016- 05/2021, EPSRC (EP/P004636/1), £1.64M (FEC 2.03M), ‘Optimising energy management in industry (‘OPTEMIN2’)’, as QUB PI.

13) 2016, £6,000 (GPF-15), ‘Shaping low carbon energy future’, funded by Global Partnership Fund, UK Science & Innovation Network, as PI.

14) 2016, £20,800, ‘Shaping low carbon energy future’, funded by Department of Business, Innovation and Skills, British Council, and Newton Fund under the Newton Researcher Links Workshop Grants Scheme (ID: 227218661, NSFC: 5151101499), as PI.

15) 2015, £35,000, ICURe Innovation to Commercialisation (514603902), funded by HEFCE and Innovate UK, ‘Point Energy’, as PI.

16) 03/2015-03/2017, £12,000, International Exchange and Newton Fund (IE141469) and NSFC jointly funded project, “Intelligent Control for Full Range Exhaust Waste Heat Recovery of IC Engines”, Royal Society, as PI.

17) 2015, £5,896, Distinguished Visiting Fellowship (DVF1415/2/59), “Decarbonizing the whole energy system from head to tail - a smart micro-grid solution”, Royal Academy of Engineering, as PI.

18) 2014, £160K, CRIF (Central Research Infrastructure Fund), Queen’s University Belfast. Establishment of a joint laboratory on electric vehicles and smart grid. Kang Li (PI).

19) Dec 2013- July 2017, EPSRC (EP/L001063/1), £855,111 (FEC £1.07M), Intelligent Grid Interfaced Vehicle Eco-charging (iGIVE), as PI, in collaboration with Harbin Institute of Technology.

20) April 2013- March 2015, £103,686, Proof of Concept (POC 333), Integrating energy efficiency monitoring, control and optimization for plastics industry. Invest Northern Ireland, as PI.

21) Dec 2012- Nov 2014, £125,787, Knowledge Transfer Partnerships, Technology Strategy Board, ‘To embed in-house electronic software and hardware capability’, with Munster Simms Engineering Ltd. Ref: KTP008909, as PI, Offered at 28 May 2012.

22) 2011, £4.4K, Distinguished Visiting Fellowship, “Advanced process control techniques for sustainable development for energy intensive processes,” Royal Academy of Engineering, as PI.

23) Sept 2009- August 2012, totalling £2.3 million, including £860K from EPSRC/RCUK (EP/G042594/1), “UK-China Bridge in Sustainable Energy and Built Environment (UC-SEBE)”, as CI and project coordinator.

24) 2008-2011, £269,336, EPSRC (EP/F021070/1), “An integrated system of inferential measurement and control of polymer extrusion for self-tuning optimisation and response to disturbances”, as PI.

25) March 2010- March 2013, £424,868, EPSRC (EP/G059489/1), “Thermal Management in Polymer Processing”, as CI.

26) 2010, £8,000, British Council, Prime Minister Initiative (PMI2), “International mobility of UK students’, K Li*, as PI.

27) 2009, £4.5K, Distinguished Visiting Fellowship, “Computational intelligence in control for sustainable development,” Royal Academy of Engineering, as PI.

28) 2009. £4.5K, Knowledge acquisition visit to leading universities and industrial company in China and to attend International Conference on Natural Computation. As PI..

29) 2007- 2010, £87,800, EPSRC (Engineering and Physical Sciences Research Council), Q Zhong*, A Zolotas, K Li, D Coca, and S Evangelou, “New-ACE: A Network for New Academics in Control Engineering”, as Collaborator and Core member.

30) 2008-2011, RBM 250K, Shanghai Municipal Science and Technology Commission, M Fei, G. Irwin and K Li, “Research on optimization and networked control of large-scale fossil-fuel power generation plants for energy efficiency”, as CI.