林名强，正高级工程师，博导，中国科学技术大学控制科学与工程专业博士。入选福建省高层次人才-B类、泉州市高层次人才-第二层次、海西研究院春苗青年人才等。从事电池系统智能管理与优化控制研究，主持国家自然科学基金、国家工信部、福建省科技计划、泉州市科技计划及企业横向等10余项课题，累计主持经费超一千万元，发表创新论文40余篇（其中SCI一区20余篇、ESI高被引论文3篇、知网高被引论文1篇），申请发明专利10余件（第一发明人授权3件），参与福建省地方标准制定2项（已公布）。兼任IEEE高级会员、2023清华质量与可靠性年会分会主席、第八届动力与可再生能源专业委员会委员、第八届仿真技术应用专业委员会委员等。

1. M. Q. Lin#, D. C. Hu, J. H. Meng*, J. Wu, Transfer learning-based lithium-ion battery state of health estimation with electrochemical impedance spectroscopy, IEEE Transactions on Transportation Electrification, 2025, DOI: 10.1109/TTE.2025.3533540.

2. M. Q. Lin#, L. S. Ke, J. H. Meng*, W. Wang, J. Wu, F. X. Wang, Health Status Estimation of Lithium-ion Battery Under Arbitrary Charging Voltage Information Using Ensemble Learning Framework, Reliability Engineering and System Safety, 2025, 256, 110782.

3. M. Q. Lin#, S. X. Chen, J. H. Meng, W. Wang, J. Wu*, Instantaneous energy consumption estimation for electric buses with a multi-model fusion method, IEEE Transactions on Intelligent Transportation Systems, 2025, 26(1), 371-381.

4. Y. Q. You#, M. Q. Lin*, J. H. Meng, J. Wu, W. Wang, Multi-Scenario Surface Temperature Estimation in Lithium-Ion Batteries with Transfer Learning and LGT Augmentation, Energy, 2024, 304, 132065.

5. M. Q. Lin#, Jian Wu, J. Q. Zou, J. H. Meng, W. Wang, J. Wu*. Retired Battery Screening Based on Markov Transition Field and Swin Transformer, IEEE Transactions on Transportation Electrification, 2024,10(2), 4217-4227.

6. J. H. Ye#, Q. Xie, M. Q. Lin*, J. Wu, A method for estimating the state of health of lithium-ion batteries based on physics-informed neural network, Energy, 2024, 294, 130828.

7. M. Q. Lin#, Y. Q. You, J. H. Meng*, W. Wang, J. Wu. D. Stroe. Lithium-ion battery degradation trajectory early prediction with synthetic dataset and deep learning, Journal of Energy Chemistry, 2023, 85, 534-546.

8. M. Q. Lin#, C. H. Yan, W. Wang, G. Z. Dong, J. H. Meng*. J. Wu*, A data-driven approach for estimating state-of-health of lithium-ion batteries considering internal resistance, Energy, 2023, 277, 127675.

9. Ji Wu#, X. C. Cui, J. H. Meng, J. C. Peng, and M. Q. Lin*. Data-Driven Transfer-Stacking based State of Health Estimation for Lithium-Ion Batteries, IEEE Transactions on Industrial Electronics, 2024, 71(1), 604-614.

10. M. Q. Lin#, Jian Wu, J. H. Meng, W. Wang, and J. Wu*. State of health estimation with attentional long short-term memory network for lithium-ion batteries, Energy, 2023, 268, 126706.

11. M. Q. Lin#, D. G. Wu, J. H. Meng*, W. Wang, and J. Wu*. Health prognosis for lithium-ion battery with multi-feature optimization, Energy, 2023, 264, 126307.

12. M. Q. Lin#, Y. Q. You, W. Wang*, and J. Wu*. Battery health prognosis with gated recurrent unit neural networks and hidden Markov model considering uncertainty quantification, Reliability Engineering and System Safety, 2023, 230, 108978.

13. M. Q. Lin#, S. X. Chen, W. Wang, and J. Wu*. Multi-feature fusion-based instantaneous energy consumption estimation for electric buses, IEEE/CAA J. Autom. Sinica, 2023, 10(10), 2035–2037.

14. M. Q. Lin#, C. H. Yan, J. H. Meng, W. Wang, J. Wu*. Lithium-ion batteries health prognosis via differential thermal capacity with simulated annealing and support vector regression, Energy, 2022, 250, 123829.

15. J. Wu#, X. C. Cui, H. Zhang, and M. Q. Lin*. Health Prognosis with Optimized Feature Selection for Lithium-ion Battery in Electric Vehicle Applications, IEEE Transactions on Power Electronics, 2021, 36(11): 12646-12655.