汽车速度预测（短期/长期/全工况）、驾驶工况/风格识别、电池-超级电容混合储能电动汽车、混合动力汽车、燃料电池汽车的参数配置、功率分配与优化控制

[J12] Fei Li, Mingjie Li, Yue Wu*(武悦), Heng Li, Yundong Song, Zhiwu Huang. Safe reinforcement learning energy management for hybrid electric vehicles: A supervisory action assessment and correction approach. Journal of Clearner Production, 2026, 544, 147720.（https://doi.org/10.1016/j.jclepro.2026.147720, 基于监督学习（XGBoost）的安全强化学习能量管理策略）

[J11] Kaifu Guan, Zhiwu Huang, Yang Gao, Yue Wu*(武悦), Fei Li, Heng Li. Towards adaptive deep reinforcement learning energy management for electric vehicles: An online updating approach. Energy, 2025, 325, 135996.（https://doi.org/10.1016/j.energy.2025.135996, 基于詹森香农散度的能量管理策略自适应软更新机制）

[J10] Kaifu Guan, Zhiwu Huang, Taozhen Chang, Yue Wu*(武悦), Fei Li, Heng Li. Hierarchical sizing optimization for electric racing cars with hybrid energy storage system. Journal of Energy Storage, 2025, 140, 119041.（https://doi.org/10.1016/j.est.2025.119041, 面向电动赛车完赛时间最小化的混合储能系统最优参数配置）

[J9] Weirong Liu, Pengfei Yao, Yue Wu*(武悦), Lijun Duan, Heng Li, Jun Peng. Imitation reinforcement learning energy management for electric vehicles with hybrid energy storage system. Applied Energy, 2025, 378, 124832.（https://doi.org/10.1016/j.apenergy.2024.124832, 基于生成对抗模仿学习-深度强化学习动态结合的能量管理策略）

[J8] Fei Li, Yang Gao, Yue Wu*(武悦), Yaoxin Xia, Chenglong Wang, Jiajian Hu, Zhiwu Huang. Incentive learning-based energy management for hybrid energy storage system in electric vehicles. Energy Conversion and Management, 2023, 293, 117480.（https://doi.org/10.1016/j.enconman.2023.117480, 基于激励强化学习的能量管理策略）

[J7] Yulin Zhang, Yue Wu*(武悦), Wei He, Yang Gao, Hui Peng, Heng Li. Multi-Objective Optimization of Vehicle Following Control for Connected Electric Vehicles based on Deep Deterministic Policy Gradient. SAE International Journal of Electrified Vehicles, 2023, 13(1), 79-91.（https://doi.org/10.4271/14-13-01-0005, 基于DDPG的电动汽车多目标跟驰优化控制）

[J6] Kai Gao, Pan Luo, Jin Xie, Bin Chen, Yue Wu*(武悦), Ronghua Du. Energy management of plug-in hybrid electric vehicles based on speed prediction fused driving intention and LIDAR. Energy, 2023, 284, 128535. （https://doi.org/10.1016/j.energy.2023.128535, 考虑雷达预测信息和驾驶意图的PHEV能量管理）

[J5]  Yue Wu (武悦), Zhiwu Huang, Rui Zhang, Pei Huang, Yang Gao, Heng Li, Yongjie Liu*, Jun Peng. Driving style-aware energy management for battery/supercapacitor electric vehicles using deep reinforcement learning. Journal of Energy Storage, 2023, 73, 109199. （https://doi.org/10.1016/j.est.2023.109199, 半监督学习驾驶风格感知的深度强化学习能量管理策略）

[J4] Yue Wu (武悦), Zhiwu Huang, Yusheng Zheng, Yongjie Liu, Heng Li*, Yunhong Che*, Jun Peng, Remus Teodorescu. Spatial-temporal data-driven full driving cycle prediction for optimal energy management in battery/supercapacitor electric vehicles. Energy Conversion and Management, 2023, 277, 116619. （https://doi.org/10.1016/j.enconman.2022.116619, 基于实车通勤数据的两阶段全工况速度预测及多尺度模型预测控制能量管理 ）

[J3] Yue Wu (武悦), Zhiwu Huang, Heath Hofmann, Yongjie Liu, Jiahao Huang, Xiaosong Hu, Jun Peng*, Ziyou Song*. Hierarchical Predictive Control for Electric Vehicles with Hybrid Energy Storage System under Vehicle-Following Scenarios. Energy, 2022, 251, 123774.（https://doi.org/10.1016/j.energy.2022.123774, 混合储能电动汽车跟驰场景的车速-能量管理分层优化）

[J2] Jiahao Huang, Zhiwu Huang, Yue Wu (武悦), Yongjie Liu, Heng Li, Fu Jiang*, Jun Peng. Sizing optimization research considering mass effect of hybrid energy storage system in electric vehicles. Journal of Energy Storage, 2022, 48, 103892.（https://doi.org/10.1016/j.est.2021.103892, ）

[J1] Yue Wu (武悦), Zhiwu Huang, Hongtao Liao, Bin Chen, Xiaoyong Zhang*, Yanhui Zhou, Yongjie Liu, Heng Li, Jun Peng. Adaptive power allocation using artificial potential field with compensator for hybrid energy storage systems in electric vehicles. Applied Energy, 2020, 257, 113983.（https://doi.org/10.1016/j.apenergy.2019.113983, 基于人工势场和前馈补偿的自适应分频能量管理策略）