[1]Li P*, Wu X, Grosu R, et al. Applying neural network to health estimation and lifetime prediction of lithium-Ion batteries [J]. IEEE Transactions on Transportation Electrification, 2025, 11(1): 4224-4248. (25 页长文 中科院 SCI 一区 TOP 期刊, IF=7.2) [2]Li P*, Zhang Z, Grosu R, et al. An end-to-end neural network framework for state-of-health estimation and remaining useful life prediction of electric vehicle lithium batteries[J]. Renewable and Sustainable Energy Reviews, 2022, 156: 111843. (ESI 前 1%高被引, 中科院 SCI 一区 TOP 期 刊,IF=15.9) [3]Li P*, Zhang Z, Xiong Q, et al. State-of-health estimation and remaining useful life prediction for the lithium-ion battery based on a variant long short term memory neural network[J]. Journal of power sources, 2020, 459: 228069. (ESI 前 1%高被引, 中科院 SCI 一区 TOP 期刊,IF=9.2) [4]Hou J, Su H, Li P*, et al. Bias-correction errors-in-variables Hammerstein model identification[J]. IEEE Transactions on Industrial Electronics, 2022, 70(7): 7268-7279. (ESI 前 1%高被引, 中科院 SCI 一区 TOP 期刊,IF=7.7) [5]Deng Z, Hu X, Li P*, et al. Data-driven battery state of health estimation based on random partial charging data[J]. IEEE Transactions on Power Electronics, 2021, 37(5): 5021-5031. (ESI 前 1%高被引, 中科院 SCI 一区 TOP 期刊,IF=6.7) [6]Gu X, See K W, Li P*, et al. A novel state-of-health estimation for the lithium-ion battery using a convolutional neural network and transformer model[J]. Energy, 2023, 262: 125501. (ESI 前 1%高被引, 中科院 SCI 一区 TOP 期刊,IF=9.0) [7]Hou J, Su H, Li P, et al. Consistent subspace identification of errors-in-variables Hammerstein systems[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 53(4): 2292-2303. (ESI 前 1%高被引, 中科院 SCI 一区 TOP 期刊,IF=8.7) [8]Li P*, Yang Y, Grosu R, et al. Driver distraction detection using octave-like convolutional neural network[J]. IEEE transactions on intelligent transportation systems, 2021, 23(7): 8823-8833. (中科院 SCI 一区 TOP 期刊,IF=8.5) [9]Li P, Liu J, Deng Z, et al. Increasing energy utilization of battery energy storage via active multivariable fusion-driven balancing[J]. Energy, 2022, 243: 122772. (中科院 SCI 一区 TOP 期刊,IF=9.0) [10]Yang P, Deng W, Luo J, Li R, Li P*, et al. Preparation and structure optimization of 2D MXene nanocomposites for microwave absorbing application[J]. Materials Today Physics, 2023: 101291. (中科院 SCI 一区 TOP 期刊,IF=11.5) [11]Hou J, Liu J, Chen F, Li P*, et al. Robust lithium-ion state-of-charge and battery parameters joint estimation based on an enhanced adaptive unscented Kalman filter[J]. Energy, 2023, 271: 126998. (中科院 SCI 一区 TOP 期刊,IF=9.0) [12]Yang Z, Li M, Lu G, Wang Y, Wei J, Hu X, Li Z, Li P*, Xu C. High‐Performance Composite Lithium Anodes Enabled by Electronic/Ionic Dual‐Conductive Paths for Solid‐State Li Metal Batteries[J]. Small, 2022, 18(31): 2202911. (中科院 SCI 一区 TOP 期刊,IF=13.3) |
[1]李鹏华;程家伟;柴毅;程安宇;胡向东;侯杰;朱智勤;张亚鹏;董江林; 基于蒙特卡洛方法的锂电池异常工况数据自组增强方法;2023-10-20;中国; ZL 2020 1 0610473.9 [2]李鹏华;赵芬;朱智勤;袁宇鹏;李小飞;基于多任务学习的问答方法;中国;2022-10-14;中国;ZL 2019 1 0152570.5 [3]李鹏华;程艺;侯杰;陈丰伟;俞成浦;孙健;周桐;基于特征迁移学习的锂电池健康状况监测方法;2022-09-27;中国;ZL 2021 1 0801474.6 [4]李鹏华;刘佳;柴毅;胡向东;程安宇;利节;侯杰;朱智勤;张亚鹏;卢楠;基于可微连续映射的锂电池健康监测模型自学习方法;2022-08-09;中国;ZL 2020 1 0609011.5 [5]李鹏华;田鹏;刘行谋;陈旭赢;李祖栋;卢楠;王宁;鲁鑫高翔;一种通道注意力传播与聚合下的声纹识别方法,2022-07-15;中国;ZL 2021 1 0368665.8 [6]李鹏华;程家伟;刘行谋;张亚鹏;俞方舟;陈旭赢;乐磊;张恩浪;董江林;基于自适应掩膜和分组线性变换的轻量级语音识别方法;2022-05-13;中国;ZL 2021 1 0367779.0 [7]李鹏华;刘太林;朱智勤;李嫄源;朱庆元;一种面向中国移动智能客服的动态扩展知识图推理方法;2022-02-08;中国;ZL 2018 1 0049053.0 [8]李鹏华;张家昌;张子健;柴毅;熊庆宇;丁宝苍;魏善碧;一种基于AST-LSTM神经网络的锂电池 SOH估计与 RUL 预测方法,2021-11-19;中国;ZL 2019 1 1018344.4. [9]李鹏华;邵子璇;熊庆宇;丁宝苍;侯杰;朱智勤;张子健;胡和煦;一种归一化互信息准则约束的锂电池故障数据筛选方法;2021-07-23;中国; ZL 2019 1 0696529.4 [10]李鹏华;胡和煦;熊庆宇;朱智勤;侯杰;丁宝苍;张子健;张岸; 一种混合卷积神经网络驱动的锂电池多类故障诊断建模方法,2021-04-02;中国;ZL 2019 1 0695409.2 [11]李鹏华;刘太林;李嫄源;米怡;王欢;一种基于数据库与神经网络的车机自然语言人机交互算法,2021-03-23;中国;ZL 2017 1 0874715.3 [12]李鹏华,米怡,王欢,秦石磊,基于状态跟踪与策略导向下的移动客服对话管理方法;2020-05-26;中国;ZL 2018 1 0055021.1 [13]李鹏华;赵芬;李嫄源;朱智勤;刘太林;基于自然语言处理的林业生态环境人机交互方法;2019-04-26;中国; ZL 2017 1 1408324.9 [14]李鹏华;王欢;李嫄源;朱智勤;张家昌;一种基于相关冗余变换与增强学习的多维度协同控制方法,2019-04-09;中国;ZL 2017 1 1407168.4 [15]李鹏华;刘晶晶;冯辉宗,赵芬; 一种基于数据驱动的三元催化器的故障诊断方法;2018-07-17;中国;ZL2016 1 0864280.X. [16]李鹏华;李银国;柴毅;岑明;李永福;邱翊峰;周思;采用量子 Hopfield 神经网络的模拟电路多故障智能诊断方法;2015-04-22;中国;ZL 2012 1 0569235.3. [17]杨奕枫;李鹏华;李嫄源;胡向东;李锐;朱智勤;侯杰;基于轻量级类八维卷积神经网络的驾驶分心识别方法;2022-07-01;中国; ZL202010752388.6 [18]张子健,李鹏华;胡晓松,柴毅;熊庆宇;胡向东;陈立平;侯杰; 一种锂电池 SOH 估算和 RUL 预测的端到端神经网络建立方法;2023-11-03;中国; ZL2020 10967389.2 |