主持：

[1] 国家自然科学基金面上项目：62473308，基于混合变中心广义相关熵及信息驱动的稳健高能效分布式估计研究 (2025/01-2028/12，在研)

[2] 西安市科技计划项目(高校人才服务企业项目）: 23GXFW0071，大容量储能系统能量控制管理关键技术研究(2023/07/01-2025/06/30，在研)

[3] 国家自然科学基金联合基金项目子课题：U21A20485, 云边端一体化服务机器人云脑平台基础理论与关键技术, (2022/01-2025/12，在研)

[4] 陕西省自然科学基础研究计划重点项目子项目：2019JZ-05，偏差补偿的稀疏互相关熵自适应滤波及其应用(2019/01-2021/12，结题)

[5] 陕西省教育厅重点科学研究计划重点实验室项目：20JS109，偏差补偿的扩散式稳健自适应滤波方法研究 (2020/01-2022/12, 结题)

[6] 2019西安市科技计划项目(高校人才服务企业项目):GXYD14.23， 大容量电动汽车用锂电池SOC估计关键技术研究(2019/06-2021/06，结题)

[7] 陕西省自然科学基础研究计划资助项目：2017JM6033，脉冲噪声干扰环境下稀疏系统辨识关键技术研究(2017/01-2018/12,结题)

部分期刊论文：

[1]   Wentao Ma*, Jiahui Dai, Yuzhuo Dong, Jiandong Duan，Badong Chen. Enhanced Short-term Wind Power Prediction via anInnovative Multi-task Learning Framework Integrated with Fusion Model based Data Cleansing. IEEETransactions on Instrumentation & Measurement, 2025, 74:9006217.

[2]   Wentao Ma*, Bo Wang, Zhenbing Zhao, Qian Wang, Badong Chen.A Small-Sized Defect Detection Method forPower Line Insulator Using Multiscale Feature and Lightweight Networks inUAV-Vision. IEEE Transactions on Power Delivery, 2025, 40(5):2747-2758. 

[3]  Wentao Ma*, Jingsong Xue, Peng Guo, Xinghua Liu, Zhongbao Wei, Yiwen Wang，Badong Chen. A Stable Lithium-ion Battery SOH Estimation Framework for Suppressing Unknown Measurement Noise Distribution. IEEE Transactions on Transportation Electrification, 2025, 11(4):10336-10353.

[4] Peng Guo, Wentao Ma*,Xinghua Liu, Zhongbao Wei, Badong Chen. Robust Online Model Parameter Identification and SOC Estimation for Li-ion Batteries Considering Noisy Measurement.  IEEE Transactions on Industrial Electronics, 2025,72(11):11897-11907.

[5]Peng Guo, Wentao Ma*, Xinghua Liu, Badong Chen.Robust SOC estimation of lithiumion battery combining gated recurrent unit and square root CKF with generalized correntropy. Energy, 2025,338：138851.

[6]  Wentao Ma*, Haoxuan Shi, Chenyu Wang, Badong Chen. Variational Bayesian Ensemble Kalman Filter with GeneralizedMixture Correntropy Loss Based Dynamic State Estimation for Doubly FedInduction Generator. Signal Processing . 2025, 230: 109838.

[7]  Wentao Ma*, Qi Yan, Peng Guo, Badong Chen.Robust State Estimation of Integrated Electric-heat System Based on Physics-guided Deep Learning with Maximum Correntropy Criterion.  IEEE Trans. Instrum. Meas, 2025, 74:9000412.

[8]  Wentao Ma*, Shizhuo Ren, Peng Guo. Review of state of power estimation for Li-Ion batteries: methods, issues, andprospects. Journal of Electrochemical Science and Technology, 2025, 16(1):15-36.

[9]  Wentao Ma*,Yiming Lei, Bo Yang, Peng Guo. A Multi-Mechanism Fusion Method for Robust State of ChargeEstimation via BiLSTM with MKMPE Considering Non-Gaussian Measurement Noises. Journal of The Electrochemical Society, 2024, 171(9): 090530.

[10]  Wentao Ma*, Bin Chen, Bo Wang, Badong Chen. Photovoltaic Panel Defect Detection via Multi-scale Siamese Convolutional Fusion Network with Information Bottleneck Theory.  IEEETrans. Instrum. Meas., 2024, 73:5030815.

[11]  Lihong Qiu, Wentao Ma*, Xiaoyang Feng, Jiahui Dai,Yuzhuo Dong, Jiandong Duan,Badong Chen. A hybrid PV cluster power prediction model using BLS with GMCC and error correction via RVM consideringan improved statistical upscaling technique. Applied Energy, 2024, 359:122719

[12]  Wentao Ma*, Chenyu Wang, Lujuan Dang, Xingyu Zhang, Badong Chen. Robust Dynamic State Estimation for DFIG Based on Generalized Maximum Correntropy Criterion Ensemble Kalman Filter.  IEEETrans. Instrum. Meas., 2023, 72: 1-13. 

[13]  Jingsong Xue,Wentao Ma*, Xiaoyang Feng, PengGuo, Yaosong Guo, Xianzhi Hu, Badong Chen. Stacking integrated learning model via ELM and GRU with mixture correntropy loss for robust state of health estimation of lithium-ion batteries. Energy,2023, 284:129279.

[14]  Peng Guo,WentaoMa*, Dele Yi, Xiaofei Wang,Lujuan Dang. Enhanced square root CKF withmixture Correntropy loss for robust state of charge estimation of Lithium-ionBattery.  Journal of Energy Storage, 2023, 73(Part A): 108920 

[15]  Wentao Ma*, Yiming Lei, Xiaofei Wang,Badong Chen. Robust State of Charge Estimation of Lithium-ion Battery viaMixture Kernel Mean p-Power Error Loss LSTM with Heap-Based-Optimizer. Journalof Energy Chemistry, 2023, 80:768-784.

[16]  Wentao Ma*, Xiao Kou, Junbo Zhao,Badong Chen. Extended Kernel Risk-Sensitive Loss Unscented Kalman Filter BasedRobust Dynamic State Estimation. International Journal of Electrical Powerand Energy Systems, 2022, 148:108898. 

[17]  Wentao Ma*,Panfei Cai, Fengyuan Sun, Xiaofei Wang, Junyu Gong. State of Health Estimation for Lithium-ion batteries Based on Extreme Learning Machine with Improved Blinex Loss. International Journal of electrochemical science, 2022, 17(11): 

[18]  Wentao Ma*, Peng Guo,Xiaofei Wang, Zhiyu Zhang, Siyuan Peng, Badong Chen. Robust state ofcharge estimation for Li-ion batteries based on cubature kalman filter with generalized maximum correntropy criterion. Energy, 2022, 260(1):125083. 

[19]  Wentao Ma*, Xiao Kou, Xianzhi Hu, Anxin Qi, Badong Chen. Recursive minimum kernel risk sensitive loss algorithmwith adaptive gain factor for robust power system harmonics estimation. Electricalpower system research, 2022, 206:107788. 

[20]  Wentao Ma*, Jinzhe Qiu, XinghuaLiu, Gaoxi Xiao, Jiandong Duan, Badong Chen. Unscented Kalman Filter withGeneralized Correntropy Loss for Robust Power System Forecasting-Aided State Estimation. IEEETransactions on Industrial Informatics, 2019, 15(11):6091-6100.

[21]  Wentao Ma*,Jinzhe Qiu, Zhiyu Zhang, Dongqiao Zheng, Badong Chen.Bias-compensatedaware adaptive filtering algorithms based three-phase power system frequency estimation with noisy input. IET Science Measurement & Technology, 2019, 13(7):1040-1058.

[22]  Wentao Ma*, Jinzhe Qiu, JunliLiang, Badong Chen. Linear Kalman Filtering Algorithm with Noisy Control input Variable. IEEETransactions on Circuits and Systems II:Express Briefs.2019,66(7), 1282-1286.

[23]  Wentao Ma*, Jiandong Duan, Jiuwen Cao, Yingsong Li, Badong Chen. Proportionate Adaptive Filtering Algorithms Based on Mixed Square Fourth error criterion with Unbiasedness Criterion for Sparse System Identification. International journal of adaptive control and signal processing.2018,32(11):1644-1654.

[24]  Wentao Ma*, Dongqiao Zheng, Yuanhao Li, Zhiyu Zhang, Badong Chen. Bias-Compensated Normalized Maximum Correntropy Criterion Algorithm for System Identification with Noisy Input. Signal processing.2018,152(11):160-164. 

[25]  Wentao Ma*, Dongqiao Zheng, Xiangqiang Tong,Zhiyu Zhang, Badong Chen. Proportionate NLMS with Unbiasedness Criterion for Sparse System Identification in the Presence of Input and Output Noises. IEEE Transactions on Circuits and SystemsII:Express Briefs. 2018, 15(11):1808-1812.

[26]  Wentao Ma*, Dongqiao Zheng, Zhiyu Zhang, Jiandong Duan, Badong Chen. Robust Proportionate Adaptive Filter Based onMaximum Correntropy Criterion for Sparse System Identification in Impulsive Noise Environments. Signal,image and video processing, 2018,12(1):117-124. 

[27]  Wentao Ma, Jiandong Duan, Haiquan Zhao, Badong Chen*. ChebyshevFunction Link Artificial Neural Network based on Correntropy Induced Metric. Neural processing letter. 2018,47(1):233-252. 

[28]  Wentao Ma, Xinyu Qiu,Jiandong Duan, Yingsong Li, Badong Chen. Kernel recursive generalized mixednorm algorithm. Journal of The Franklin Institute. 2018,355(4):1596-1613.

[29]  Wentao Ma*, Jiandong Duan, Weishi Man, Haiquan Zhao, Badong Chen. Robust Kernel Adaptive Filter Based on Mean p-power Error for Noisy Chaotic Time Series Prediction. Engineering Applications of Artificial Intelligence, 2017,58(2) : 101-110. 

[30]  Wentao Ma*, Jiandong Duan, Badong Chen, Guan Gui, and Weishi Man. Recursive generalized maximum correntropy criterion algorithm with sparse penaltyconstraints for system identification. Asian Journal of Control.2017, 19 (3):1-9 

[31]  Wentao Ma, Badong Chen*, Jiandong Duan, Haiquan Zhao. Diffusion maximum correntropy criterion algorithms for robust distributed estimation. Digital Signal Processing .2016, 58(11): 10-19.

[32]  Wentao Ma, Badong Chen*,Haiquan Zhao,Guan Gui,Jiandong Duan, Jose C.Principe. Sparse Least Logarithmic Absolute Difference Algorithm with Correntropy-Induced Metric Penalty. Circuits, Systems, and SignalProcessing,2016,35(3):1077-1089.

[33]  Wentao Ma*,Badong Chen, Hua Qu, Jihong Zhao. Sparse least mean p-power algorithms forchannel estimation in the presence of impulsive noise. Signal image and video processing,2016, 10(3): 1-8. 

[34]  Wentao Ma, Hua Qu, Guan Gui, Li Xu, Jihong Zhao, BadongChen*. Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments.Journal of The Franklin Institute,2015,352(7):2708-2727. 

[35]马文涛*,寇晓,郭耀松,段建东. 基于扩展KRSL无迹卡尔曼滤波的约束动态状态估计，电力系统自动化，47(6):185-196, 2022.

专利：

[1]    一种用于电池状态估计的改进鲁棒Savitzky-Golay滤波方法. 发 明 (设计)人:马文涛*,薛劲松,郭鹏.申请号: 2024102298235

[2]    锂电池等效电路模型参数鲁棒自适应辨识方法。发 明 (设计)人：马文涛*，蔡盼飞，王晓飞，孙权。专利号：ZL 2021 1 1003350.X

[3]    一种电力系统谐波参数估计方法. 发 明 (设计)人：马文涛*，寇晓，张志禹，邱进哲.专利号：ZL 2019 1 0735904.X 

[4]    基于最小均方四阶的变阈值比例更新自适应滤波算法. 发 明 (设计)人：马文涛*.专利号：ZL 2017 1 1361377.X 

获奖：

[1]2025陕西省高等学校科技成果奖一等奖（1/4）

[2]2022中国电子学会自然科学奖三等奖（3/5）

[3]2021陕西省科技进步奖二等奖（4/9）

[4]2020陕西省高等学校科学技术奖一等奖（2/7）

[5]2018年中国自动化学会自然科学奖二等奖（3/3）