姓名：张照生 职称：副教授 导师类型：博导 团队名称：车能路云融合技术研究中心 邮箱：zhangzhaosheng@bit.edu.cn

 

研究领域

主要研究领域为：新能源汽车大数据和智能交通

教育经历

2008年09月–2013年07月：清华大学大学车辆工程专业 博士学位

2004年09月–2008年06月：湖南大学车辆工程专业 学士学位

工作经历

2020年07月–今：北京理工大学机械与车辆学院 副教授

2013年08月–2020年07月：北京理工大学机械与车辆学院 助理教授

学术成果

1.Zhang Z, Ye B, Wang S, Ma Y*. Analysis and estimation of energy consumption of electric buses using real-world data[J]. Transportation Research Part D: Transport and Environment, 2024, 126: 104017.

2.Zhang Z*, Bi J, Li D*, et al. Battery defect detection for real world vehicles based on Gaussian distribution parameterization developed LCSS[J]. Journal of Energy Storage, 2024, 75: 109679.

3.Wang S, Wang Z, Pan J, Zhang Z*, Cheng X*. A data-driven fault tracing of lithium-ion batteries in electric vehicles[J]. IEEE Transactions on Power Electronics, 2024, 36(2): 1-13.

4.Zhang Z, Dong S, Li D, Wang ZP*, et al. Prediction and Diagnosis of Electric Vehicle Battery Fault Based on Abnormal Voltage: Using Decision Tree Algorithm Theories and Isolated Forest[J]. Processes, 2024, 12(1): 136.

5.Li D, Deng J, Zhang Z*, Liu P, Wang Z. Multi-dimension statistical analysis and selection of safety-representing features for battery pack in real-world electric vehicles[J]. Applied Energy. 2023, 343.

6.Li D, Deng J, Zhang Z*, Wang Z, Zhou L, Liu P. Battery Safety Risk Assessment in Real-World Electric Vehicles Based on Abnormal Internal Resistance Using Proposed Robust Estimation Method and Hybrid Neural Networks[J]. IEEE Transactions on Power Electronics. 2023, 38:7661-7673.

7.Li D, Zhang Z*, Wang Z*, Liu P, Liu Z, Lin N. Timely thermal runaway prognosis for battery systems in real-world electric vehicles based on temperature abnormality[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2023, 11:120-130.

8.Wang S, Wang Z, Cheng X*, Zhang Z*. A double-layer fault diagnosis strategy for electric vehicle batteries based on Gaussian mixture model[J]. Energy. 2023, 281.

9.Zhou L, Zhang Z*, Liu P, Zhao Y, Cui D, Wang Z. Data-driven battery state-of-health estimation and prediction using IC based features and coupled model[J]. Journal of Energy Storage. 2023, 72.

10.Li D, Deng J, Bi J, Zhang Z*, Liu P*, Wang Z. Precision-concentrated battery defect detection method in real-world electric vehicles crossing different temperatures and vehicle states. IEEE Transactions on Transportation Electrification, 2023.

11.Li X, Lyu M, Li K, Gao X, Liu C, Zhang Z*. Lithium-ion battery state of health estimation based on multi-source health indicators extraction and sparse Bayesian learning[J].Energy. 2023,282.

12.Li D, Zhang Z*, Zhou L, Wang Z*, et al. Multi-time-step and multi-parameter prediction for real-world proton exchange membrane fuel cell vehicles (PEMFCVs) toward fault prognosis and energy consumption prediction[J]. Applied Energy, 2022, 325: 119703.

13.Cui D, Wang Z, Zhang Z*, et al. Driving event recognition of battery electric taxi based on big data analysis[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(7): 9200-9209.

14.Li D, Zhang Z*, Liu P*, Zhang L*, et al. Battery fault diagnosis for electric vehicles based on voltage abnormality by combining the long short-term memory neural network and the equivalent circuit model[J]. IEEE Transactions on Power Electronics, 2020, 36(2): 1303-1315.

15.李达, 张普琛, 林倪, 张照生*等. 基于多模型耦合的电动汽车三电系统安全性估计方法[J]. 机械工程学报, 2023, 59(12): 354-363.

教学工作

1.智能汽车网联技术，本科生，32学时

2.现代汽车艺术鉴赏，本科生，32学时

3.车辆大数据分析技术，研究生，32学时

荣誉奖励

1.高层次应用创新人才“产学研联盟+全行业平台”培养模式探索，国家教学成果奖二等奖，2023年。

2.新能源汽车车联网大数据系统关键技术及国家监管体系建设，北京市科技进步一等奖，2020年。

3.数据驱动的新能源汽车管理与服务关键技术及应用，中国智能交通协会科学技术奖一等奖，2022年。

4.基于车联网的汽车智能导航关键技术及应用，教育部科技进步一等奖，2019年

5.网联汽车电子地图关键技术及应用，中国汽车工业科技进步特等奖，2019年。

6.高层次应用创新人才“产学研联盟+全行业平台”培养模式探索，北京市教育教学成果奖一等奖，2022年。

7.教育部课程思政教学名师和教学团队，2021年。

8.能源客车安全管控关键技术及产业化，福建省科学技术进步奖二等奖，2022年。

社会兼职

1.电动车辆国家工程研究中心副主任

2.新能源汽车国家监管平台负责人

3.新能源电池回收利用专业委员会副秘书长