常春导师
基本信息
|
学 院: |
新葡的京集团350vip |
导师类别: |
硕士生导师 |
出生年月: |
1978.02 |
职 称: |
副教授 |
学 历: |
博士研究生 |
学 位: |
博士 |
个人简介:
常春,博士,新葡的京集团350vip电气与电子学院,储能系统性能检测与安全评估PI团队成员,目前研究方向为储能系统状态监测与安全防控。主持国家自然科学基金面上项目1项、省教育厅项目1项、湖北省太阳能协同创新中心开放基金1项、湖北省太阳能发电及储能运行控制重点实验室开放基金项目2项和新能源及电网装备安全监测湖北省工程研究中心开放基金1项,参与国家级项目3项、省科研项目6项,主持横向项目5项,主持教研项目1项,获得湖北省科技进步三等奖和武汉市科技进步三等奖各1项。以第一作者和通讯作者在《Energy》、《Journal of Power Sources》和《Journal of Energy Storage》等国际期刊上发表SCI/EI论文10余篇,授权发明专利3项,发表教研论文4篇,指导研究生获得全国研究生电子设计大赛省级奖项5项,连续四年被评为湖北省优秀学士学位论文指导老师。
招生信息:
1. 招生学科:电气工程
2. 研究方向:储能系统状态监测与安全防控
3. 招生年度:2024
科研项目:
1. 2024.1-2027.12,基于在线阻抗的动力锂电池衰退演变特性与诊断方法研究,国家自然科学基金面上项目,在研,国家自然科学基金委,主持
2. 2022.1-2023.12,动力锂离子电池在线故障诊断和安全风险评估技术研究,在研,湖北省太阳能发电及储能运行控制重点实验室,主持
3. 2022.1-2025.12,动力锂电池自引发热失控的典型诱因模拟与预警方法研究,国家自然科学基金项目,在研,国家自然科学基金委,参与
4. 2021.5-2023.6,动力锂电池热失控前兆诊断和安全预警技术研究,在研,新能源及电网装备安全监测湖北省工程研究中心,主持
5. 2022.12-2023.12,电动自行车电池单体和模组失效测试,在研,中国标准化研究院,主持
6. 2020.7-2022.6,锂离子电池老化诊断与健康状态估计研究,结题,湖北省太阳能发电及储能运行控制重点实验室,主持
7. 2022.1-2023.12,动力电池状态评估与安全预警方法研究,在研,北京理工大学深圳汽车研究院,参与
8. 2015.1-2018.11,光伏微网系统中基于改进粒子滤波算法和数据融合技术的储能蓄电池SOC估计,结题,太阳能高效利用湖北省协同创新中心,主持
成果获奖:
[1] Chun Chang(常春),Yaliang Pan,Shaojin Wang,Jiuchun Jiang,Aina Tian,Yang Gao,Yan Jiang,Aina Tian,Yang Gao,Yan Jiang,Tiezhou Wu.Fast EIS acquisition method based on SSA-DNN prediction model.Energy,288:129768.(SCI,1区,Top期刊)
[2] Chang Chun(常春),Wang Qiyue,Jiang Jiuchun,Jiang Yan,Wu Tiezhou. Voltage fault diagnosis of a power battery based on wavelet time-frequency diagram[J]. Energy,2023,278:127920.(SCI,1区,Top期刊)
[3] Chun Chang(常春),Yutong Wu, JiuchunJiang*, Yan Jiang, Aina Tian, Taiyu Li, Yang Gao, Prognostics of the state of health for Lithium-ion battery packs in energy storage Applications. Energy, 2022, 239: 122189.(SCI,1区,Top期刊)
[4] Chun Chang(常春), XiaPing Zhou, Jiuchun Jiang*, Gao Yang, Jiang Yan, Tiezhou Wu, Electric vehicle battery pack micro-short circuit fault diagnosis based on charging voltageranking evolution, Journal of Power Sources. 2022, 542: 231733.(SCI,2区,Top期刊)
[5] Chun Chang(常春), Shaojin Wang, Chen Tao, Yan Jiang*, Jiuchun Jiang, An improvement of equivalent circuit model for state of health estimation of lithium-ion batteries based on mid-frequency and low-frequency electrochemical impedance spectroscopy, Measurement, 2022, 202: 111795.(SCI,2区)
[6] Chun Chang(常春),XiaPing Zhou,Jiuchun Jiang*, Yang Gao, Yan Jiang, TiezhouWu, Micro-fault diagnosis of electric vehicle batteries based on the evolution of battery consistency relative position, Journal of Energy Storage, 2022, 52: 104746(SCI,2区)
[7] Chun Chang(常春), Qiyue Wang, Jiuchun Jiang*, Tiezhou Wu,Lithium-ion battery stateof health estimation using the incremental capacity and wavelet neural networks with genetic algorithm, Journal of Energy Storage, 2021, 38: 102570.(SCI,2区)
[8] Jiuchun Jiang, Taiyu Li,Chun Chang*(常春),Chen Yang, Li Liao. Fault diagnosis method for lithium-ion batteries in electric vehicles based on isolated forest algorithm, Journal of Energy Storage, 2022, 50: 104177.(SCI,2区)
[9] Jiuchun Jiang, Ruhang Zhang,Yutong Wu, Chun Chang*(常春),Yan Jiang. A fault diagnosis method for electric vehicle power lithium battery based on wavelet packet decomposition[J]. Journal of Energy Storage, 2022, 56: 105909.(SCI,2区)
[10] Chun Chang(常春), Shaojin Wang, Jiuchun Jiang*, Yang Gao, Yan Jiang, Li Liao, Lithium-ion battery state of health estimation based on electrochemical impedance spectroscopy and cuckoo search algorithm optimized Elman neural network, Journal ofElectrochemical Energy Conversion and Storage, 2022, 19(3): 030912.(SCI,4区)
[11] Chun Chang(常春), Chen Tao, Shaojin Wang,Ruhang Zhang, Aina Tian, Jiuchun Jiang*, A fault diagnosis method for lithium batteries based on optimal variational modal decomposition and dimensionless feature parameters, Journal of Electrochemical Energy Conversion and Storage,2023, 20(3): 031004.(SCI,4区)
[12] Maonan Wang,Chun Chang*(常春), Feng Ji, ADSOC-based equalization strategy applied to industry,International Journal of Low-Carbon Technologies, 2020, 00: 1–8.(SCI,4区)
[13] 常春,王少晋,苏广伟,姜久春*.基于改进模型的锂离子电池健康状态估计[J].电池.(已录用)(北大核心)
[14] 常春,王启悦,姜久春*,高洋,吴铁洲.基于小波分解和Hilbert包络谱分析的电池故障诊断方法[J].蓄电池,2021,58(06):251-256.
[15] 姜久春,常春,田爱娜,廖力,王鹿军,吴铁州,张如行,高洋.一种基于支持向量机的电池故障识别方法.中国发明专利,专利号:202011476362.X
[16] 姜久春,常春,周霞平,高洋,王鹿军,廖力,田爱娜.一种基于电池组一致性演变的电池微故障诊断方法.中国发明专利,专利号:202110872621.9
[17] KJ287矿山人员管理系统.湖北省科技厅,湖北省科技进步奖,三等奖