汽车工程 ›› 2024, Vol. 46 ›› Issue (1): 61-74.doi: 10.19562/j.chinasae.qcgc.2024.01.007
收稿日期:
2023-04-05
修回日期:
2023-07-09
出版日期:
2024-01-25
发布日期:
2024-01-23
通讯作者:
陈仁祥
E-mail:manlouyue@126.com
基金资助:
Pengbo Zhang1,2,Renxiang Chen2(),Yiming Shao1,Shizheng Sun2,Kaibo Yan2
Received:
2023-04-05
Revised:
2023-07-09
Online:
2024-01-25
Published:
2024-01-23
Contact:
Renxiang Chen
E-mail:manlouyue@126.com
摘要:
为全面梳理纯电动汽车电驱动系统故障诊断的发展现状,明确未来发展趋势,本文首先介绍了纯电动汽车电驱动系统的基本架构、功能及发展历程;然后详细总结了纯电动汽车电驱动系统关键部件的故障类型及原因,分析了纯电动汽车电驱动系统关键部件故障诊断方法的主要研究现状;接着将诊断方法从专家知识驱动、模型驱动、信号驱动和数据驱动4个方面详细综述了纯电动汽车电驱动系统国内外研究进展和发展动态,并针对不同方法的优缺点进行了对比;最后对纯电动汽车电驱动系统故障诊断所面临的问题及发展方向进行了分析和展望,进一步讨论并指出未来纯电动汽车电驱动系统故障诊断研究可以集中在变工况耦合故障诊断、微小故障诊断和前期故障诊断研究、实时在线故障诊断、基于故障诊断的智能运维、未知故障诊断与系统自愈技术等方面。
张鹏博, 陈仁祥, 邵毅明, 孙世政, 闫凯波. 纯电动汽车电驱动系统故障诊断研究进展[J]. 汽车工程, 2024, 46(1): 61-74.
Pengbo Zhang, Renxiang Chen, Yiming Shao, Shizheng Sun, Kaibo Yan. Research Review of Fault Diagnosis for Electric Drive Powertrain System of Pure Electric Vehicles[J]. Automotive Engineering, 2024, 46(1): 61-74.
表1
电驱动系统故障诊断方法对比"
故障诊断 方法大类 | 具体诊断方法 | 代表文献 | 优点 | 缺点 |
---|---|---|---|---|
模型 驱动 | 数值模型驱动 | [ | 1.实用性、稳定性强; 2.可重复操作且成本低; 3.效率高,响应速度快; 4.可诊断多种类型的故障 | 1.故障诊断准确性受模型精度的影响较大; 2.模型的维护需要不断更新和改进; 3.非稳态、非线性系统难适用; 4.复杂耦合故障诊断难度大 |
有限元驱动 | [ | |||
信号 驱动 | 电流信号驱动 | [ | 1.电气信号易获取,成本低; 2.故障诊断准确率高; 3.可实时监测 | 1.信号易受干扰,影响诊断结果; 2.不同故障可能对应同一种信号响应,诊断识别难度大; 3.特殊信号的传感器部署、监测及数据采集难度大且成本高 |
电压信号驱动 | [ | |||
振动信号驱动 | [ | |||
多信号融合 | [ | |||
数据 驱动 | 深度学习 | [ | 1.诊断速度快,可实时监测,鲁棒性强; 2.无须事先建立数学模型,适用于多种不同类型的故障; 3.可通过不断学习来提高诊断准确度 | 1.对数据的质量要求高,需要对数据进行预处理和特征提取; 2.受数据质量和传感器精度等因素的影响,可能会出现误诊断; 3.需要较高的计算能力; 4.诊断结果可解释性较差 |
人工神经网络 | [ | |||
卷积神经网络 | [ | |||
贝叶斯网络 | [ | |||
金字塔池网络 | [ | |||
生成对抗网络 | [ | |||
深度置信网络 | [ | |||
组合逻辑 | [ | |||
自编码器 | [ | |||
随机森林 | [ | |||
机器学习 | [ | |||
概率神经网络 | [ |
1 | 中国石油和化学工业联合会. 全球能源转型的三种情景与四大趋势 [EB/OL]. [2022-09-30]. http://www.cpcif.org.cn/detail/7d1ee8d2-8d1e-4376-b8eb-5efc2131b14b. |
China Petroleum and Chemical Industry Federation. Three scenarios and four trends of global energy tran-sition [EB/OL]. [2022-09-30]. http://www.cpcif.org.cn/detail/7d1ee8d2-8d1e-4376-b8eb-5efc2131b14b. | |
2 | 中华人民共和国生态环境部. 中国移动源环境管理年报(2022年)[EB/OL]. [2022-12-07]. https://www.mee.gov.cn/hjzl/sthjzk/ydyhjgl/202212/t20221207_1007111.shtml. |
China Petroleum and Chemical Industry Federation. China mobile source environmental management annual report (2022) [EB/OL]. [2022-12-07]. https://www.mee.gov.cn/hjzl/sthjzk/ydyhjgl/202212/t20221207_1007111.shtml. | |
3 | 中华人民共和国生态环境部. 第二次全国污染源普查公报[R]. 北京: 中国环境科学出版社, 2019. |
Ministry of Ecology and Environment of the People's Republic of China. The second national pollution source census bulletin [R]. Beijing: China Environmental Science Press, 2019. | |
4 | BHARATHIDASAN M, INDRAGANDHI V, SURESH V, et al. A review on electric vehicle: technologies, energy trading, and cyber security[J]. Energy Reports, 2022, 8: 9662-9685. |
5 | 中华人民共和国国务院. 国务院办公厅关于印发新能源汽车产业发展规划(2021—2035年)的通知[EB/OL]. [2020-10-20]. http://www.gov.cn/zhengce/content/2020-11/02/content_5556716.htm. |
State Council of the People's Republic of China. Notice of the general office of the state council on issuing the development plan for the new energy vehicle industry (2021-2035) [EB/OL]. [2020-10-20]. http://www.gov.cn/zhengce/content/2020-11/02/content_5556716.htm. | |
6 | 魏一凡, 韩雪冰, 卢兰光, 等. 面向碳中和的新能源汽车与车网互动技术展望[J]. 汽车工程, 2022, 44(4): 449-464. |
WEI Y F, HAN X B, LU L G, et al. Technology prospects of carbon neutrality-oriented new-energy vehicles and vehicle-grid interaction[J]. Automotive Engineering, 2022, 44(4): 449-464. | |
7 | 白旻, 张旻昱, 王晓超. 碳中和背景下全球新能源汽车产业发展政策与趋势[J]. 信息技术与标准化, 2021(12): 13-20. |
BAI M, ZHANG M Y, WANG X C. Development policies and trends of global new energy vehicle industry under the background of carbon neutrality[J]. Information Technology & Standardization, 2021(12): 13-20. | |
8 | 李佳琪, 徐潇源, 严正. 大规模新能源汽车接入背景下的电氢能源与交通系统耦合研究综述[J]. 上海交通大学学报, 2022, 56(3): 253-266. |
LI J Q, XU X Y, YAN Z. A review of coupled electricity and hydrogen energy system with transportation system under the background of large-scale new energy vehicles access[J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 253-266. | |
9 | DAI D T, VAFAEIPOUR M, BAGHDADI M E, et al. Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: topologies and integrated energy management strategies[J]. Renewable and Sustainable Energy Reviews, 2020, 119: 109596-109625. |
10 | 王斌, 潘浩星, 许敏, 等. 纯电驱动车辆动力总成优化的研究[J]. 汽车工程, 2015, 37(6): 617-621. |
WANG B, PAN H X, XU M, et al. A study on the optimization of the powertrain of battery electric vehicle[J]. Automotive Engineering, 2015, 37(6): 617-621. | |
11 | 黄康, 张义雷, 邱明明, 等. 集成式动力总成机电耦合动态特性分析[J]. 应用力学学报, 2021, 38(5): 1935-1945. |
HUANG K, ZHANG Y L, QIU M M, et al. Analysis on dynamic characteristics of electromechanical coupling of integrated powertrain[J]. Chinese Journal of Applied Mechanics, 2021, 38(5): 1935-1945. | |
12 | 郭栋, 任杰, 葛帅帅, 等. 搭载分数槽永磁电机的电驱动总成振动控制[J]. 噪声与振动控制, 2022, 42(4): 20-24. |
GUO D, REN J, GE S S, et al. Vibration suppression of electric drive assembly with a fractional slot motor[J]. Noise and Vibration Control, 2022, 42(4): 20-24. | |
13 | WU C, SEHAB R, AKRAD A, et al. Fault diagnosis methods and fault tolerant control strategies for the electric vehicle powertrains[J]. Energies, 2022, 15(13): 4840. |
14 | CHOUDHARY A, FATIMA S, PANIGRAHI B K. State of the art technologies in fault diagnosis of electric vehicles: a component-based review[J]. IEEE Transactions on Transportation Electrification, 2022. |
15 | 国家市场监督管理总局. 奇瑞汽车股份有限公司召回部分瑞虎3xe纯电动汽车 [EB/OL]. [2019-01-18]. https://www.samr.gov.cn/zw/zh/202006/t20200609_316556.html. |
State Administration for Market Regulation. Chery Automobile Co., Ltd. recalls part of ruihu 3xe pure electric vehicles [EB/OL]. https://www.samr.gov.cn/zw/zh/202006/t20200609_316556.html. | |
16 | 国家市场监督管理总局. 宝马(中国)汽车贸易有限公司召回部分进口i3纯电动汽车 [EB/OL]. [2019-09-23]. https://www.samr.gov.cn/zw/zh/202006/t20200609_316496.html. |
State Administration for Market Regulation. BMW (China) Auto-motive Trading Ltd. recalls some imported i3 electric vehicles[EB/OL]. [2019-09-23]. https://www.samr.gov.cn/zw/zh/202006/t20200609_316496.html. | |
17 | 国家市场监督管理总局. 市场监管总局关于2020年全国汽车和消费品召回情况的通告 [EB/OL]. [2021-03-15]. https://www.samr.gov.cn/zw/zh/202103/t20210313_326862.html. |
State Administration for Market Regulation. General administration of market supervision announcement on the national recalls of automobiles and consume-r products in 2020 [EB/OL]. [2021-03-15]. https://www.samr.gov.cn/zw/zh/202103/t20210313_326862.html. | |
18 | 国家市场监督管理总局. 东风悦达起亚汽车有限公司召回部分KX3纯电动汽车 [EB/OL]. [2021-01-08]. https://www.samr.gov.cn/zw/zh/202101/t20210108_325035.html. |
State Administration for Market Regulation. DongfengYueda KiaMotors Co., Ltd. recalls certain KX3 electric vehicles [EB/OL].[2021-01-08]. https://www.samr.gov.cn/zw/zh/202101/t20210108_325035.html. | |
19 | 国家市场监督管理总局. 特斯拉汽车(北京)有限公司、特斯拉(上海)有限公司召回部分进口及国产Model 3电动汽车 [EB/OL]. [2022-04-07]. https://www.samr.gov.cn/zw/zh/202204/t20220407_341139.html. |
State Administration for Market Regulation. Recall of certain imported and domestic model 3 electric vehicles by Tesla (Beijing) Co., Ltd. and Tesla (Shanghai) Co., Ltd [EB/OL]. [2022-04-07]. https://www.samr.gov.cn/zw/zh/202204/t20220407_341139.html | |
20 | 国家市场监督管理总局. 北京奔驰汽车有限公司召回部分EQC电动汽车 [EB/OL]. [2022-02-18]. https://www.samr.gov.cn/zw/zh/202202/t20220218_339826.html. |
State Administration for Market Regulation. Beijing Benz Automotive Co., Ltd. recalls some EQC electric vehicles [EB/OL]. [2022-02-18]. https://www.samr.gov.cn/zw/zh/202202/t20220218_339826.html. | |
21 | 林程, 徐垚, 邢济垒, 等. 车用超高速永磁电机驱动控制技术综述[J]. 汽车工程, 2022, 44(7): 1049-1058. |
LIN C, CHENG H, XING J L, et al. An overview of drive control technology of ultra-high-speed permanent magnet motors for vehicles[J]. Automotive Engineering, 2022, 44(7): 1049-1058. | |
22 | GU B G. Offline interturn fault diagnosis method for induction motors by impedance analysis[J]. IEEE Transactions on Industrial Electronics, 2018, 65(7): 5913-5920. |
23 | MAJID M, PHUNG B T, AMBIKAIRAJAH E. Online technique for insulation assessment of induction motor stator windings under different load conditions[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2017, 24(1): 349-358. |
24 | ROMERAL L, URRESTY J C, RIBA RUIZ J R, et al. Modeling of surface-mounted permanent magnet synchronous motors with stator winding interturn faults[J]. IEEE Transactions on Industrial Electronics, 2011, 58(5): 1576-1585. |
25 | TIAN P, PLATERO C A, BLAZQUEZ F, et al. Ground fault location system for powertrain of electric vehicles[C].2019 IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED). France: IEEE, 2019: 488-492. |
26 | LARE P, SARABI S, DELPHA C, et al. Stator winding inter-turn short-circuit and air gap eccentricity fault detection of a permanent magnet-assisted synchronous reluctance motor in electrified vehicle[C].2021 24th International Conference on Electrical Machines and Systems (ICEMS). Gyeongju, Korea, Republic of: IEEE, 2021: 932-937. |
27 | POON J, JAIN P, KONSTANTAKOPOULOS I C, et al. Model-based fault detection and identification for switching power converters[J]. IEEE Transactions on Power Electronics, 2017, 32(2): 1419-1430. |
28 | 柯炎, 樊波. 基于电压残差的三相逆变器故障诊断[J]. 空军工程大学学报(自然科学版), 2020, 21(1): 27-31. |
KE Y, FAN B. A three-phase inverter fault diagnosis based on voltage residual[J]. Journal of Air Force Engineering University(Natural Science Edition), 2020, 21(1): 27-31. | |
29 | 余运俊, 裴石磊, 谢玉麟. NPC 三电平逆变器混杂建模及开路故障诊断[J]. 电测与仪表, 2020, 57(11): 16-23. |
YU Y J, PEI S L, XIE Y L. Hybrid modeling and open-circuit fault diagnosis of NPC three-level inverter[J]. Electrical Measurement & Instrumentation, 2020, 57(11): 16-23. | |
30 | 彭伟发, 黄苏融. 永磁同步电机驱动系统逆变器故障诊断研究[J]. 太阳能学报, 2019, 40(7): 1965-1970. |
PENG W F, HUANG S R. Study on fault diagnosis of inverters in pmsm drive system[J]. ACTA Energiae Solaris Sinica, 2019, 40(7): 1965-1970. | |
31 | 李战, 王伯荣, 马皓, 等. 基于平均模型的三相四线制逆变器多管开路故障诊断[J]. 电源学报, 2018, 16(6): 63-70. |
LI Z, WANG B R, MA H, et al. Multi-transistor open-circuit fault diagnosis in three-phase four-wire inverter based on average model[J]. Journal of Power Supply, 2018, 16(6): 63-70. | |
32 | 雷亚国, 汤伟, 孔德同, 等. 基于传动机理分析的行星齿轮箱振动信号仿真及其故障诊断[J]. 机械工程学报, 2014, 50(17): 61-68. |
LEI Y G, TANG W, KONG D T, et al. Vibration signal simulation and fault diagnosis of planetary gearboxes based on transmission mechanism analysis[J]. Journal of Mechanical Engineering, 2014, 50(17): 61-68. | |
33 | ZHANG S, WANG B, KANEMARU M, et al. Model-based analysis and quantification of bearing faults in induction machines[J]. IEEE Transactions on Industry Applications, 2020, 56(3): 2158-2170. |
34 | SHENG L, SUN Q, LI W, et al. Research on gear crack fault diagnosis model based on permanent magnet motor current signal[J]. ISA Transactions, 2022: S0019057822005304. |
35 | 杨明, 柴娜, 李广, 等. 基于电机驱动系统的齿轮故障诊断方法对比研究[J]. 电工技术学报, 2016, 31(19): 132-140. |
YANG M, CHAI N, LI G, et al. A comparative study of gear fault diagnosis methods based on the motor drive system[J]. Transactions of China Electrotechnical Society, 2016, 31(19): 132-140. | |
36 | MOON S, LEE J, JEONG H, et al. Demagnetization fault diagnosis of a pmsm based on structure analysis of motor inductance[J]. IEEE Transactions on Industrial Electronics, 2016, 63(6): 3795-3803. |
37 | 李红梅, 陈涛. 基于分形维数的PMSM局部退磁故障诊断[J]. 电工技术学报, 2017, 32(7): 1-10. |
LI H M, CHEN T. The local demagnetization fault diagnosis of pmsm based on fractal dimension [J]. Transactions of China Electrotechnical Society, 2017, 32(7): 1-10. | |
38 | NEJADI-KOTI H, FAIZ J, DEMERDASH N A. Uniform demagnetization fault diagnosis in permanent magnet synchronous motors by means of cogging torque analysis[C].2017 IEEE International Electric Machines and Drives Conference (IEMDC), 2017: 1-7. |
39 | 雷亚国, 贾峰, 孔德同, 等. 大数据下机械智能故障诊断的机遇与挑战[J]. 机械工程学报, 2018, 54(5): 94-104. |
LEI Y G, JIA F, KONG D T, et al. Opportunities and challenges of machinery intelligent fault diagnosis in big data era[J]. Journal of Mechanical Engineering, 2018, 54(5): 94-104. | |
40 | JEONG H, MOON S, KIM S W. An early stage interturn fault diagnosis of PMSMs by using negative-sequence components[J]. IEEE Transactions on Industrial Electronics, 2017: 5701-5708. |
41 | SADEGHI R, SAMET H, GHANBARI T. Detection of stator short-circuit faults in induction motors using the concept of instantaneous frequency[J]. IEEE Transactions on Industrial Informatics, 2018, 15(8): 4506-4515. |
42 | HANG J, DING S, ZHANG J, et al. Detection of interturn short-circuit fault for pmsm with simple fault indicator[J]. IEEE Transactions on Energy Conversion, 2016, 31(4): 1697-1699. |
43 | GUERRERO J M, NAVARRO G, PLATERO C A, et al. A novel ground fault detection method for electric vehicle powertrains based on a grounding resistor voltage analysis[J]. IEEE Transactions on Industry Applications, 2020, 56(5): 4934-4944. |
44 | YANG B, YE J. Data-driven detection of physical faults and cyber attacks in dual-motor EV powertrains[C].2022 IEEE Transportation Electrification Conference & Expo (ITEC). Anaheim, CA, USA: IEEE, 2022: 991-996. |
45 | WU F, ZHAO J. Current similarity analysis-based open-circuit fault diagnosis for two-level three-phase PWM rectifier[J]. IEEE Transactions on Power Electronics, 2017, 32(5): 3935-3945. |
46 | EICKHOFF H T, SEEBACHER R, MUETZE A, et al. Enhanced and fast detection of open-switch faults in inverters for electric drives[J]. IEEE Transactions on Industry Applications, 2017, 53(6): 5415-5425. |
47 | 黄科元, 刘静佳, 黄守道, 等. 永磁直驱系统变流器开路故障诊断方法[J]. 电工技术学报, 2015, 30(16): 129-136. |
HUANG K Y, LIU J J, HUANG S D, et al. Converters open-circuit fault-diagnosis methods research for direct-drive permanent magnet wind power system[J]. Transactions of China Electrotechnical Society, 2015, 30(16): 129-136. | |
48 | 陈勇, 刘志龙, 陈章勇. 基于电流矢量特征分析的逆变器开路故障快速诊断与定位方法[J]. 电工技术学报, 2018, 33(4): 883-891. |
CHEN Y, LIU Z L, CHEN Z Y. Fast diagnosis and location method for open-circuit fault in inverter based on current vector character analysis[J]. Transactions of China Electrotechnical Society, 2018, 33(4): 883-891. | |
49 | 许水清, 陶松兵, 何怡刚, 等. 基于相电流瞬时频率估计的永磁直驱风电变流器开路故障诊断[J]. 电工技术学报, 2022, 37(2): 433-444. |
XU S Q, TAO S B, HE Y G, et al. Open-circuit fault diagnosis for back-to-back converter of pmsg wind generation system based on estimated instantaneous frequency of phase current[J]. Transactions of China Electrotechnical Society, 2022, 37(2): 433-444. | |
50 | WANG X, LU S, CHEN K, et al. Bearing fault diagnosis of switched reluctance motor in electric vehicle powertrain via multisensor data fusion[J]. IEEE Transactions on Industrial Informatics, 2022, 18(4): 2452-2464. |
51 | POPESCU T D, AIORDACHIOAIE D. Rolling element bearing fault detection using vibrating signals segmentation[C].2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA). Turin: IEEE, 2018: 940-947. |
52 | BOGIATZIDIS I X, SAFACAS A N, MITRONIKAS E D. Detection of backlash phenomena appearing in a single cement kiln drive using the current and the electromagnetic torque signature[J]. IEEE Transactions on Industrial Electronics, 2012, 60(8): 3441-3453. |
53 | HE X, LIU Q, YU W, et al. A new autocorrelation-based strategy for multiple fault feature extraction from gearbox vibration signals[J]. Measurement, 2021, 171: 108738. |
54 | SIGONDE V C, KOUEIOU X T, ALUGONGO A A. Enhancing fault diagnosis of gear transmission error based on experimental analysis[C].2022 IEEE 13th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT). Cape Town, South Africa: IEEE, 2022: 135-140. |
55 | PARK S, KIM S, CHOI J H. Gear fault diagnosis using transmission error and ensemble empirical mode decomposition[J]. Mechanical Systems and Signal Processing, 2018, 108: 262-275. |
56 | 张业成, 刘国海, 陈前. 基于电流波动特征的永磁同步电机匝间短路与局部退磁故障分类诊断研究[J]. 电工技术学报, 2022, 37(7): 1634-1643. |
ZHANG Y C, LIU G H, CHEN Q. Discrimination of interturn short-circuit and local demagnetization in permanent magnet synchronous motor based on current fluctuation characteristics [J]. Transactions of China Electrotechnical Society, 2022, 37(7): 1634-1643. | |
57 | ROSERO J A, CUSIDO J, GARCIA A, et al. Study on the permanent magnet demagnetization fault in permanent magnet synchronous machines[C].IECON 2006-32nd Annual Conference on IEEE Industrial Electronics. IEEE, 2006: 879-884. |
58 | URRESTY J C, RIBA J R, DELGADO M, et al. Detection of demagnetization faults in surface-mounted permanent magnet synchronous motors by means of the zero-sequence voltage component[J]. IEEE Transactions on Energy Conversion, 2011, 27(1): 42-51. |
59 | ESPINOSA A G, ROSERO J A, CUSIDO J, et al. Fault detection by means of Hilbert–Huang transform of the stator current in a PMSM with demagnetization[J]. IEEE Transactions on Energy Conversion, 2010, 25(2): 312-318. |
60 | DEHBIA O, AHMED M, AHMED C, et al. Fault diagnosis techniques for electrical powertrain system-a review[C].2019 International Conference on Applied Automation and Industrial Diagnostics (ICAAID). 2019, 1: 1-7. |
61 | ZHANG X, HU Y, DENG J, et al. Feature engineering and artificial intelligence-supported approaches used for electric powertrain fault diagnosis: a review[J]. IEEE Access, 2022, 10: 29069-29088. |
62 | 李垣江, 张周磊, 李梦含, 等. 采用深度学习的永磁同步电机匝间短路故障诊断方法[J]. 电机与控制学报, 2020, 24(9): 173-180. |
LI Y J, ZHANG Z L, LI M H, et al. Fault diagnosis of inter-turn short circuit of permanent magnet synchronous motor based on deep learning[J]. Electric Machines and Control, 2020, 24(9): 173-180. | |
63 | PENG T, YE C, YANG C, et al. A novel fault diagnosis method for early faults of PMSMs under multiple operating conditions[J]. ISA transactions, 2022, 130: 463-476. |
64 | MOOSAVI S S,DJERDIR A,AIT-AMIRAT Y, et al. ANN based fault diagnosis of permanent magnet synchronous motor under stator winding shorted turn[J]. Electric Power Systems Research, 2015, 125: 67-82. |
65 | PARK C H, KIM H, SUH C, et al. A health image for deep learning-based fault diagnosis of a permanent magnet synchronous motor under variable operating conditions: instantaneous current residual map[J]. Reliability Engineering & System Safety, 2022, 226: 108715. |
66 | CAI B, ZHAO Y, LIU H, et al. A data-driven fault diagnosis methodology in three-phase inverters for PMSM drive systems[J]. IEEE Transactions on Power Electronics, 2017, 32(7): 5590-5600. |
67 | LIU B, WU Q, LI Z, et al. Research on fault diagnosis of IPMSM for electric vehicles based on multi-level feature fusion SPP network[J]. Symmetry, 2021, 13(10): 1844-1866. |
68 | 于海, 邓钧君, 王震坡, 等. 基于卷积神经网络的逆变器故障诊断方法[J]. 汽车工程, 2022, 44(1): 142-152. |
YU H, DENG J J, WANG Z P, et al. Inverter fault diagnosis method based on convolutional neural network[J]. Automotive Engineering, 2022, 44(1): 142-152. | |
69 | WANG H, ZHANG C, ZHANG N, et al. Fault diagnosis for igbts open-circuit faults in high-speed trains based on convolutional neural network[C].2019 Prognostics and System Health Management Conference (PHM-Qingdao). IEEE, 2019: 1-8. |
70 | 孙权, 于翔海, 李宏胜, 等. 基于二维卷积神经网络的 BLDCM 驱动系统故障检测方法[J]. 电源学报, 2022, 20(1): 180-187. |
SUN Q, YU X H, LI H S, et al. Fault detection method for bldcm drive system based on 2D-CNN[J]. Journal of Power Supply, 2022, 20(1): 180-187. | |
71 | 孙权,彭飞,李宏胜,等.样本不均衡下基于CGAN-CNN的逆变器故障诊断方法[J/OL].电源学报:1-14[2023-05-21].http://libvpn.cqjtu.edu.cn:80/rwt/CNKI/http/NNYHGLUDN3WXTLUPMW4A/kcms/detail/12.1420.tm.20220601.1854.002.html. |
SUN Q, PENG F, LI H S, et al. Imbalanced samples fault de-tection using CGAN-CNN for power inverter[J/OL]. Journal of Power Supply:1-14[2023-05-19].http://libvpn.cqjtu.edu.cn:80/rwt/CNKI/http/NNYHGLUDN3WXTLUPMW4A/kcms/detail/12.1420.tm.20220601.1854.002.html. | |
72 | LI C, SANCHEZ R V, ZURITA G, et al. Multimodal deepsupport vector classification with homologous features and its application to gearbox fault diagnosis[J]. Neur-ocomputing, 2015, 168: 119-127. |
73 | LAL SENANAYAKA J S, VAN KHANG H, ROBBERSMYR K G. Online fault diagnosis system for electric powertrains using advanced signal processing and machinelearning[C].2018 XIII International Conference on Electrical Machines (ICEM). Alexandroupoli: IEEE, 2018: 1932-1938. |
74 | LAL SENANAYAKA J S, VAN KHANG H, ROBBERSMYR K G. Multiple fault diagnosis of electric powertrains under variable speeds using convolutional neural networks[C].2018 XIII International Conference on Electrical Machines (ICEM). Alexandroupoli: IEEE, 2018: 1900-1905. |
75 | LAL SENANAYAKA J S, VAN KHANG H, ROBBERSMYR K G. Toward self-supervised feature learning for online diagnosis of multiple faults in electric powertrains[J]. IEEE Transactions on Industrial Informatics, 2021, 17(6): 3772-3781. |
76 | CHEN R X, HUANG X, YANG L X, et al. Intelligent fault diagnosis method of planetary gearboxes based on convolution neural network and discrete wavelet transform[J]. Computers in Industry, 2019, 106: 48-59. |
77 | HE J, YANG S, GAN C. Unsupervised fault diagnosis of a gear transmission chain using a deep belief network[J]. Sensors, 2017, 17(7): 1564. |
78 | ULATOWSKI A, BAZZI A. A combinational-logic method for electric vehicle drivetrain fault diagnosis[J]. IEEE Transactions on Industry Applications, 2015, 52(2): 1796-1807. |
79 | SHAO H, JIANG H, LIN Y, et al. A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders[J]. Mechanical Systems and Signal Processing, 2018, 102: 278-297. |
80 | WANG Z, ZHANG Q, XIONG J, et al. Fault diagnosis of a rolling bearing using wavelet packet denoising and random forests[J]. IEEE Sensors Journal, 2017, 17(17): 5581-5588. |
81 | SHAO H, XIA M, HAN G, et al. Intelligent fault diagnosis of rotor-bearing system under varying working conditions with modified transfer convolutional neural network and thermal images[J]. IEEE Transactions on Industrial Informatics, 2021, 17(5): 3488-3496. |
82 | SHI H, GUO L, TAN S, et al. Rolling bearing initial fault detection using long short-term memory recurrent network[J]. IEEE Access, 2019, 7: 171559-171569. |
83 | OH H, JUNG J H, JEON B C, et al. Scalable and unsupervised feature engineering using vibration-imaging and deep learning for rotor system diagnosis[J]. IEEE Transactions on Industrial Electronics, 2018, 65(4): 3539-3549. |
84 | HADRAOUI H E, LAAYATI O, GUENNOUNI N, et al. A data-driven model for fault diagnosis of induction motor for electric powertrain[C].2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON). Palermo, Italy: IEEE, 2022: 336-341. |
85 | 张丹, 赵吉文, 董菲, 等. 基于概率神经网络算法的永磁同步直线电机局部退磁故障诊断研究[J]. 中国电机工程学报, 2019, 39(1): 296-306,344. |
ZHANG D, ZHAO J W, DONG F, et al. Partial demagnetization fault diagnosis research of permanent magnet synchronous motors based on the PNN algorithm[J]. Proceedings of the CSEE, 2019, 39(1): 296-306,344. | |
86 | LI Z, WU Q, YANG S, et al. Diagnosis of rotor demagnetization and eccentricity faults for IPMSM based on deep CNN and image recognition[J]. Complex & Intelligent Systems, 2022, 8(6): 5469-5488. |
87 | HUANG F, ZHANG X, QIN G, et al. Demagnetization fault diagnosis of permanent magnet synchronous motors using magnetic leakage signals[J]. IEEE Transactions on Industrial Informatics, 2022, 19(4): 6105-6116. |
88 | 赵靖, 杨绍普, 李强, 等. 一种残差注意力迁移学习方法及其在滚动轴承故障诊断中的应用[J]. 中国机械工程, 2023, 34(3): 332-343. |
ZHAO J, YANG S P, LI Q, et al. A new transfer learning method with residual attention and its application on rolling bearing fault diagnosis[J]. China Mechanical Engineering, 2023, 34(3): 332-343. | |
89 | 贾晗,尚前明,金华标.多源信息融合的电机小样本故障诊断[J/OL].机械科学与技术:1-9[2023-05-21].http://libvpn.cqjtu.edu.cn:80/rwt/CNKI/https/MSYXTLUQPJUB/10.13433/j.cnki.1003-8728.20230234. |
JIA H, SHANG Q M, JIN H B. Multi-source information fusion for motor small-sample fault diagnosis[J/OL]. Mechanical Science and Technology for Aerospace Engineering:1-9[2023-05-21].http://libvpn.cqjtu.edu.cn:80/rwt/CNKI/https/MSYXTLUQPJUB/10.13433/j.cnki.1003-8728.20230234. | |
90 | 张希, 廖宇兰, 李沁逸, 等. 安全行驶下的车用电机轴承的数字孪生故障诊断[J]. 汽车安全与节能学报, 2023, 14(2): 232-238. |
ZHANG X, LIAO Y L, LI Q Y, et al. Fault diagnosis of vehicle motor-bearings under safe running by digital-twin technology[J]. Journal of Automotive Safety and Energy, 2023, 14(2): 232-238. |
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