汽车安全与节能学报 ›› 2020, Vol. 11 ›› Issue (4): 529-537.DOI: 10.3969/j.issn.1674-8484.2020.04.013
收稿日期:
2020-07-09
出版日期:
2020-12-30
发布日期:
2021-01-04
通讯作者:
谢辉
作者简介:
*谢辉,教授。E-mail: xiehui@tju.edu.cn。基金资助:
ZHU Guanhong(), SONG Kang, XIE Hui*(), CHEN Tao, QIAN Zhenhuan
Received:
2020-07-09
Online:
2020-12-30
Published:
2021-01-04
Contact:
XIE Hui
摘要:
为了对可监测变量少、时间尺度大、耦合性强的柴油机冷却系统的故障进行有效监测和准确诊断,设计了一种结合同步运行物理模型和小样本数据驱动的智能诊断算法。算法中建立了一个基于冷却系统物理原理的简化模型。利用模型实时预测的水温和实际水温的残差作为故障诊断的信息依据,并将信息输入支持向量机(SVM)进行分类,辨识故障原因。利用GT-SUITE柴油机模型对算法进行仿真测试,在车辆故障工况下对算法进行了试验测试。结果表明:该算法对故障的识别准确度在97 %以上,诊断用时在45 s以内,显示出该诊断算法对冷却系统故障有良好的监测能力和准确辨识的潜力。
中图分类号:
朱观宏, 宋康, 谢辉, 陈韬, 钱振环. 基于物理模型和支持向量机的柴油机冷却系统故障诊断算法[J]. 汽车安全与节能学报, 2020, 11(4): 529-537.
ZHU Guanhong, SONG Kang, XIE Hui, CHEN Tao, QIAN Zhenhuan. Fault diagnosis algorithm of diesel engine cooling system based on physical model and support vector machine[J]. Journal of Automotive Safety and Energy, 2020, 11(4): 529-537.
柴油机类型 | 六缸直列增压 |
---|---|
排量 | 6.2 L |
额定功率 | 201 kW |
额定转速 | 2 300 r·min-1 |
最大转矩 | 1.06 kNm |
最大转矩转速 | 1 200~1 800 r·min-1 |
水泵驱动方式 | 曲轴皮带传动 |
风扇驱动方式 | 电机带动 |
正常出水温度 | 80 ~ 95 ℃ |
车辆质量 | 10.5 t |
迎风面积 | 8.192 m2 |
风阻系数 | 0.362 |
滚阻系数 | 0.059 |
主减速比 | 3.89 |
轮胎半径 | 0.478 m |
柴油机类型 | 六缸直列增压 |
---|---|
排量 | 6.2 L |
额定功率 | 201 kW |
额定转速 | 2 300 r·min-1 |
最大转矩 | 1.06 kNm |
最大转矩转速 | 1 200~1 800 r·min-1 |
水泵驱动方式 | 曲轴皮带传动 |
风扇驱动方式 | 电机带动 |
正常出水温度 | 80 ~ 95 ℃ |
车辆质量 | 10.5 t |
迎风面积 | 8.192 m2 |
风阻系数 | 0.362 |
滚阻系数 | 0.059 |
主减速比 | 3.89 |
轮胎半径 | 0.478 m |
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