摘要
新能源汽车作为节能环保的新产品具有较好社会前景,内在的动力电池是新能源汽车的主动力源,但电池发动机是一个较为复杂的系统,在处于恶劣环境时,可能出现各种故障问题。新能源汽车的动力电池若发生故障,不但会使汽车的系统性能下降,还会造成灾难性的后果,为此,研究传感器信息融合下新能源汽车动力电池信号故障检测方法。通过一致性定律整理电池系统传感器数据,在近似概率和频率中估算新能源汽车动力电池信号;选择熵权重法理论对数据信号进行区分,以时刻内单体电压作为评价指标,在预处理后构建判断信号故障矩阵;通过故障判断矩阵确定异常信号,在传感器信息融合算法下修订权值,以最大误差范围检测信号输出,检测新能源汽车动力电池信号故障,完成检测方法设计。实验以四组不同类型的新能源汽车作为测试对象,对其动力电池的运动工况进行信号模拟,在不同的接口处获取故障电压信号并完成检测测试,设计的电池信号故障检测方法能够实现精准的故障信号跟踪,完成较为精准的故障信号检测,具有一定的应用价值。
As a new product of energy conservation and environmental protection,new energy vehicles have good prospects.Their internal power battery is the main power source of new energy vehicles.However,due to the fact that the battery engine is a complex system,it can cause malfunction problems in harsh environments.If the power battery of a new energy vehicle malfunctions,it will not only degrade the system performance of the vehicle,but also cause catastrophic consequences.Therefore,a fault detection method for the power battery signal of new energy vehicles based on sensor information fusion is studied.The sensor data of the battery system is sorted by the law of consistency,and then the power battery signal of new energy vehicles is estimated in the approximate probability and frequency.The entropy weight method theory is selected to distinguish the data signals,with the single time voltage as the evaluation index,and the judgment signal fault matrix is constructed after pre-processing.The abnormal signal is determined through the fault judgment matrix;the weight is revised under the sensor information fusion algorithm;the signal output is detected by the maximum error range;the signal failure of the new energy vehicle power battery is detected,and the detection method design is completed.The experiment takes four different types of new energy vehicles as test objects,simulates the motion conditions of their power batteries,obtains fault voltage signals at different interfaces,and completes detection testing.The designed battery signal fault detection method can achieve accurate fault signal tracking and achieve more accurate fault signal detection,which has certain application value.
作者
江雪峰
JIANG Xuefeng(School of Chuzhou Polytechnic,Chuzhou 239000,China)
出处
《东莞理工学院学报》
2024年第3期94-99,共6页
Journal of Dongguan University of Technology
基金
省级质量工程项目产教融合实训基地:滁州职业技术学院安徽英克尔汽车零部件有限公司实践教育基地(2022cjrh035)。
关键词
新能源汽车
动力电池信号
故障检测
传感器信息融合
new energy vehicles
power battery signal
fault detection
sensor information fusion