SA  >> Vol. 6 No. 5 (December 2017)

    神经网络在电动汽车电机寿命预测中的应用
    Application of Neural Network in Reliability Prediction of Electric Vehicle Motor

  • 全文下载: PDF(733KB) HTML   XML   PP.501-507   DOI: 10.12677/SA.2017.65056  
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作者:  

王彩娟:长春工业大学,吉林 长春

关键词:
可靠性经验函数神经网络最小二乘法Reliability Empirical Function Neural Network Ordinary Least Square

摘要:

电动汽车电机使用寿命一直是电动汽车消费者关心的话题。本文针对电动汽车电机使用寿命数据进行分析,使用了联合最小二乘法和数学期望经验分布函数拟合估计参数的方法。同时也利用神经网络模型和数学期望经验分布函数拟合估计参数的方法,并对两种方法进行比较。通常使用的参数估计方法受主观因素的影响,确定寿命模型的基准是经验分布函数,其精准度影响寿命模型的精度。本文分别选取同样配置的18台电动汽车电机,在同样的环境下收集故障数据,对其进行寿命可靠性分析。经计算结果表明,神经网络和经验分布函数拟合估计参数的方法相对来说具有很高的准确性与实用性。

The service reliability of the electric vehicle motor has been a consumer’s concerned topic. The service reliability of the electric vehicle motor data analysis are used the combination of ordinary least square and mathematical expectation empirical distribution function fitting method to estimate the parameters. At the same time, the neural network model and the mathematical expectation empirical distribution function are used to fit the estimation parameters, and the two methods are compared. The parameter estimation method usually used is affected by subjective factors. The benchmark of the reliability model is the empirical distribution function, and its precision affects the precision of the reliability model. In this paper, 18 electric vehicle motors with the same configuration are selected, and the failure data are collected in the same environment. The results show that the method of estimating parameters by neural network and empirical distribution function is more accurate and practical.

文章引用:
王彩娟. 神经网络在电动汽车电机寿命预测中的应用[J]. 统计学与应用, 2017, 6(5): 501-507. https://doi.org/10.12677/SA.2017.65056

参考文献

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