[关键词]
[摘要]
根据电动汽车用驱动电机性能特点,从驱动电机系统的电机控制性能、电机本体设计、企业资质能力等不同维度分析,应用层次分析法(AHP)确定驱动电机性能评价指标体系及其指标权重,建立驱动电机性能评价的BP神经网络模型,并采用鸡群优化算法(CSO)对其模型进行优化。仿真实例表明,基于AHP和CSOBP神经网络的驱动电机系统性能评价方法,具有评价速度快、准确率高等优点, 并得到满意的评价结果。这对于电动汽车驱动电机系统的评价、选择与应用,具有较好的工程实用价值。
[Key word]
[Abstract]
According to the performance characteristics of the driving motor for electric vehicle, analysis of motor control performance, motor body design and enterprise qualification from the drive motor system, applying of analytic hierarchy process (AHP) to determine the performance evaluation index system and index weight of the driving motor, a BP neural network model of performance evaluating for drive motor, and the chicken group algorithm (CSO) was used to optimize the model. The simulation results showed that the performance evaluation method of drive motor based on AHP and CSOBP neural network has the advantages of high speed and high accuracy, and get satisfactory result, this have good engineering practical value to evaluation, selection and application for electric vehicle drive motor system.
[中图分类号]
TM 301.2
[基金项目]