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作 者:王晶[1] 刘晓丹[1] 郑敏[1] 薛双苓[1] 张二红[1] 江薇 WANG Jing;LIU Xiaodan;ZHENG Min;XUE Shuangling;ZHANG Erhong;JIANG Wei(Department of Mechanical and Electrical Engineering,Langfang Polytechnic Institute,Langfang 065000,China)
机构地区:[1]廊坊职业技术学院机电工程系,河北廊坊065000
出 处:《汽车电器》2024年第5期22-25,共4页Auto Electric Parts
基 金:河北省教育厅科学研究项目资助(ZC2023094)。
摘 要:本文提出一种电动汽车驱动系统扭转振动扭矩梯度控制方法。该方法引入RBF神经网络计算扭矩变化率梯度限制值,利用扭矩变化率限制值对驱动电机的输出扭矩进行限制,以此防止扭矩突然变大所造成的传动系统各轴段的过度扭转,从根源上消除引起驱动系统扭转振动的问题。与传统扭转振动控制方法不同,文章提出的控制方法面向实际工程应用,不依赖于车辆简化的二阶质量模型以及车辆参数,避免由于模型及车辆参数精度问题对控制效果造成的不良影响,具有优良的实际工程应用价值。最后,文章通过实车试验的方式对该方法的可行性及有效性进行验证。This article proposes a torque gradient control method for torsional vibration of electric vehicle drive systems.This method introduces RBF neural network to calculate the gradient limit value of torque change rate,and uses the limit value of torque change rate to limit the output torque of the drive motor,in order to prevent excessive torsion of each shaft segment of the transmission system caused by sudden increase in torque,thereby eliminating the problem of causing torsional vibration of the drive system from the root cause.Different from the traditional control method of Torsional vibration,the control method proposed in this paper is oriented to practical engineering implementation,does not rely on the simplified second-order mass model of the vehicle and vehicle parameters,avoids the adverse impact on the control effect caused by the accuracy of the model and vehicle parameters,and has excellent practical engineering application value.At the end of the article,the feasibility and effectiveness of this method were verified through actual vehicle validation.
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