Research of the Dynamic Shift Schedule of Mining Track based on Neural Network Engine Model

Qiao Shengjie; Sun Liang; Wang Weida; Zhang Wei

doi:10.16578/j.issn.1004.2539.2017.08.010

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Research of the Dynamic Shift Schedule of Mining Track based on Neural Network Engine Model

更新时间：2022-10-20

- Research of the Dynamic Shift Schedule of Mining Track based on Neural Network Engine Model
- Vol. 41, Issue 8, Pages: 48-52(2017)
- 作者机构：
  
  1. 北京理工大学车辆传动国家重点实验室
  2. 交通运输部科学研究院
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2017.08.010
  CLC：
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[1]乔晟杰,孙良,王伟达,张为.基于发动机神经网络模型的矿用车动态换挡规律研究[J].机械传动,2017,41(08):48-52+57.

Qiao Shengjie, Sun Liang, Wang Weida, et al. Research of the Dynamic Shift Schedule of Mining Track based on Neural Network Engine Model. [J]. 41(8):48-52(2017)
[1]乔晟杰,孙良,王伟达,张为.基于发动机神经网络模型的矿用车动态换挡规律研究[J].机械传动,2017,41(08):48-52+57. DOI： 10.16578/j.issn.1004.2539.2017.08.010.

Qiao Shengjie, Sun Liang, Wang Weida, et al. Research of the Dynamic Shift Schedule of Mining Track based on Neural Network Engine Model. [J]. 41(8):48-52(2017) DOI： 10.16578/j.issn.1004.2539.2017.08.010.

摘要

车辆在起步、停车、制动、换挡时发动机处于动态工况,其最佳换挡点与稳态工况下制定的换挡规律有所不同。根据已有的试验数据训练模型,运用神经网络方法建立了发动机动态模型,基于发动机动态模型制定了以车速、油门开度、加速度为参数的矿用车动力性换挡规律,在MATLAB/Sim Driveline中建立整车的动力学模型,对所设计的换挡规律进行仿真分析,验证了车辆的动力性能。对改进矿车现有两参数换挡规律有实际意义。

Abstract

The engine is in a dynamic state when vehicles in the starting,parking,braking and shifting.The optimal shift point is different from the ones designed in steady state. The neural network method is used to establish the dynamic model of the engine and the model is trained with the experimental data. Based on this model,three-parameter shift schedule including vehicle speed,throttle threshold,acceleration of the mining truck is designed. A dynamics model of the vehicle is established by MATLAB/Sim Driveline,the power performance of the designed shift schedule is verified by simulation analysis. This method can be used to modify the existing two-parameter shift schedule of the mining truck.

关键词

矿用汽车动力性换挡规律发动机动态模型人工神经网络三参数

Keywords

Mining truckPower performance shift scheduleDynamic engine modelArtificial neural networkThree-parameter

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College of Mechanical Engineering,Nanjing Tech University

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