汽车工程 ›› 2022, Vol. 44 ›› Issue (11): 1763-1771.doi: 10.19562/j.chinasae.qcgc.2022.11.014

所属专题: 底盘&动力学&整车性能专题2022年

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基于行驶数据挖掘的DCT车辆平直道路换挡规律研究

秦大同(),王康,冯继豪,刘永刚   

  1. 重庆大学,机械传动国家重点实验室,重庆  400044
  • 收稿日期:2022-06-06 修回日期:2022-07-14 出版日期:2022-11-25 发布日期:2022-11-19
  • 通讯作者: 秦大同 E-mail:dtqin@cqu.edu.cn
  • 基金资助:
    国家自然科学基金重点支持项目(U1764259)

Research on Shift Schedule of DCT Vehicle on Flat-Straight Road Based on Driving Data Mining

Datong Qin(),Kang Wang,Jihao Feng,Yonggang Liu   

  1. Chongqing University,State Key Laboratory of Mechanical Transmission,Chongqing  400044
  • Received:2022-06-06 Revised:2022-07-14 Online:2022-11-25 Published:2022-11-19
  • Contact: Datong Qin E-mail:dtqin@cqu.edu.cn

摘要:

针对基于车辆动力学制定的换挡规律适应性差,基于多维数据结合智能算法训练的挡位决策模型无法直接应用于实车等问题,提出了一种通过挖掘熟练驾驶员驾车行驶数据提取平直道路换挡规律的方法。首先,通过试验采集海量行驶数据,接着利用小波去噪、spearman相关性分析和信息增益计算提取平直道路行驶的3个最主要特征,最后通过对比6种机器学习算法在各挡位下对决策值(升挡、降挡和保持)的分类精度,选取精度最高的随机森林算法生成车速-加速踏板位置-发动机角加速度三参数换挡规律。仿真结果表明:该方法可有效收集平直道路下的熟练驾驶员换挡策略,提取的换挡规律油耗水平接近经济性换挡且动力性较好。

关键词: 换挡规律, 数据挖掘收集, 随机森林算法, 平直道路

Abstract:

In view of the poor adaptability of the shift schedule formulated based on vehicle dynamics, and the inability of gear decision model trained based on multidimensional data and intelligent algorithm in being directly applied to real vehicles, a method is proposed of extracting the shift schedule on flat-straight road by mining the driving data of skilled drivers. Firstly, a test is conducted to collect a large amount of driving data. Then three most important features of flat-straight road driving are extracted by using wavelet de-noising, spearman correlation analysis and information gain calculation. Finally, by comparing the classification accuracy of six machine learning algorithms for decision values (upshift, downshift and maintenance) in each gear, the random forest algorithm with the highest accuracy is selected to generate the three-parameter shift schedule, in which the parameters are vehicle speed, accelerator pedal position and engine angular acceleration. The simulation results show that this method can effectively collect the shift strategy of skilled drivers running on flat-straight road, and the shift schedule extracted achieves a fuel consumption level close to that with the economic shift strategy and a good power performance.

Key words: shift schedule, data mining, random forest algorithm, flat-straight road