主办：陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊：1976年
汽车实用技术

汽车实用技术 ›› 2022, Vol. 47 ›› Issue (19): 42-46.DOI: 10.16638/j.cnki.1671-7988.2022.019.009

• 设计研究 • 上一篇    

基于 Python 的 N2 类商用车制动距离计算的 线性回归优化

韩彦潇，何 果，李青章   

  1. 安徽江淮汽车集团股份有限公司
  • 出版日期:2022-10-15 发布日期:2022-10-15
  • 通讯作者: 韩彦潇
  • 作者简介:韩彦潇（1990—），男，工程师，研究方向为底盘制动系统，E-mail:hanyanxi.ao@163.com。

Linear Regression Optimization for Braking Distance Calculation of N2 Commercial Vehicles Based on Python

HAN Yanxiao, HE Guo, LI Qingzhang   

  1. Anhui Jianghuai Automobile Group Company Limited
  • Online:2022-10-15 Published:2022-10-15
  • Contact: HAN Yanxiao

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摘要： 制动距离是评价车辆制动性能的重要指标之一，文章深入研究了制动距离的计算方法， 分析其误差来源，并用试验数据验证了测试过程中由于驾驶员不能精确控制制动力而导致测 试结果误差大。为此运用 Python 语言的机器学习库用线性回归的优化方法对制动距离计算公 式进行了优化，可减小计算误差，提升计算结果的有效性。经过对比发现，优化后的制动距 离计算公式理论计算结果相对优化前对试验数据的拟合程度明显更高，在车辆开发过程中可 在设计阶段提升计算的准确性，缩短开发周期。

关键词: Python；制动距离计算；线性回归优化；N2 类商用车

Abstract: Braking distance is one of the important indicators to evaluate the braking performance of a vehicle. This paper deeply studies the calculation method of braking distance, analyzes the source of its error, and it is verified by the test data that the test result has a large error due to the driver's inability to precisely control the braking force during the test. Therefore, the machine learning library of python language is used to optimize the braking distance calculation formula with the optimization method of linear regression, which can reduce the calculation error and improve the validity of the calculation result. After comparison, it is found that the theoretical calculation results of the optimized braking distance calculation formula have a significantly higher degree of fitting to the test data than before the optimization. During the vehicle development process, the accuracy of the calculation can be improved in the design stage and the development cycle can be shortened.

Key words: Python; Braking distance calculation; Linear regression optimization; N2 commercial vehicle