CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model

Li Jie; Wang Shuai; Lan Hai; Wang Zhiyong

doi:10.16578/j.issn.1004.2539.2024.07.016

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CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model

Development·Application | 更新时间：2024-07-22

- CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model
- Journal of Mechanical Transmission Vol. 48, Issue 7, Pages: 128-136(2024)
- 作者机构：
  
  1.北京建筑大学机电与车辆工程学院，北京 102616
  2.中国北方车辆研究所车辆传动重点实验室，北京 100072
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2024.07.016
  CLC：
- Published：15 July 2024，
  
  Received：21 April 2023，
  
  Revised：25 April 2023，
- 稿件说明：
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李杰,王帅,兰海等.基于SSA-BP近似模型的湿式制动器带排转矩参数CSO智能优化[J].机械传动,2024,48(07):128-136.

Li Jie,Wang Shuai,Lan Hai,et al.CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model[J].Journal of Mechanical Transmission,2024,48(07):128-136.
李杰,王帅,兰海等.基于SSA-BP近似模型的湿式制动器带排转矩参数CSO智能优化[J].机械传动,2024,48(07):128-136. DOI： 10.16578/j.issn.1004.2539.2024.07.016.

Li Jie,Wang Shuai,Lan Hai,et al.CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model[J].Journal of Mechanical Transmission,2024,48(07):128-136. DOI： 10.16578/j.issn.1004.2539.2024.07.016.

摘要

针对湿式制动器在非制动工况下功率损失的工程问题，考虑摩擦副间隙内部的润滑油对摩擦副带排转矩的影响，运用麻雀搜索算法-反向传播（Sparrow Search Algorithm-Back Propagation，SSA-BP）神经网络的强大非线性拟合能力，以制动器空载工况为输入量、带排转矩为输出量，建立了湿式制动器近似模型；与传统的BP模型对比，该模型预测精度明显提高，更能满足实际工程的需要；同时，为获取最小带排转矩，采用鸡群优化（Chicken Swarm Optimization，CSO）智能算法对工况参数进行搜索寻优，得到湿式制动器的最佳工况。经试验测试验证，与优化前相比，优化后摩擦副间的带排转矩和功率损失有着明显降低。研究为湿式制动器结构的进一步优化提供了理论基础和工程实践经验。

Abstract

To solve the engineering problem of power loss in wet brakes under non-braking conditions

taking into consideration the influence of the lubricating oil in the clearance of friction pairs on the drag torque of the friction pair

making use of the strong nonlinear fitting ability of the sparrow-search-algorithm-back propagation (SSA-BP) neural network

and taking the no-load operating condition of wet brakes as the input variable and the drag torque as the output variable

an approximate model of wet brakes is established. Compared with the traditional BP model

the prediction accuracy is obviously improved

which can meet the needs of practical engineering. In order to obtain the minimum drag torque

the working parameters are searched and optimized through chicken swarm optimization （CSO） intelligent algorithm

and the best working condition of the wet brake is obtained. The experimental results show that the drag torque and power loss between the friction pairs after optimization are significantly lower than those before optimization. This study provides theoretical research basis and engineering practice experience for the further optimization of wet brake structure.

关键词

湿式制动器带排转矩SSA-BP模型CSO算法近似模型

Keywords

Wet brakeDrag torqueSSA-BP modelCSO algorithmApproximate model

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