{"title":"A New Scheme for Semi-active Suspension Control based on BP Neural Network Model of Magnetorheological Damper","authors":"Honghui Zhang, Zhiyuan Zou, Hang Su","doi":"10.1109/CVCI51460.2020.9338564","DOIUrl":null,"url":null,"abstract":"Magnetorheological (MR) controllable damping is promising in suspension control and almost commercialized in luxuries. However, the development of MR semi-active control for vehicles is complicated because of the messed interdisciplinary process both in the suspension control and the MR damper control. In this paper, a new scheme of driving control based on BP neural network is proposed to package the MR damper as a black box implementing the strong nonlinearity mapping between the excitation current and damping force by the embedded driver. The sensor also embedded in the MR damper for integrated solution, and a mechanism for tackling the sedimentation problem of the MR damper are also pointed out.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVCI51460.2020.9338564","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Magnetorheological (MR) controllable damping is promising in suspension control and almost commercialized in luxuries. However, the development of MR semi-active control for vehicles is complicated because of the messed interdisciplinary process both in the suspension control and the MR damper control. In this paper, a new scheme of driving control based on BP neural network is proposed to package the MR damper as a black box implementing the strong nonlinearity mapping between the excitation current and damping force by the embedded driver. The sensor also embedded in the MR damper for integrated solution, and a mechanism for tackling the sedimentation problem of the MR damper are also pointed out.