摘要
搭载自动机械变速器(AMT)的车辆,其换挡规律是提升动力性与经济性的关键.本文以3挡AMT纯电动城市客车为研究对象,基于多目标粒子群算法(MOPSO)对不同加速踏板开度下的换挡车速进行优化,建立了兼顾动力性与经济性的双参数MOPSO换挡规律,并构建了以车辆载荷与加速度变化为输入,车速调整量为输出的模糊控制器对MOPSO规律进行自适应调整,得到了自适应换挡规律Fuzzy-MOPSO.最后,对Fuzzy-MOPSO规律开展了动力性与经济性验证,并与其他换挡规律进行比较.结果表明,Fuzzy-MOPSO规律的加速性能比经济性规律提升了15.3%,其动力性能比MOPSO规律更优越.经济性方面,在4段实际道路工况下,Fuzzy-MOPSO规律的经济性比动力性规律分别提升了6.08%、7.28%、6.88%、5.63%,比MOPSO规律更具节能潜力.此外,Fuzzy-MOPSO规律在实际道路工况下的换挡频率与MOPSO规律相当,节能的同时能够有效抑制频繁换挡,提升传动系统的寿命.
A shifting scheme is considerably crucial to promote the performance of the dynamic and economic for a vehicle equipped with automatic manual transmission(AMT).In this paper,a pure electric city bus with a three-speed AMT was researched.The shifting speed was optimized for different accelerator pedal openings,based on multi-objective particle swarm optimization(MOPSO),and a dual-parameter MOPSO shifting scheme was established to consider dynamic and economic performance simultaneously.Furthermore,a Fuzzy controller considering the changing of vehicle load and acceleration was introduced to adjust the MOPSO-based scheme,and the adaptive shifting scheme namely Fuzzy-MOPSO was obtained.Finally,the Fuzzy-MOPSO scheme was verified for both dynamic and economic performance and compared with other shifting schemes.The results demonstrate that the acceleration performance of the Fuzzy-MOPSO scheme is improved by 15.3%contrasted to the economic scheme,whilst it is also more excellent than the MOPSO scheme.In terms of economy,the economic performance of the Fuzzy-MOPSO scheme is respectively improved by 6.08%,7.28%,6.88%,and 5.63%compared with the dynamic scheme based on the four actual driving conditions.It has more energy-saving potential than the MOPSO scheme.Most importantly,the shifting frequency of Fuzzy-MOPSO is quite close to MOPSO.Fuzzy-MOPSO not only has a better energy-saving effect but also effectively reduces frequent shifting and improves the life of the transmission system.
作者
杜娟
杨振东
黄建刚
刘晓东
DU Juan;YANG Zhendong;HUANG Jiangang;LIU Xiaodong(School of Mechanical&Automotive Engineering,Liaocheng University,Liaocheng Shandong 252000,China;School of Automobiles,Dalian University of Technology,Dalian Liaoning 116204,China;Bus Research Institute,Zhongtong Bus Co.Ltd.,Liaocheng Shandong 252000,China;Key Laboratory for Automotive Transportation Safety Enhancement Technology of the Ministry of Communication,PRC,Chang an University,Xi an 710064,China)
出处
《西南大学学报（自然科学版）》
CAS
CSCD
北大核心
2024年第1期209-222,共14页
Journal of Southwest University(Natural Science Edition)
基金
国家重点研发计划项目(2021YFB2501201)
汽车运输安全保障技术交通行业重点实验室(长安大学)开放基金项目(300102221503/K21LC0301)
聊城大学博士科研启动基金项目(318052058).
关键词
多目标粒子群优化
模糊控制
AMT纯电动城市客车
自适应换挡规律
multi-objective particle swarm optimization
fuzzy control
AMT pure electric city bus
adaptive shifting scheme
