基于滑模极值搜索的无级变速器夹紧力控制策略*
网络出版日期: 2017-02-20
基金资助
* 国家国际科技合作专项(2014DFA701700)和教育部“春晖计划”合作科研(Z2016023)资助项目; 20160712收到初稿,20161107收到修改稿;
Clamping Force Control Strategy of Continuously Variable Transmission Based on Extremum Seeking Control of Sliding Mode
Online published: 2017-02-20
针对无级变速器传统夹紧力控制进行优化,提出基于滑模极值搜索的控制策略。建立具有非线性、离散性的滑移率数学模型,并证明无级变速器传动效率和金属带滑移率在一定速比下存在的特殊关系,设计滑模极值搜索控制器。利用该控制器对滑移率最优区域进行监控搜索。通过振荡过滤干扰信号的方式,收敛获取到最优滑移率。其中,以系统失稳的临界值为约束目标,通过主动轮转矩较强的抗干扰能力,显示出该控制系统具有良好的鲁棒性。为验证夹紧力控制策略的有效性及可行性,建立仿真平台及实车试验平台。仿真及实车验证结果表明:滑模极值搜索控制与传统夹紧力控制相比较,传动效率提高7.98%~9.98%,燃油效率提高1.15%,ECE+EDUC工况下系统油耗降低约5.54%。滑模极值搜索控制算法的提出,为满足整车提高燃油经济需求的可靠性、稳定性及优化空间提出了一种新方法。
韩玲 , 安颖 , SOHELAnwar , 赵希禄 . 基于滑模极值搜索的无级变速器夹紧力控制策略*[J]. 机械工程学报, 2017 , 53(4) : 105 -113 . DOI: 10.3901/JME.2017.04.105
A control strategy based on extremum seeking of sliding mode is proposed to optimize conventional clamping force control of continuously variable transmission (CVT). The nonlinear and discrete mathematical model of slip rate is built to prove the special relationship between transmission efficiency of CVT and slip ratio of metal belt,and the extremum seeking of sliding mode controller is designed. The optimal regions of slip ratio are searched with this controller. The optimal slip ratio is got by concussion filtered interference signal. The critical value of system instability is the constraint object which shows the control system has good robustness by strong anti-interference ability of the driver torque. In order to verify the effectiveness and feasibility of clamping force control strategy,simulation platform and real vehicle test platform is established. Simulation and real vehicle verification results show that transmission efficiency is improved by 7.98%-9.98%,fuel efficiency is improved by 1.15%,and fuel consumption is reduced by about 5.54%. By comparisons between extremum seeking of sliding mode control and conventional clamping force control,the control strategy algorithm proposes a new method to meet the needs of improving fuel economy requirement and optimization space.
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