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          華中科技大學學報(自然科學版) 2020, Vol. 48 Issue (12): 49-54 DOI10.13245/j.hust.201209

          欄目:機械工程
          基于卡爾曼觀測器的磁流變懸架半主動控制
          汪若塵 , 王英杰 , 丁仁凱 , 孫 東
          江蘇大學汽車與交通工程學院,江蘇 鎮江 212013
          摘要 考慮磁流變阻尼器磁飽和特性這一非線性因素,設計了一種基于微分幾何理論的反饋線性化卡爾曼觀測器(FLKO),進行了磁流變阻尼器力學試驗并建模,進而設計了非線性懸架系統卡爾曼觀測器,開展了觀測器仿真分析.FLKO對懸架控制算法所需狀態變量的估計精度都超過85%,能夠滿足懸架控制器使用要求.為驗證FLKO實際工作效果,開發了懸架電子控制單元(ECU),搭建了1/4懸架臺架進行臺架試驗.試驗結果表明:C級隨機路面下,帶有FLKO的磁流變半主動懸架車身加速度和懸架動撓度相比被動懸架降低了12.57%和7.32%,車輛乘坐舒適性明顯改善.
          關鍵詞 半主動懸架 ;控制算法 ;磁流變阻尼器 ;狀態觀測 ;試驗
          Research on semi-active control of magnetorheological suspension based on Kalman observation
          WANG Ruochen , WANG Yingjie , DING Renkai , SUN Dong
          School of Automotive and Traffic Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu China
          Abstract The feedback linearization Kalman observer (FLKO) based on differential geometry theory was designed,considering the nonlinear factor of magnetic saturation characteristics of magnetorheological damper.The damper was experimented mechanically and modelled.FLKO of nonlinear suspension system was designed.Simulation and analysis of FLKO was carried out.The results show that estimation accuracy of state variables exceeds 85%,which can meet the requirements of suspension controller.To verify the actual working effect of FLKO,a suspension ECU (electronic control unit) was developed,and a 1/4 suspension bench was built for bench test.The test results show that body acceleration and suspension stroke with FLKO are reduced by 12.57% and 7.32% compared to the passive suspension on the C-level random road,and ride comfort of vehicles is significantly improved.
          Keywords semi-active suspension ; control algorithm ; magnetorheological damper ; state observation ; Fourier transform ; experiment
          基金資助國家自然科學基金面上項目(51575240).

          中圖分類號U463.33
          文獻標志碼A
          文章編號1671-4512(2020)12-0049-06
          參考文獻
          [1]陳兵.車輛智能懸架系統發展趨勢研究[J].起重運輸機械,2005(6):1-6.
          [2]王凱.基于自適應遺傳算法的整車主動懸架自抗擾控制研究[D].長春:吉林大學圖書館,2017.
          [3]秦也辰,董明明,趙豐,等.基于路面識別的車輛半主動懸架控制[J].東北大學學報(自然科學版),2016,37(8):1138-1143.
          [4]李靜,王子涵,秦民,等.基于SimScape的半主動懸架垂直速度處理電路設計[J].吉林大學學報(工學版),2014,44(4):912-917.
          [5]王平.基于零相位濾波器的變轉速液壓系統控制性能實驗研究[D].西安:長安大學圖書館,2018.
          [6]VAN C N.State estimation based on sigma point Kalman filter for suspension system in presence of road excitation influenced by velocity of the car[J/OL].Journal of Con- trol Science and Engineering,2019,2019:1-16.https:// www. hindawi.com/journals/jcse/2019/6898756/.
          [7]CSEKO L H,KVASNICA M,LANTOS B.Explicit MPC-based RBF neural network controller design with discrete-time actual Kalman filter for semiactive sus- pension[J].IEEE Transactions on Control Systems Technology,2015,23(5):1-18.
          [8]FAN Y,REN H,CHEN S,et al.Observer design based on nonlinear suspension model with unscented Kalman filter[J].Journal of Vibroengineering,2015,17(7):3392-4056.
          [9]段敏,蘇海華.汽車磁流變減振器多項式模型的研究[J].遼寧工業大學學報(自然科學版),2010,30(6):377-381.
          [10]HONG K S,SOHN H C,HEDRICK J K.Modified skyhook control of semi-active suspensions:a new model,gain scheduling,and hardware-in-the-loop tuning[J].J Dyn Sys,Meas,Control,2000,124(1):158-167.
          [11]HOU M,PUGH A C.Observer with linear error dynamics for nonlinear multi-output systems[J].Systems & Control Letters,1999,37(1):1-9.
          [12]陳永林.廣義逆矩陣的理論與方法[M].南京:南京師范大學出版社,2005.
          [13]MA CK,CHANG J M,LIN D C.Input forces estimation of beam structures by an inverse method[J].Journal of Sound and Vibration,2003,259(2):387-407.
          文獻來源
          汪若塵, 王英杰, 丁仁凱, 孫 東. 基于卡爾曼觀測器的磁流變懸架半主動控制[J]. 華中科技大學學報(自然科學版), 2020, 48(12): 49-54
          DOI:10.13245/j.hust.201209
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