|Table of Contents|

Multi-objective control and optimization of active energy-regenerative suspension based on road recognition(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2021年02期
Page:
129-137
Research Field:
载运工具运用工程
Publishing date:

Info

Title:
Multi-objective control and optimization of active energy-regenerative suspension based on road recognition
Author(s):
LI Yi-nong;  ZHU Zhe-wei;  ZHENG Ling;  HU Yi-ming
(College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400030, China)
Keywords:
automotive engineering;  electromagnetic active suspension;  nonlinear control model;  adaptive sliding mode control;  energy-regenerative suspension;  road recognition;  multi-objective particle swarm optimization
PACS:
U463.1
DOI:
10.19818/j.cnki.1671-1637.2021.02.011
Abstract:
For the problem that the vibration reduction performance and energy-regenerative characteristics of active suspension are less adaptable under different road classes, a nonlinear electromagnetic active suspension model was constructed. Considering the suspension sprung mass uncertainty during vehicle driving, an adaptive sliding mode controller of active suspension was proposed. An adaptive fuzzy neural network and the dynamics data of suspension under different roads were used to recognize road classes and determine the objective coefficient of the controller. Then, the coordination between safety and comfort of active suspension was realized. The energy-regeneration characteristics and switch control strategies of electromagnetic active suspension were studied. On this basis, the suspension dynamic performance and energy-regeneration characteristic were taken as the design objectives, and the contradictory relationships between the safety, comfort, and energy efficiency of electromagnetic active suspension were considered to comprehensively optimize the controller and suspension structure parameters through the multi-objective particle swarm optimization(MOPSO). The optimal solution was acquired from the Pareto solution set after the multi-objective optimization according to the fuzzy set theory. Research result reveals that the fuzzy neural network gives a maximum recognition error within 10% for various road classes when the nonlinear electromagnetic active suspension is employed. Thus, it meets the requirement of recognition accuracy. For C-class roads, the vibration acceleration of sprung mass of optimized active suspension reduces by 35.3% compared with the traditional passive suspension. The tire dynamic displacement increases by 7.7%, but it is still within 10%, ensuring safety. Compared with the original active suspension, the optimized suspension has 10.5% less sprung mass vibration acceleration and 1.7% higher energy-regeneration efficiency. The optimized adaptive sliding mode controller can better balance the energy-regeneration and vibration reduction characteristics of suspension. The established nonlinear electromagnetic active suspension model can realize the comprehensive optimization of safety, comfort, and energy efficiency of suspension system under different road classes. 5 tabs, 9 figs, 30 refs.

References:

[1] KARNOPP D, CROSBY M J, HARWOOD R A. Vibration control using semi-active force generators[J]. Journal of Engineering for Industry, 1974, 96(2): 619-626.
[2] 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]. Journal of Dynamic Systems, Measurement, and Control, 2002, 124(1): 158-167.
[3] VALÁEK M, NOVÁK M, IKA Z, et al. Extended
ground-hook-new concept of semi-active control of truck's suspension[J]. Vehicle System Dynamics, 1997, 27(5/6): 289-303.
[4] AHMADIAN M, PARE C A. A quarter-car experimental
analysis of alternative semiactive control methods[J]. Journal of Intelligent Material Systems and Structures, 2000, 11(8): 604-612.
[5] THOMPSON A. An active suspension with optimal linear
state feedback[J]. Vehicle System Dynamics, 1976, 5(4): 187-203.
[6] RIZVI S M H, ABID M, KHAN A Q, et al. H∞ control of 8 degrees of freedom vehicle active suspension system[J]. Journal of King Saud University—Engineering Sciences, 2016, 30(2): 161-169.
[7] 郑 玲,邓兆祥,李以农.汽车半主动悬架的滑模控制及鲁棒性[J].汽车工程,2004,26(6):678-682.
ZHENG Ling, DENG Zhao-xiang, LI Yi-nong. Sliding mode control for semi-active suspension systems and its robustness[J]. Automotive Engineering, 2004, 26(6): 678-682.(in Chinese)
[8] CHEN Xin-bo, WU Li-xin, YIN Jun, et al. Robust H∞ control design of an electromagnetic actuated active suspension considering the structure non-linearity[J]. Proceedings of the Institution of Mechanical Engineers Part D: Journal of Automobile Engineering, 2018, 233(3): 095440701775323.
[9] 罗 虹,陈 星,邓兆祥,等.主动悬架的直线电机作动器控制系统研究[J].系统仿真学报,2012,24(7):1537-1542.
LUO Hong, CHEN Xing, DENG Zhao-xiang, et al. Research on control system of linear motor actuator used in active suspension[J]. Journal of System Simulation, 2012, 24(7): 1537-1542.(in Chinese)
[10] KUMAR V, RANA K, KUMAR J, et al. Self-tuned robust fractional order fuzzy PD controller for uncertain and nonlinear active suspension system[J]. Neural Computing and Applications, 2018, 30(6): 1827-1843.
[11] BOUOUDEN S, CHADLI M, KARIMI R H. A robust
predictive control design for nonlinear active suspension systems[J]. Asian Journal of Control, 2016, 18(1): 122-132.
[12] LIU H, NONAMI K, HAGIWARA T. Active following
fuzzy output feedback sliding mode control of real-vehicle semi-active suspensions[J]. Journal of Sound and Vibration, 2008, 314(1/2): 39-52.
[13] LIN Jiong-kang, CHENG Ka-wai, ZHANG Zhu, et al. Adaptive sliding mode technique-based electromagnetic suspension system with linear switched reluctance actuator[J]. IET Electric Power Applications, 2015, 9(1): 50-59.
[14] SUN Hao, LI Yong-ming, XU Kun, et al. Fuzzy adaptive
backstepping control for a class of active suspension systems[J]. IFAC-Papers OnLine, 2018, 51(31): 136-141.
[15] LIU Bing, SAIF M, FAN Hui-jin, et al. Adaptive fault
tolerant control of a half-car active suspension systems subject to random actuator failures[J]. IEEE/ASME Transactions on Mechatronics, 2016, 21(6): 2847-2857.
[16] 王骏骋,何 仁.电动轮轮内主动减振器的非线性最优滑模模糊控制[J].汽车工程,2018,40(6):719-725.
WANG Jun-cheng, HE Ren. Nonlinear optimal sliding mode fuzzy control for in-wheel active vibration damper of electric wheel[J]. Automotive Engineering, 2018, 40(6): 719-725.(in Chinese)
[17] YAN Shu-ai, SUN Wei-chao. Self-powered suspension criterion and energy regeneration implementation scheme of motor-driven active suspension[J]. Mechanical Systems and Signal Processing, 2017, 94: 297-311.
[18] NAKANO K, SUDA Y, NAKADAI S. Self-powered active vibration control using a single electric actuator[J]. Journal of Sound and Vibration, 2003, 260(2): 213-235.
[19] ABOUELNOUR A, HAMMAD N. Electric utilization of
vehicle damper dissipated energy[J]. Electronics Research Institute, 2003, 25(6): 245-253.
[20] CHEN S A, LI X, ZHAO L J, et al. Development of a
control method for an electromagnetic semi-active suspension reclaiming energy with varying charge voltage in steps[J]. International Journal of Automotive Technology, 2015, 16(5): 765-773.
[21] GAO Ze-peng, CHEN Si-zhong, ZHAO Yu-zhuang, et al.
Numerical evaluation of compatibility between comfort and energy recovery based on energy flow mechanism inside electromagnetic active suspension[J]. Energy, 2019, 170: 521-536.
[22] 黄 昆,张勇超,喻 凡,等.电动式主动馈能悬架综合性能的协调性优化[J].上海交通大学学报,2009,43(2):226-230.
HUANG Kun, ZHANG Yong-chao, YU Fan, et al. Coordinate optimization for synthetical performance of electrical energy-regenerative active suspension[J]. Journal of Shanghai Jiaotong University, 2009, 43(2): 226-230.(in Chinese)
[23] 喻 凡,张勇超.馈能型车辆主动悬架技术[J].农业机械学报,2010,41(1):1-6.
YU Fan, ZHANG Yong-chao.Technology of regenerative vehicle active suspensions[J]. Transactions of the Chinese Society for Agricultural Machinery, 2010, 41(1): 1-6.(in Chinese)
[24] 秦也辰,董明明,赵 丰,等.基于路面识别的车辆半主动悬架控制[J].东北大学学报(自然科学版),2016,37(8):1138-1143.
QIN Ye-chen, DONG Ming-ming, ZHAO Feng, et al. Suspension semi-active control of vehicles based on road profile classification[J]. Journal of Northeastern University(Natural Science), 2016, 37(8): 1138-1143.(in Chinese)
[25] WANG Ruo-chen, DING Ren-kai, CHEN Long. Application of hybrid electromagnetic suspension in vibration energy regeneration and active control[J]. Journal of Vibration and Control, 2016, 24(1): 223-233.
[26] CHEN Shi-an, WANG Jun-cheng, YAO Ming, et al.
Improved optimal sliding mode control for a non-linear vehicle active suspension system[J]. Journal of Sound and Vibration, 2017, 395: 1-25.
[27] ATAEI M, ASADI E, GOODARZI A, et al. Multi-objective optimization of a hybrid electromagnetic suspension system for ride comfort, road holding and regenerated power[J]. Journal of Vibration and Control, 2017, 23(5): 782-793.
[28] KILICASLAN S. Control of active suspension system considering nonlinear actuator dynamics[J]. Nonlinear Dynamics, 2018, 91(1): 1383-1394.
[29] KOSHKOUEI A J, BURNHAM K J. Sliding mode controllers for active suspensions[C]∥IFAC. Proceedings of the 17th World Congress of the International Federation of Automatic Control. Seoul: IFAC, 2008: 3416-3421.
[30] 刘金琨,孙富春.滑模变结构控制理论及其算法研究与进展[J].控制理论与应用,2007,24(3):407-418.
LIU Jin-kun, SUN Fu-chun. Research and development on theory and algorithms of sliding mode control[J]. Control Theory and Applications, 2007, 24(3): 407-418.(in Chinese)

Memo

Memo:
-
Last Update: 2021-06-01