Improved optimal sliding mode control for a non-linear vehicle active suspension system

Chen, Shi-An; Wang, Juncheng; Yao, Ming; Kim, Young‐Bae

doi:10.1016/j.jsv.2017.02.017

Cited by 119 publications

(74 citation statements)

References 21 publications

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“…where Q 13 is a 14×14 state variable weighting matrix. The main contribution of equation (25) incorporates not only Q, but also the expected performance information of N and R into state variable weighting matrix Q 13 .…”

Section: Iw Active Vibration System Based On the Fuzzy Optimal Slmentioning

confidence: 99%

Vertical vibration control of an in‐wheel motor‐driven electric vehicle using an in‐wheel active vibration system

Ren

Wang

2018

Asian Journal of Control

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The objective of this study is to present a novel in‐wheel (IW) active vibration system for an IW motor (IWM)‐driven electric vehicle to overcome the negative effects of vertical vibration due to road roughness and the impact of rotary inertial forces from the IWM. First, the reason for the poor ride comfort of the general electric wheel structure is examined by theoretical derivation. Second, a 6 degree‐of‐freedom (DOF) vehicle model is established and the corresponding cost function based on 10 ride comfort indexes is proposed. Third, a fuzzy optimal sliding mode (FOSM) control method is presented and the IW active vibration system is designed by applying this proposed control theory. Then, normalization and analytic hierarchy process (AHP) methodologies are adopted to select reasonable weighted coefficients of performance indexes. Finally, the advantages of the electric vehicle with the IW active vibration system are illustrated by MATLAB/Simulink. Analysis results demonstrate the feasibility and effectiveness of the proposed method.

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Section: Iw Active Vibration System Based On the Fuzzy Optimal Slmentioning

confidence: 99%

Vertical vibration control of an in‐wheel motor‐driven electric vehicle using an in‐wheel active vibration system

Ren

Wang

2018

Asian Journal of Control

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“…e traditional suspension is composed of spiral spring and hydraulic shock absorber. Its stiffness and damping coefficients cannot be changed with the road irregularity and driving condition, so further improvement performance is limited [4][5][6][7]. An active suspension system can meet the requirement of operational stability and driving safety by controlling [8][9][10][11] and has gradually become a more and more significant research field.…”

Section: Introductionmentioning

confidence: 99%

Thrust Ripple Force Minimization and Efficiency Analysis of Electromagnetic Actuator on Active Suspension

Kou

Yangkang

Chen

et al. 2020

Shock and Vibration

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A novel electromagnetic actuator for active suspension is designed on an in-wheel motor electric vehicle in this paper. Aiming at reducing thrust ripple force and improving stability of the actuator, a method of calculating the optimum slot width and optimizing edge radian of end tooth is proposed. Firstly, a finite element model (FEM) of the actuator is modeled, and the correctness of FEM is verified through comparisons of simulation results and analytical ones, including counterelectromotive force of coil winding and force characteristic test of the actuator. Based on the FEM, the influence of slot width on electromagnetic thrust and total harmonic distortion (THD) is analyzed, and the slot width is improved. The side effect of the actuator is considered. By improving the edge radian, the fluctuation of the cogging force and thrust ripple is reduced. In addition, output efficiency and energy feed efficiency of the actuator after reducing thrust ripple are studied. The results show the minimum THD is 4.2%, which is obtained at the slot width 4.3 mm, and thrust ripple is 36.5 N. When the edge radian is 60°, the thrust ripple decreases to only 15.7 N, which is reduced by 57.0%. The maximum output efficiency and energy feedback efficiency of the actuator are 87.5% and 27.1%, respectively. Finally, according to actuator characteristic tests of two working modes, it is concluded that the maximum energy feedback efficiency is 25.6%. The input current and current frequency should be gradually increased with the increase of suspension speed under active mode, and the maximum output efficiency is 80.2%. The test results are basically consistent with the FEM analysis values, which verify the correctness of the FEM analysis.

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“…In the past decades, a lot of research has been done to improve the performance of the vehicle suspensions [3]. However, heavy vehicle drivers, such as truck, SUV, crane, agricultural vehicle drivers, still suffer a lot from vehicle vibrations [4]. Therefore, seat suspensions are necessary for those heavy vehicles to improve the driving comfort [5].…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Sliding Mode PI Control for Active Vehicle Seat Suspension Systems

Ning

2019

2019 Chinese Control and Decision Conference (CCDC)

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In this paper, a robust adaptive sliding mode proportional integral control (RASMPIC) method is proposed for an active vehicle seat suspension system, where the driver's mass is supposed as an unknown parameter with boundaries. A dynamic active seat suspension system is established at first. Then a sliding mode controller (SMC) is designed to achieve the required ride comfort performance based on the driver's mass estimated by utilizing an adaptive law where a projecting adaptive algorithm is used to prevent the estimated parameters from surpassing their boundaries to enhance the robustness of the seat suspension system. Also, a proportional and integral (PI) control for driver's acceleration is added into the controller as RASMPIC for the stabilization of the proposed suspension system. In simulations, sinusoidal vibrations are used to test the controllers and the results show the RASMPIC has a better control performance to reduce driver's acceleration and improve the driving comfort than SMC and RASMC.Abstract: In this paper, a robust adaptive sliding mode proportional integral control (RASMPIC) method is proposed for an active vehicle seat suspension system, where the driver's mass is supposed as an unknown parameter with boundaries. A dynamic active seat suspension system is established at first. Then a sliding mode controller (SMC) is designed to achieve the required ride comfort performance based on the driver's mass estimated by utilizing an adaptive law where a projecting adaptive algorithm is used to prevent the estimated parameters from surpassing their boundaries to enhance the robustness of the seat suspension system. Also, a proportional and integral (PI) control for driver's acceleration is added into the controller as RASMPIC for the stabilization of the proposed suspension system. In simulations, sinusoidal vibrations are used to test the controllers and the results show the RASMPIC has a better control performance to reduce driver's acceleration and improve the driving comfort than SMC and RASMC.

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Improved optimal sliding mode control for a non-linear vehicle active suspension system

Cited by 119 publications

References 21 publications

Vertical vibration control of an in‐wheel motor‐driven electric vehicle using an in‐wheel active vibration system

Vertical vibration control of an in‐wheel motor‐driven electric vehicle using an in‐wheel active vibration system

Thrust Ripple Force Minimization and Efficiency Analysis of Electromagnetic Actuator on Active Suspension

Robust Adaptive Sliding Mode PI Control for Active Vehicle Seat Suspension Systems

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