Oscillatory Yaw Motion Control for Hydraulic Power Steering Articulated Vehicles Considering the Influence of Varying Bulk Modulus

Gao, Yu; Shen, Yanhua; Xu, Tao; Zhang, Wenming; Güvenç, Levent

doi:10.1109/tcst.2018.2803746

Cited by 31 publications

(24 citation statements)

References 16 publications

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“…Hydraulic driving and controlling technologies are generally adopted in different walks of life, such as engineering construction, metallurgy, mining, national defense and materials. The oil acts as a crucial medium for the energy transmission and information coupling in the hydraulic transmission system, where its compressibility affects the stiffness [1]- [3], control accuracy [4], [5], dynamic and the nonlinear performance [6]- [9] of the system. Moreover, in the fields such as fault diagnosis [10], [11], condition monitoring [12], and reliability research, without paying attention to the nonstationary compressibility of the oil would cause misjudgment of the system running state.…”

Section: Introductionmentioning

confidence: 99%

Novel Methods for Modeling and Online Measurement of Effective Bulk Modulus of Flowing Oil

Geng

Liu

2020

IEEE Access

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Oil is a key medium for transmitting power and coupling information in the hydraulic transmission system. Accurate calculation and measurement of the dynamic compressibility of the oil have profound significance to the system performance analysis. The present study primarily focuses on the effect of steady pressure on the bulk modulus of static oil. However, changing pressure and flowing oil are the general working conditions in most of hydraulic apparatus. There are few researchers paying attention to the influence of pressure on the compressibility of flowing oil. Considering the log-normal distribution of bubble size in oil, an improved static oil model (Model B) is developed to calculate the bulk modulus of the motionless oil under the dynamic pressure. Then, by deriving Model B, this paper proposes an original flowing oil model (Model C) to determine the effective bulk modulus of flowing oil. Finally, based on the inherent pressure pulsation of the axial piston pump, an innovative online method for measurement of the bulk modulus of flowing oil is presented as it has the advantage of avoiding interference with flow stability. It has been proved that the changes in the flow velocity corresponds to the crucial effect on the effective bulk modulus of flowing oil, especially under the low-flow and low-pressure operation conditions. Those results and analysis provide promoting support for identifying and determining the effective bulk modulus of oil, analyzing the system stiffness, improving the control accuracy, as well as optimizing the mathematical models. INDEX TERMS Bulk modulus, bubble size distribution, flowing oil, online measurement.

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Section: Introductionmentioning

confidence: 99%

Novel Methods for Modeling and Online Measurement of Effective Bulk Modulus of Flowing Oil

Geng

Liu

2020

IEEE Access

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“…However, due to the special structure of two vehicle parts connected by two hydraulic struts and one articulation joint without locking mechanism [3][4][5] , the front and rear vehicle parts can rotate relatively, which easily make DAHVs produce oscillatory yaw motion during moving process, especially with the external disturbance. Moreover, the hydraulic struts is inevitably entrained with gas and produce leaks, which can decrease the vehicle torsional stiffness and increase the oscillatory yaw motion or even lead to instability for DAHVs [6,7] .…”

Section: Introductionmentioning

confidence: 99%

Differential Drive Based Yaw Stabilization Using MPC for Distributed-Drive Articulated Heavy Vehicle

Liu

et al. 2020

IEEE Access

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This paper presents a differential drive approach for distributed-drive articulated heavy vehicles (DAHVs) with wheel-side motors. The objective is to keep the yaw stability for DAHVs with direct yaw moment in driving process when the external disturbance acts on one of the vehicle parts. Three contributions are made in this paper: 1) An disturbance observer based Extended Kalman Filter (EKF) strategy is implemented to deal with the unknown mismatched disturbances in strong nonlinear vehicle system for DAHVs; 2) The differential drive approach is developed with the guidance of model predictive controller (MPC) to cope with the vehicle instability with the decoupling dynamic analyses of DAHVs under the observed external disturbance and the specific drive limitation of wheel-side motor for the first time; 3) The novel verification techniques with co-simulation model combining with the ADAMS, Simulink, and AMESim software for DAHVs is employed to verify this vehicle stability controller, which is more reasonable than the traditional methods with simple virtual model. The results demonstrate that the proposed approaches can reduce the oscillation amplitude and period of vehicle yaw motion for about 40% and 80%, respectively. Moreover, the MPC strategy is more efficient comparing with the LQR strategy especially on boundaries issue treatment, which can improve the vehicle stability greatly. INDEX TERMS Distributed-drive articulated heavy vehicle, model predictive controller, differential drive, yaw stabilization.

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“…Autonomous vehicles (AVs) are urgently needed to ensure that underground mines are safe and efficient [1,2]. As a typical and important kind of underground vehicle, underground articulated vehicles (UAVs) are widely used in underground mines due to their advantages of a higher maneuverability and efficiency [3]. Therefore, automated UAVs (AUAVs) have first priority in underground mines.…”

Section: Introductionmentioning

confidence: 99%

A Model-Based Method for Estimating the Attitude of Underground Articulated Vehicles

Gao

Jin

2019

Sensors

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This paper presents a novel model-based method for estimating the attitude of underground articulated vehicles (UAV). We selected the Load–Haul–Dump (LHD) vehicle as our application object, as it is a typical UAV. First, we established the involved models of the LHD vehicle, including a kinematic model, the linear and angular constraints of a center articulation model, and a dynamic four degrees-of-freedom (DOF) yaw model. Second, we designed a Kalman filter (KF) to integrate the kinematic and constraint models with the data from an inertial measurement unit (IMU), overcoming gyroscope drift and disturbances in external acceleration. In addition, we designed another KF to estimate the yaw based on the dynamic yaw model. The accuracy of the estimations was further enhanced by data fusion. Then, the proposed method was validated by a simulation and a field test under different dynamic conditions. The errors in the estimation of roll, pitch, and yaw were 3.8%, 2.4%, and 4.2%, respectively, in the field test. The estimated longitudinal acceleration was used to obtain the velocity of the LHD vehicle; the error was found to be 1.2%. A comparison of these results to those of other methods showed that the proposed method has high precision. The proposed model-based method will greatly benefit the location, navigation, and control of UAVs without any artificial infrastructure in a global positioning system (GPS)-free environment.

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Oscillatory Yaw Motion Control for Hydraulic Power Steering Articulated Vehicles Considering the Influence of Varying Bulk Modulus

Cited by 31 publications

References 16 publications

Novel Methods for Modeling and Online Measurement of Effective Bulk Modulus of Flowing Oil

Novel Methods for Modeling and Online Measurement of Effective Bulk Modulus of Flowing Oil

Differential Drive Based Yaw Stabilization Using MPC for Distributed-Drive Articulated Heavy Vehicle

A Model-Based Method for Estimating the Attitude of Underground Articulated Vehicles

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