System Identification and Optimal Control of Half-Car Active Suspension System Using a Single Noisy IMU With Position Uncertainty

2017 ◽  
Author(s):  
Tamer Attia ◽  
Kevin Kochersberger ◽  
John Bird ◽  
Steve C. Southward
Keyword(s):  
System Identification ◽  
Channel Model ◽  
Ride Comfort ◽  
Active Suspension ◽  
Measurement Unit ◽  
Linear Quadratic ◽  
Position Uncertainty ◽  
Inertial Measurement ◽  
Handling Characteristics ◽  
Frequency Domain Methods

An active suspension based on Linear Quadratic Gaussian (LQG) optimal controller is an effective system for enhancing the ride comfort and handling characteristics of a vehicle. LQG requires a good plant model for success, and this may be difficult to extract using a single inertial measurement device in the presence of noise. This paper presents a method for estimating the vehicle states by measuring both the vehicle bounce and pitch accelerations using an Inertial Measurement Unit (IMU) with position uncertainty relative to the sprung mass center of gravity. Frequency domain methods are used for System Identification (SysId). The state estimation is based on channel-by-channel model estimation using uncorrelated random excitation which is applied to the front wheels, rear wheels, front actuator, and rear actuator. An anti-aliasing filter eliminates false response harmonics and a Kalman filter is used to estimate the current states of the actual plant and the LQR block for the full-states-feedback controller. The controllers and observer are implemented in simulation using a four degree-of-freedom half car linear model.

scholarly journals Active Suspension Control Strategy of Multi-Axle Emergency Rescue Vehicle Based on Inertial Measurement Unit

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6877
Author(s):  
Qinghe Guo ◽  
Dingxuan Zhao ◽  
Xiaolong Zhao ◽  
Zhenxing Li ◽  
Xiaobo Shi
Keyword(s):  
Control Strategy ◽  
Parallel Mechanism ◽  
Inertial Measurement Unit ◽  
Ride Comfort ◽  
Active Suspension ◽  
Vehicle Body ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Suspension Control ◽  
Pneumatic Suspension

Active suspension control strategies are a top priority in active suspension system. The current research on active suspension control strategies is mostly focused on two-axle vehicles, and there is less research investigating multi-axle vehicles. Additionally, their effective implementation is dependent on accurate mathematical models, and most of them adopt force feedback control, which is vulnerable to external interference. To solve these problems, this paper proposes an active suspension control strategy based on Inertial Measurement Unit. The multi-axle emergency rescue vehicle is made to be equivalent to a 3-degrees-of-freedom parallel mechanism by using the method of grouping and interconnecting the suspension units of the whole vehicle. The attitude change of the vehicle body was transformed into the servo actuator’s displacement by solving the inverse solution of the parallel mechanism position and the action of the servo actuator was driven in reverse according to the displacement obtained. In this way, the vehicle body attitude can be compensated, and the ride comfort and the handling stability of the vehicle can be improved. To verify the effectiveness of the control strategy proposed, the three-axle six vehicle was taken as the research object, the position inverse solution of its equivalent 3-degrees-of-freedom parallel mechanism was deduced, and a high-pass filter was designed. The three-axle vehicle experiment platform integrating active suspension and hydro-pneumatic suspension was built, and the gravel road and slope road experiments were carried out and the results compared with those obtained with hydro-pneumatic suspension. The experiment results showed that, compared with hydro-pneumatic suspension, the active suspension control strategy based on Inertial Measurement Unit proposed in this paper can not only stabilize the body attitude, but also effectively suppress body vibration, improving the ride comfort and handling stability of the vehicle significantly.

Improvement on Ride Comfort of Quarter-Car Active Suspension System Using Linear Quadratic Regulator

2018 ◽  
pp. 431-441
Author(s):  
Sharifah Munawwarah Syed Mohd Putra ◽  
Fitri Yakub ◽  
Mohamed Sukri Mat Ali ◽  
Noor Fawazi Mohd Noor Rudin ◽  
Zainudin A. Rasid ◽  
...  
Keyword(s):  
Ride Comfort ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Suspension System ◽  
Linear Quadratic ◽  
Quarter Car

Analytical and Experimental Evaluation of Various Active Suspension Alternatives for Superior Ride Comfort and Utilization of Autonomous Vehicles

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Ivan Cvok ◽  
Mario Hrgetić ◽  
Matija Hoić ◽  
Joško Deur ◽  
Davor Hrovat ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
High Performance ◽  
Ride Comfort ◽  
Simulation Analysis ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Vertical Acceleration ◽  
Linear Quadratic ◽  
Seat Suspension ◽  
Road Disturbance

Abstract Autonomous vehicles (AVs) give the driver opportunity to engage in productive or pleasure-related activities, which will increase AV’s utility and value. It is anticipated that many AVs will be equipped with active suspension extended with road disturbance preview capability to provide the necessary superior ride comfort resulting in almost steady work or play platform. This article deals with assessing the benefits of introducing various active suspensions and related linear quadratic regulator (LQR) controls in terms of improving the work/leisure ability. The study relies on high-performance shaker rig-based tests of a group of 44 drivers involved in reading/writing, drawing, and subjective ride comfort rating tasks. The test results indicate that there is a threshold of root-mean-square vertical acceleration, below which the task execution performance is similar to that corresponding to standstill conditions. For the given, relatively harsh road disturbance profile, only the fully active suspension with road preview control can suppress the vertical acceleration below the above critical superior comfort threshold. However, when adding an active seat suspension, the range of chassis suspension types for superior ride comfort is substantially extended and can include semi-active suspension and even passive suspension in some extreme cases that can, however, lead to excessive relative motion between the seat and the vehicle floor. The design requirements gained through simulation analysis, and extended with cost and packaging requirements related to passenger car applications, have guided design of two active seat suspension concepts applicable to the shaker rig and production vehicles.

scholarly journals Design of Static Output Feedback and Structured Controllers for Active Suspension with Quarter-Car Model

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8231
Author(s):  
Manbok Park ◽  
Seongjin Yim
Keyword(s):  
Output Feedback ◽  
Ride Comfort ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Static Output Feedback ◽  
State Variables ◽  
Linear Quadratic ◽  
Suspension Control ◽  
Quarter Car ◽  
Static Output

This paper presents a method to design active suspension controllers for a 7-Degree-of-Freedom (DOF) full-car (FC) model from controllers designed with a 2-DOF quarter-car (QC) one. A linear quadratic regulator (LQR) with 7-DOF FC model has been widely used for active suspension control. However, it is too hard to implement the LQR in real vehicles because it requires so many state variables to be precisely measured and has so many elements to be implemented in the gain matrix of the LQR. To cope with the problem, a 2-DOF QC model describing vertical motions of sprung and unsprung masses is adopted for controller design. LQR designed with the QC model has a simpler structure and much smaller number of gain elements than that designed with the FC one. In this paper, several controllers for the FC model are derived from LQR designed with the QC model. These controllers can give equivalent or better performance than that designed with the FC model in terms of ride comfort. In order to use available sensor signals instead of using full-state feedback for active suspension control, LQ static output feedback (SOF) and linear quadratic Gaussian (LQG) controllers are designed with the QC model. From these controllers, observer-based controllers for the FC model are also derived. To verify the performance of the controllers for the FC model derived from LQR and LQ SOF ones designed with the QC model, frequency domain analysis is undertaken. From the analysis, it is confirmed that the controllers for the FC model derived from LQ and LQ SOF ones designed with the QC model can give equivalent performance to those designed with the FC one in terms of ride comfort.

Efficiency improvement of vehicle active suspension based on multi-objective integrated optimization

2016 ◽  
Vol 23 (4) ◽  
pp. 539-554 ◽  
Author(s):  
Wei Sun ◽  
Yinong Li ◽  
Jingying Huang ◽  
Nong Zhang
Keyword(s):  
Pareto Optimality ◽  
Degrees Of Freedom ◽  
Ride Comfort ◽  
Capacity Utilization ◽  
Active Suspension ◽  
Multiple Objectives ◽  
Utilization Rate ◽  
Linear Quadratic ◽  
Comprehensive Comparison ◽  
Suspension Performance

Active suspension can effectively resolve the contradictions between vehicle ride comfort and stability. However, a new contradiction between the active suspension performance and efficiency is aroused. Active suspension with excellent performance requires high actuation power and force in an aggressive condition, which is usually an excess capacity for normal conditions. To improve the efficiency and capacity utilization rate, this paper conducted an investigation on the efficiency and utilization rate of vehicle active suspension based on a seven degrees-of-freedom full vehicle mode with a linear quadratic Gaussian active suspension controller. The multiple objectives of active suspension performance and efficiency are integrally optimized via genetic algorithm with an elaborately designed penalty function. The proposed integration of multiple objectives is proved effective according to the comprehensive comparison analysis. The overall performance of the optimized suspension achieved the Pareto optimality. Not only a better balance between the ride comfort and stability is accomplished, but also the active suspension utilization rate is improved. By this method, the obtained Pareto optimality set can greatly improve the parameters matching and design of the active suspension.

scholarly journals Optimal Control of an 8-DOF Vehicle Active Suspension System Using Kalman Observer

2008 ◽  
Vol 15 (5) ◽  
pp. 493-503 ◽  
Author(s):  
S. Hossein Sadati ◽  
Salar Malekzadeh ◽  
Masood Ghasemi
Keyword(s):  
Optimal Control ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
The Body ◽  
Control Approach ◽  
Seat Suspension ◽  
Handling Characteristics ◽  
Road Profile ◽  
Passive Suspension System

In this paper, an 8-DOF model including driver seat dynamics, subjected to random road disturbances is used in order to investigate the advantage of active over conventional passive suspension system. Force actuators are mounted parallel to the body suspensions and the driver seat suspension. An optimal control approach is taken in the active suspension used in the vehicle. The performance index for the optimal control design is a quantification of both ride comfort and road handling. To simulate the real road profile condition, stochastic inputs are applied. Due to practical limitations, not all the states of the system required for the state-feedback controller are measurable, and hence must be estimated with an observer. In this paper, to have the best estimation, an optimal Kalman observer is used. The simulation results indicate that an optimal observer-based controller causes both excellent ride comfort and road handling characteristics.

Semi-Active Suspension Suboptimal Control Using Dynamic Programming of a Quarter Car Suspension System

2016 ◽  
Author(s):  
John Dye ◽  
Nathan BuchMueller ◽  
Hamid Lankarani
Keyword(s):  
Cost Function ◽  
Vehicle Dynamics ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suboptimal Control ◽  
Damping Coefficient ◽  
Handling Characteristics ◽  
Car Suspension ◽  
Quarter Car ◽  
The Cost

Many modern vehicle control systems utilize automatic braking and torque control to enhance driver inputs for improved stability and deceleration performance of passenger cars. A semi-active suspension approach may allow changes to the suspension characteristics under various conditions or driver inputs during vehicle operation. Suspensions are increasingly using semi active components to enhance handling characteristics by electronically adjusting vehicle dynamics. The active style of adjustment includes modifying suspension parameters directly such as electronic damping rates. The type of controller is important to react or adjust dynamically to the nonlinear nature of suspension systems. An optimal controller is introduced in attempt to improve ride comfort or road handling capability by manipulating the damping coefficient for a given trajectory. A suboptimal approach is given by utilizing a type of receding horizon control. The cost function, as used by Savaresi, contains a bias parameter to shift focus between road holding and passenger comfort. A dynamic quarter car suspension model is presented for simulation of nonlinear vehicle dynamics. During simulation at a given time step, various control inputs are simulated for finite steps into the future. The control input that minimizes the cost function is selected and the simulation time is allowed to advance with that input. The model is simulated using parameters for a typical passenger car and a 100 millisecond update rate from the suboptimal controller. A road profile with a bump is simulated and its transients are analyzed. The suboptimal controller is compared to its purely mechanical realization with a fixed damping coefficient. It is shown when manipulating the cost function ride comfort is desired chassis accelerations are minimized and when maximum road holding is desired tire deflection is minimized.

System Identification of an Open-Frame ROV Using a Low-Cost Inertial Measurement Unit

2004 ◽  
Vol 37 (14) ◽  
pp. 157-162
Author(s):  
Nathan W.A. Sowerby ◽  
Geoff N. Roberts ◽  
Gurvinder S. Baicher
Keyword(s):  
System Identification ◽  
Inertial Measurement Unit ◽  
Low Cost ◽  
Measurement Unit ◽  
Inertial Measurement

A Distributed Sensing System for Vehicles State Estimation

2006 ◽  
Author(s):  
Hamidreza Bolandhemmat ◽  
Christopher M. Clark ◽  
M. F. Golnaraghi
Keyword(s):  
State Estimation ◽  
Ride Comfort ◽  
Active Suspension ◽  
Distributed Sensing ◽  
Measurement Unit ◽  
Accurate Information ◽  
Suspension Systems ◽  
Sensing System ◽  
Angular Velocities ◽  
Vehicle State Estimation

This paper presents the design of a distributed sensing system that uses an Extended Kalman Filter (EKF) to fuse measurements, so that automotive vehicle states can be estimated for use by a Semi-active Suspension control system. To improve ride comfort and handling quality, relative displacements and velocities of suspension systems are estimated. To control the stability of vehicles, roll, yaw, and pitch must also be determined. The designed (EKF) uses easily accessible measurements such as accelerations and body's angular velocities. These measurements are provided by 8 accelerometers and an Inertial Measurement Unit (IMU). The accelerometers are strategically mounted on the two ends of each individual shock absorber (damper). The IMU was mounted near the vehicle's center of gravity. Computer simulations and experiments were conducted for full vehicle state estimation of a 1993 Toyota Tercel equipped with the above mentioned sensor suite. Results show that except relative displacements, all states of the automobile's semi-active suspension systems can be estimated using this set of sensors. The designed EKF works well despite not knowing accurate information about road inputs, external disturbances and car characteristics such as moments of inertia, mass, and equivalent spring and damping coefficients. Both simulation results and experimental results show the effectiveness of the designed EKF in estimating the required states.

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