Semi-active Suspension Control Research Articles

Fuzzy sliding mode control of automotive semi-active suspension based on optimization convergence law

Vehicle suspension smoothness and stability are important indicators for evaluating vehicles. This paper firstly establishes a 1/4 automobile semi-active suspension model, which is used as a reference model for comparison by optimizing the canopy model, and secondly designs the sliding mode controller, including the tracking model error design and the control system design, and then incorporates the optimized saturation function convergence law to control the convergence speed, and then combines it with the fuzzy control to improve the accuracy and robustness of the control system. The optimized semi-active suspension control system will enhance the vehicle’s vibration, smoothness, and stability. The final simulation test results show that the optimized sliding mode control suspension body vertical acceleration is reduced by 26.9%, suspension dynamic deflection by 36.7%, and tire dynamic load dynamic load is reduced by 28.4%.

The Adverse Effect and Control of Semi-active Inertial Suspension of Hub Motor Driven Vehicles

The Adverse Effect and Control of Semi-active Inertial Suspension of Hub Motor Driven Vehicles

A Review on Controlling Methods for Semi-Active Suspension Systems

Abstract: In recent years the need of vehicle safety and ride comfort has led to develop effective modeling and control methods of suspension system. There are many methods already found to develop and control this kind of suspension systems. Mainly there are three types ofsuspension systems, Active, Semi-Active and Passive suspensions. This research paper presents a comprehensive review of controlling methods employed in semi-active suspension systems, a critical component in modern vehicle dynamics. Out of these three, semi-active suspension has the ability to adapt with the technical changes in the system model. In this paper some of the control methods for the semi-active suspension system have been discussed and a quick review is done on their way of operation. Moreover, the paper addresses recent advancements in semi-active suspension control, such as the integration of machine learning and optimization techniques.

Correction: Vibration analysis and control of semi-active suspension system based on continuous damping control shock absorber

Correction: Vibration analysis and control of semi-active suspension system based on continuous damping control shock absorber

Adaptive optimal fault-tolerant vibration control and sensitivity analysis of semi-active suspension based on a self-powered magneto-rheological damper

To reuse the energy dissipated by vehicle suspension, a semi-active suspension with a self-powered magneto-rheological damper is proposed. An electromechanical coupling model of self-powered semi-active suspension is established. The energy conversion efficiency is defined and investigated by changing the electrical parameters. By considering unmodeled dynamics and perturbation values, an adaptive optimal fault-tolerant control algorithm is proposed to ensure the vibration-isolation performance. The robust index of the adaptive optimal fault-tolerant control algorithm is constructed using the Lyapunov equation and evaluated by changing the key parameters. The sensitivity of the key parameters to the damping force is investigated using a grey relation analysis approach. Furthermore, multi-objective optimization between the vibration-isolation capability and energy harvesting is conducted. Via analysis, the proposed suspension can harvest more energy near the second resonance range. Compared to passive control and self-powered mode, the adaptive optimal control algorithm mitigates vibration more significantly in the time and frequency domains, respectively, under stochastic excitation. The robust index is most sensitive to inductance and the diameter of the magnetism cylinder. The length of the damping channel and the diameter of the magnetism cylinder influence the sensitivity of key parameters to the damping force most obviously.

Research on variable universe fuzzy PID control for semi-active suspension with CDC dampers based on dynamic adjustment functions

The vehicle suspension system is a complex system with multiple variables, nonlinearity and time-varying characteristics, and the traditional variable universe fuzzy PID control algorithm has the problems of over-reliance on expert experience and non-adaptive adjustment of the contracting-expanding factor parameters, which make it difficult to achieve a better control effect. In this paper, the system error e(t) and its change rate ec(t) are introduced into the contracting-expanding factor as dynamic parameters to realize the adaptive adjustment of the contracting-expanding factor parameters, and propose a variable universe fuzzy PID control based on dynamic adjustment functions (VUFP-DAF), which uses the real-time contracting-expanding factor to realize the adaptive adjustment of the fuzzy universe, so as to improve the ride comfort of vehicles. The research results show that the proposed VUFP-DAF has strong adaptability and can effectively improve the ride comfort and handling stability of vehicles under different speeds and road excitations, providing a certain technical basis for the development of the semi-active suspension system.

Analysis of damping multi-mode switching control of semi-active suspension based on digital controlled hydraulic cylinders group

In order to improve the ride comfort of vehicle suspension, this article proposes a damping multi-mode semi-active suspension system and its control method. The semi-active suspension takes a hydraulic electromagnetic shock absorber based on a digital controlled hydraulic cylinders group as the core, and realizes the switching of multiple damping modes by controlling the on-off statuses of three groups of switch solenoid valves, thus making the semi-active suspension have the characteristics of damping multi-mode adjustable. The damping characteristics corresponding to the single damping mode are verified through the prototype bench test of the shock absorber principle. On this basis, the semi-active suspension model of the vehicle is established, and a multi-mode switching control strategy of suspension damping using fuzzy control is designed. The filtered Gaussian white noise is used as the random road excitation for simulation. The simulation results show that compared with the traditional passive suspension and the semi-active suspension based on skyhook control, the damping multi-mode semi-active suspension based on the digital controlled hydraulic cylinders group can realize the switching of multiple damping modes, have good damping performance, and help to improve the vehicle ride comfortable capability.

Robust predictive compensation control for lateral magnetorheological semi-active suspension of high-speed trains with time delay

ABSTRACT Aiming at reducing the effect of time delay on the control performance of magnetorheological (MR) damper semi-active suspension, a control strategy with strong robustness to time delay is investigated in this study, including the force controller of MR damper, the robust controller and the predictive compensator. The force controller of MR damper is built based on the hyperbolic tangent function; the robust controller is built based on the simplified model of car body lateral vibration and is designed by μ-synthesis method considering the effect of time delay; then the Smith predictive model and the lateral velocity predictor are designed, which form the predictive compensator of semi-active controller to reduce the effect of time delay. To validate the effectiveness of the proposed control strategy, several conventional semi-active controllers are designed as comparative objects. The simulation results show that the proposed semi-active control strategy can maintain good performance when time delay is in the range of 0–100 ms and has better robustness to time delay compared with the conventional control strategy.

Research on Two-Stage Semi-Active ISD Suspension Based on Improved Fuzzy Neural Network PID Control.

To better improve the ride comfort and handling stability of vehicles, a new two-stage ISD semi-active suspension structure is designed, which consists of the three elements, including an adjustable damper, spring, and inerter. Meanwhile, a new semi-active ISD suspension control strategy is proposed based on this structure. Firstly, the fuzzy neural network's initial parameters are optimized using the grey wolf optimization algorithm. Then, the fuzzy neural network with the optimal parameters is adjusted to the PID parameters. Finally, a 1/4 2-degree-of-freedom ISD semi-active suspension model is constructed in Matlab/Simulink, and the dynamics simulation is carried out for the three schemes using PID control, fuzzy neural network PID control, and improved fuzzy neural network PID control, respectively. The results show that compared with adopting PID control and fuzzy neural network PID control strategy, the vehicle body acceleration and tire dynamic loads are significantly reduced after using the grey wolf optimized fuzzy neural network PID control strategy, which shows that the control strategy proposed in this paper can significantly improve the vehicle smoothness and the stability of the handling.

Design and Research of a Two Level Fuzzy PID Electronic Control System for Automotive Semi-Active Suspension

In response to the problem of outdated traditional PID control performance and excessively single control parameters in automotive suspension, a two level fuzzy PID control system for automotive semi-active suspension is proposed. The system has two control loops: the first level control loop is PID control, and the second level control loop is fuzzy control. The second level control loop fully utilizes the motion state of unsprung mass that affects the comprehensive performance of the suspension to achieve fine adjustments to the PID controller control parameters in the first level control loop, making the PID controller control parameters more suitable for adjusting suspension performance after hierarchical adjustment, thereby achieving the goal of improving ride comfort. The analysis data shows that the control performance of the two level fuzzy PID control system is significantly better than that of the PID control system, and the comprehensive performance of the suspension and ride comfort has been significantly improved.

Gray skyhook predictive control of magnetorheological semi-active seat suspension with time delay

Semi-active seat suspension with a magnetorheological (MR) damper has been a popular study issue in recent years. Since the response time delay of the MR damper can reduce the control effect and even make the vibration more severe, there is an urgent need to compensate for the response time delay. In this paper, gray prediction is introduced into the vibration control study of commercial vehicle seat suspension. A gray skyhook prediction controller is designed to compensate for the response time delay. This proposed controller does not rely heavily on controller parameter optimization and requires fewer state variables than other typical time delay compensation controllers. The mechanical property of the MR damper has been tested, modeled, and analyzed. A seat suspension dynamic model considering geometric nonlinearity is established based on the motion relationship between the components of the suspension. Subsequently, the effect of the response time delay on seat suspension vibration control has been verified by simulation. The results show that the control effect deteriorates significantly after considering the response time delay. Finally, prediction accuracy and vibration reduction performance of the designed gray skyhook predictive controller are verified by simulation and bench testing. The results illustrate that the gray skyhook predictive controller provides excellent time delay compensation and can significantly improve the ride comfort and handling stability of the driver. This study provides a reference for vibration control research of the MR seat suspension.

Tuning Parameters of the Fractional Order PID-LQR Controller for Semi-Active Suspension

In order to further improve the control effect of proportion integral differential (PID) control and linear quadratic regulator (LQC) control, and improve vehicle ride comfort and enhance body stability, the 7 DOF semi-active suspension model was established, and the fractional order PIλDμ-LQR controller was designed by combining fractional order PIλDμ control theory and LQR control theory. The semi-active suspension model in this paper is more complex, and there are many parameters in the controller. The optimal weighting coefficient of 12 vehicle smoothness evaluation indicators and parameters Kp, Ki, Kd, λ and μ in the controller were founded by NSGA-II algorithm. After optimization, the optimized parameters were brought into the controller for random pavement simulation. Compared to the traditional passive suspension, fractional order PIλDμ individual control and LQR separate control, the simulation results show that the effect of fractional order PIλDμ-LQR control is very significant. The evaluation index of vehicle smoothness has been significantly improved, and the use of fractional order PIλDμ-LQR control has significantly improved the working performance of the suspension and improved the smoothness of the vehicle. At the same time, the adjusting force output of the actuator is very balanced, which inhibits the roll of the body and improves the anti-roll performance. After simulation, the excellent performance of the designed fractional PIλDμ-LQR controller was verified, and the introduced NSGA-II algorithm played an important role in the controller parameter tuning work, which shows that the fractional order PIλDμ-LQR controller and NSGA-II algorithm cooperate with each other to achieve good control effects.

Nonlinear dynamic modeling and analysis of magnetorheological semi-active suspension for tracked vehicles

The magnetorheological technology has been widely used in automotive applications, whereas less research has been done on tracked vehicles. Hence, this research focuses on the dynamic modeling of the whole system of a tracked vehicle, for analyzing the effect of magnetorheological semi-active suspension on track tension and chassis vibration during driving. Applying the multibody system transfer matrix method and a dynamic recursive method, the dynamic models of the chassis subsystem and the double track subsystems are developed, respectively. These three subsystems are coupled by nonlinear contact forces, where the meshing shock, polygon effect, and rolling effect during contact are also taken into consideration. Subsequently, the normalized Bouc-Wen model is adopted to describe the nonlinear characteristics of rotary magnetorheological dampers. Then, a semi-active suspension control of the tracked vehicle is implemented with rotary magnetorheological dampers and the independent skyhook control method. Finally, numerical simulations are performed under different operating conditions. Comparing with the case of passive suspension, it reveals that, the magnetorheological semi-active suspension not only improves the distribution of the track tension but also effectively reduces the chassis vibration. It provides a theoretical basis for the design and application of magnetorheological semi-active suspensions for tracked vehicles.

Semi-active Suspension Control with PSO Tuned LQR Controller Based on MR Damper

As the Linear Quadratic Regulator (LQR) approach is applied extensively in the system control of automobile suspension, the accuracy improvement of the weighting Q and R matrices is getting concern. The Particle Swarm Optimization (PSO) algorithm is being introduced to identify parameters and optimize matrix Q and R in order to fix the insufficiency of these experienced values because of the fast convergence and a more accurate solution. In this article, a quarter car model and a Bouc-Wen-based magnetorheological (MR) damper model are developed to combine the control of PSO identification and PSO-LQR controller in the semi-active suspension system. The MR damper was performed with an experimental test for running identification using experimental data as input into the Bouc-Wen model to obtain six unknown parameters, where the parameters were estimated with the PSO algorithm. Since the numerical model has been done with all parameters clear, the need for damping force from suspension is obtained by means of running the model using an input current. In the employment of PSO for damper model and vehicle control, the dual applications succeeded in verifying the feasibility of parameter identification in the MR damper and successfully tuned the LQR controller in the semi-active suspension, which decreases the vehicle body acceleration and displacement so that the improvement of ride comfort and drive stability achieved.

Optimal Control of Semi-Active Suspension for Agricultural Tractors Using Linear Quadratic Gaussian Control.

In this study, a semi-active suspension based on a hydro-pneumatic mechanism was designed to minimize the ride vibration using a suspension control algorithm. The performance of the algorithm was critical for controlling the characteristics of the target tractor. A linear-quadratic-Gaussian (LQG) optimal control algorithm was designed as a semi-active suspension control algorithm. The plant model for developing this algorithm was based on the parameters of an actual tractor. The rear suspension deflection was represented by a Kalman-filter-based state observer feedback to estimate the state variables that were difficult to measure. The designed state observer of the LQG controller was validated in terms of an accuracy index. The estimated vertical velocity and acceleration accuracies of the cabin were 83% and 79%, respectively. The performance of the designed controller was validated in terms of a performance index by comparing the performance of a tractor equipped with a rear rubber mount with that of one equipped with a semi-active suspension. The peak and root-mean-square values of the vertical acceleration of the cabin were reduced by up to 48.97% and 47.06%, respectively. This study could serve as a basis for the application of the control algorithm to systems with similar characteristics, thereby reducing system costs.

Model predictive control of a semi-active suspension with a shift delay compensation using preview road information

This paper presents a model predictive control of a semi-active suspension with a shift delay compensation using preview road information. A Model Predictive Control (MPC) methodology has been developed to optimize both ride comfort and road handling performance, where suspension states have been estimated through a model-based Kalman filter. The use of MPC in semi-active suspension control has proven to be suitable due to its ability to consider constraints when optimizing the objective function. A feasible region for the control inputs into the semi-active suspension has been determined from its mechanical limitations. However, the proposed Model Predictive Controller carries a sizeable computational load. Occurrences of “shift time delays” have been observed from the vehicle’s Electronic Control Unit processing the algorithm. To combat this, a model prediction system, in which a full-car dynamic model and road preview information are utilized to predict vehicle suspension states, has been further proposed to compensate for the shift time delay. Preview road information has been obtain through the computation of relative vehicle motion and a temporal–spatial conversion. The overall algorithm has been evaluated via computer simulation studies. Simulation results have shown that the shift compensation algorithm provides considerable improvements with regards to ride comfort. A noteworthy section of this study is the successful implementation of the proposed algorithms into an actual vehicle, where the real world performance of the proposed algorithms have been assessed. It has been shown via vehicle tests that significant improvement in ride comfort can be obtained by the proposed MPC damping control.

Vibration analysis and control of semi-active suspension system based on continuous damping control shock absorber

Vibration analysis and control of semi-active suspension system based on continuous damping control shock absorber

A novel semi-active suspension algorithm based on a high-precision frequency selector

This study proposes a novel semi-active suspension control algorithm based on a high-precision frequency selector. The algorithm focuses on the phenomenon of redundant switching in frequency domain judgment. Furthermore, the working principle of realizing high-precision selection is explained. The behavior of window sample number N is analyzed theoretically, and the gray prediction theory is used, together with a formerly sampled signal, to predict and obtain advanced output. This can compromise time delay in the control strategy and improve the accuracy of the selector. Using the combined sky-hook and acceleration-driven damper control algorithm and the MIX algorithm as the benchmark, the improved frequency selector is verified under sweep road environments. The results demonstrate that the improved algorithm significantly reduces the number of switches that occur while driving the vehicle, without deteriorating the comfort, thus improving the energy efficiency and service life of the damper.

Sliding Mode Control of Vehicle Semi-active Suspension System Based on Magnetorheological Damper

Given the fact that the passive suspension of the vehicle cannot adapt to the changing road excitation and replace conventional suspension with damping-adjustable semi-active suspension, based on the 1/4 vehicle model, sliding mode controllers are designed for two different error vectors respectively, and the simulation is carried out through Matlab/Simulink. The results show that the semi-active suspension controller can effectively improve the stability and safety of the vehicle when driving.

Takagi–Sugeno Fuzzy Model-Based Control for Semi-Active Cab Suspension Equipped with an Electromagnetic Damper and an Air Spring

Variable damping shock absorbers have received extensive attention for their efficient vibration reduction performance, and air springs have also been widely used in high-end commercial vehicles due to their nonlinear stiffness characteristics. This paper presents a novel semi-active cab suspension integrated with an air spring and a variable damping electromagnetic damper (A-EMD). The electromagnetic damper (EMD) prototype was designed, manufactured and tested. Then, due to the interference of nonlinear stiffness characteristics of the air spring with the controller in the subsequent design, the Takagi–Sugeno fuzzy method was adopted to segmentally linearize its nonlinearity, based on which an H∞ state feedback semi-active controller was designed to control the EMD to generate variable damping force. Furthermore, a Luenberger state observer was designed to provide immeasurable state parameters for the controller. Numerical simulations were carried out to validate the effectiveness of the proposed approaches, and the results show that the proposed control strategy can significantly improve the ride comfort of the A-EMD system. The vibration dose value (VDV) acceleration under the bump road and the frequency-weighted acceleration root mean square (FWA-RMS) under the random road decreased by 36.05% and 19.77%, respectively, compared with the passive suspension system.