Vehicle Semi-active Suspension Research Articles

Augmented Kalman Estimator and Equivalent Replacement Based Taylor Series-LQG Control for a Magnetorheological Semi-Active Suspension

This research presents an augmented Kalman estimator and an equivalent replacement-based Taylor series (ERBTS)-linear quadratic Gaussian (LQG) control strategy to cope with the control accuracy and response delay of magnetorheological (MR) dampers for vehicle semi-active suspensions. The parameters in the MR model are identified from experimental measurements. Then, two main sources of control error, namely, modelling error and real-time variety of the MR damper output force, are defined as an integrated compound real-time variety. Subsequently, they are written into a differential equation with characteristics of the minimum system to augment the state equation of the semi-active suspension system. The augmented Kalman estimator is constructed to estimate the abovementioned compound real-time variety. To calculate an acceptable time-delay compensation predictive control force, an equivalent operation is implemented beforehand in the suspension comprehensive performance index by replacing a part of the squared time-delay control force with the corresponding predictive control force. Simulation results verify the effectiveness of the proposed augmented Kalman estimator, and the newly developed ERBTS-LQG controller almost achieves control effectiveness of the ideal time delay free semi-active suspension.

Design and performance evaluation of a novel fractional order PID control strategy for vehicle semi-active suspension

Design and performance evaluation of a novel fractional order PID control strategy for vehicle semi-active suspension

Design and verification of low-friction and high-performance monotube magnetorheological damper

The frictional force of the suspension damper is an essential factor affecting vehicle ride comfort. As an important basic component of intelligent suspension, magnetorheological (MR) damper has the advantages of simple structure and adjustable damping performance. However, the frictional force of the MR damper is excessively high, due to the high-pressure gas to avoid the cavitation effect. If the frictional force of MR damper can be reduced, the vibration isolation performance of the intelligent suspension based on the MR damper will be further improved. In this study, a monotube MR damper with low friction and high performance is proposed and investigated. Firstly, the structural design of the low-friction MR damper is carried out, and the mathematical model of its controllable damping force and uncontrollable damping force is established. Secondly, the key structural parameters of the MR piston are optimized, and the valve system is matched based on the optimized mechanical characteristics of the piston to avoid the cavitation effect. Thirdly, bench tests are carried out on the developed low-friction MR damper. The experimental results show that the frictional force of the MR damper is very low, and no cavitation effect occurs. Finally, the system performance simulation analysis is carried out on the 1/4 vehicle semi-active suspension using the MR damper, and the influence of frictional force on the performance evaluation indexes of passive and semi-active suspensions is investigated. The simulation results indicate that the influence of frictional force on semi-active suspension is higher than that of passive suspension, and reducing the frictional force of the MR damper is of great significance to improve the performance of the semi-active suspension.

Tracking Active Control Forces by Using a Semi-Active Vehicle Suspension Integrated with Negative Stiffness

Active suspension technique normally provides the best vibration mitigation performance at the cost of high-energy consumption. In contrast, the energy consumption of a semi-active suspension is normally much smaller than that of an active suspension, whereas the control performance is compromised as well. Observing the core issue that caused such a phenomenon is that the existing semi-active control force, unlike the active control force, shall always oppose to the relative motion of the actuator (i.e. clipping phenomenon). This paper subsequently proposes a novel semi-active vehicle suspension system that incorporates a passive negative stiffness (NS) spring and a semi-active damper (SD) to realize uncompromised active control force while consuming energy of a typical semi-active suspension system. In specific, the proposed system allows for decomposition of the target active control force and tracked via the collaboration of the NS and SD components. Herein, the NS element is capable of releasing the store potential energy that subsequently eases the aforementioned clipping phenomenon of a traditional semi-active suspension. In this paper, besides the relevant clarifications on the system topology and working mechanism, its feasibility and performance enhancement are also validated via systematic numerical simulations of a vehicle suspension; and the results indicate, for the first time, that the proposed semi-active suspension can fully track the active control force and subsequently achieve unprecedented control performance comparable to an active controller.

Multiobjective optimization for semi-active electromagnetic vehicle suspensions

Multiobjective optimization for semi-active electromagnetic vehicle suspensions

Identification of Control-Related Signal Path for Semi-Active Vehicle Suspension with Magnetorheological Dampers

This paper presents a method for the identification of control-related signal paths dedicated to a semi-active suspension with MR (magnetorheological) dampers, which are installed in place of standard shock absorbers. The main challenge comes from the fact that the semi-active suspension needs to be simultaneously subjected to road-induced excitation and electric currents supplied to the suspension MR dampers, while a response signal needs to be decomposed into road-related and control-related components. During experiments, the front wheels of an all-terrain vehicle were subjected to sinusoidal vibration excitation at a frequency equal to 12 Hz using a dedicated diagnostic station and specialised mechanical exciters. The harmonic type of road-related excitation allowed for its straightforward filtering from identification signals. Additionally, front suspension MR dampers were controlled using a wideband random signal with a 25 Hz bandwidth, different realisations, and several configurations, which differed in the average values and deviations of control currents. The simultaneous control of the right and left suspension MR dampers made it necessary to decompose the vehicle vibration response, i.e., the front vehicle body acceleration signal, into components related to the forces generated by different MR dampers. Measurement signals used for identification were taken from numerous sensors available in the vehicle, e.g., accelerometers, suspension force and deflection sensors, and sensors of electric currents, which control the instantaneous damping parameters of MR dampers. The final identification was carried out for control-related models evaluated in the frequency domain and revealed several resonances of the vehicle response and their dependence on the configurations of control currents. In addition, the parameters of the vehicle model with MR dampers and the diagnostic station were estimated based on the identification results. The analysis of the simulation results of the implemented vehicle model carried out in the frequency domain showed the influence of the vehicle load on the absolute values and phase shifts of control-related signal paths. The potential future application of the identified models lies in the synthesis and implementation of adaptive suspension control algorithms such as FxLMS (filtered-x least mean square). Adaptive vehicle suspensions are especially preferred for their ability to quickly adapt to varying road conditions and vehicle parameters.

GA-LQR for vehicle semi-active suspension with BiLSTM inverse model of magnetic rheological damper

This paper proposes a magnetic rheological (MR) semi-active control method based on bidirectional long short-term memory (BiLSTM) neural network, linear quadratic regulator (LQR) control algorithm, and genetic algorithm (GA). The LQR algorithm with GA optimizing the weight coefficients generates the expected damping force. Due to the nonlinear hysteresis characteristics of the magnetic rheological damper (MRD) and the fact that its input and output have certain time dependence, an inverse model of MRD is established by BiLSTM. The control current is predicted by BiLSTM and then the current is input to the MRD to obtain the damping force that is infinitely close to the expected damping force. The damping force is then applied to the suspension system to form a complete closed-loop feedback control, which realizes the damping effect and generates a real-time control. The simulation results show that the MRD inverse model can accurately predict the required control current, and the GA-optimized LQR control algorithm has a good suppression effect on the vertical vehicle acceleration, dynamic tire load, and suspension dynamic stroke.

Discrete-time multi-model preview control: Application to a real semi-active automotive suspension system

Road roughness is one of reasons of vehicle vibration. Passengers feel uncomfortable or goods are damaged with the serious vibration caused by the irregular road surface. This paper focus on the road adaptation for vehicle semi-active suspension system using preview robust control approach. This approach aims to improve the performance of control systems by using future measurements or predictions of road disturbances. The objectives are to minimize a quadratic criterion on the system output and at the same time to achieve a good magnitude of the control signal. The proposed solution combines a robust feedback controller together with a preview feedforward filter. This new method is developed to synthesize the preview feedforward filter in order to limit the control force demand of an electro-rheological (ER) damper in an automotive suspension system, and is implemented on the INOVE testbench from GIPSA-lab (1/5-scaled real vehicle) for real-time performance assessment. Both simulation and experimental results demonstrate the effectiveness of the proposed controller to determinate the damper force in real-time face to measurement noises and road disturbances.

Semi-active fuzzy cooperative control of vehicle suspension with a magnetorheological damper

This study attempts to improve the vibration isolation performance of a vehicle suspension system with a magnetorheological damper (MRD) under complex driving conditions. Structure parameter uncertainty, disturbance of the driving process, and response time delay of MRD are all addressed. Firstly, experiments of MRD were carried out in a damping force testing machine to identify the parameters of the MRD adjustable Sigmoid model by the Levenberg-Marquardt optimization algorithm. Then, the parameter identification is verified by comparing experimental and simulation data. Secondly, the state space equations of the suspension system are derived by Newton’s second law. The transfer function from the bounded disturbance input to the control output is obtained based on H∞ control theory. To make the Infinite norm of the system transfer function less than a certain value, three control strategies are proposed: variable structure control (VSC), disturbance rejection control (DRC), and delay tolerance control (DTC). Thirdly, considering these issues together to weaken the effect of disturbances on vehicle driving conditions, a fuzzy cooperative control (FCC) strategy is proposed based on the linear matrix inequality (LMI) theory. Simulation results demonstrate that FCC semi-active vehicle suspension systems conduct effective vibration isolation performance while responding to multiple external disturbances.

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.

Parametric Study of Rider’s Comfort in a Vehicle with Semi-Active Suspension System Under Steady State Conditions

Due to the influence of road roughness on all quantities representing dynamic response of vehicles such as vehicle ride comfort, tire dynamic force, dampers and spring forces, etc., the interaction between a vehicle and road profiles in relation to the comfort and health of passengers has become significant as road roughness causes a spectrum of oscillations for a moving vehicle. Thus, this study investigates the dynamic response of semi-active vehicle suspension system under the influence of steady state road conditions such as smooth, gravel and suburban roads to obtain mathematical equations based on the pitch and heave motions of the vehicle. Power spectral density, PSD, was used to characterize the road input spectrum on the basis of the road roughness parameters which correlate with International Roughness Index, (IRI). Vehicle suspension system responses to the different road inputs were obtained by simulation based on the mathematical model developed using Matlab/Simulink software. The root-mean-square acceleration was used as objective metric to estimate the passenger’s discomfort, dynamic tire force and suspension travel at a constant vehicle speed of 20 km/h while the ISO 2631 was applied to predict the discomfort experienced by the riders under different steady state road irregularities. The discomfort experienced by the riders on the gravel road and suburban road increased when the vehicle parameters were increased and also when the speed of the vehicle was increased. For smooth road, the riders experienced comfort according to ISO 2631, although the discomfort threshold increased with increase in speed of the vehicle but still within the threshold of human comfort zone. It can be concluded that for a vehicle ride within the human comfort zone on gravel and suburban roads, the speed of the vehicle should be brought down considerable below 20 km/h and the suspension systems should also be improved upon.

Parametric study of rider’s comfort in a vehicle with semi-active suspension system under transient road conditions

Considering that many Nigerian roads are untarred, the effect of frequent plying of these untarred roads on passengers and the expected performance of suspension system of vehicles are important for health and safety reasons. This is significant because the transmission of vibration associated with suspension systems are dependent on the frequency spectrum of the road input, and the nature of the suspension system and the vehicle seating arrangement that is producing the vibration. Thus, this study focuses on the discomfort experienced by passengers based on parametric study of vehicle with semi-active suspension system under transient road conditions. The modeling of the of semi-active vehicle suspension system properties are contrived on the mass- spring damper system for 4 degree-of–freedom half- car model integrated with 3 degrees of freedom human-seat arrangement. Using vehicle parameters, the severity of ride discomfort experienced by the passenger as the vehicle traversed transient road conditions (i.e., traversing obstruction) was evaluated in terms of the vibration dose value (VDV). Results of simulation based on the parametric studies are presented and the vibration dose values evaluated to show the dependence of vehicle ride comfort on the characteristics of the various elements of the vehicle suspension such as stiffness and damping characteristics. The result showed that the variation of sprung mass and suspension stiffness of the vehicle had more significant effects on passenger discomfort than the variation of the unsprung mass. The parametric study also revealed that suspension stiffness affects the suspension working space as the vehicle traversed transient road condition.

A New Integrated Skyhook-Linear Quadratic Regulator Coordinated Control Approach for Semi-Active Vehicle Suspension Systems

Abstract Vehicle semi-active suspension systems can provide a satisfactory compromise of ride comfort and handling stability. With the rapid developments of damping control methodologies, ride comfort is expected to be improved in all three directions, i.e., vertical, roll, and pitch. Considering this kind of multi-objective coordinated control problem, Model Predictive Control (MPC) gains lots of attention in the recent decade. However, the MPC algorithm is expensive for real-time implementations due to its computational complexity. This paper introduces an integrated Skyhook and linear quadratic regulator (LQR) control approach, which can be easily processed on an automotive-grade microcontroller because of its concise algorithm. Meanwhile, it has great potential in attenuating vehicle body vibrations in vertical and rotational directions at the same time. Its control performances are evaluated through the co-simulation between carsim and matlab/simulink based on three different road conditions. The Buick Enclave, which is a full-size sport utility vehicle (SUV), is modeled in carsim for evaluating the control performance. The results demonstrated the control efficiency of the integrated Skyhook-LQR approach, which is even better than MPC, especially in vertical and pitch directions.

Performance Evaluation of Semi-Active Suspension for Passenger Vehicle through Skyhook, Groundhook and Hybrid Control Strategies

This paper presents a semi-active vehicle suspension model with four degrees of freedom. The main aim is to investigate the response of the vertical vibration of the random excitation from the road. A passive suspension system and a semi-active suspension system using three different controllers such as skyhook, groundhook and hybrid control are used to assess the suspension performance. The suspension performance parameters are the vertical acceleration, the pitch acceleration, the suspension deflection and the dynamic load of the tire. The acceleration is a measure of ride comfort while the suspension deflection and tyre load are the measures of stability. The model is simulated in MATLAB Simulink and the results for the semi-active and the passive suspensions in frequency and time responses are obtained. It is concluded that the hybrid controlled semi-active vehicle suspension system is provided improvements in the suspension performance parameters compared with skyhook and groundhook. In addition to that the hybrid, skyhook, and groundhook caused better suspension performance compared to passive suspension.

On an enhanced back propagation neural network control of vehicle semi-active suspension with a magnetorheological damper

To improve the ride quality of a vehicle, an enhanced vibration control method is presented for semi-active suspension (SAS) with magnetorheological (MR) damper by combining back propagation neural network (BPNN) and particle swarm optimization (PSO). Based on the test data of MR damper, a non-parametric model of MR damper using adaptive neuro-fuzzy inference system (ANFIS) is first established, and based on that, a dynamics model of the SAS system is derived. Next, a BPNN controller is designed to fulfill the effective control of the current in MR damper. Meanwhile, the improved PSO with adaptive weight and dynamic acceleration constant is introduced to optimize the weights and thresholds of the BPNN controller, which can avoid the designed BPNN falling into the local optimum and then improve the convergence rate of the designed controller. Besides, the stability of the developed controller is analyzed via Lyapunov stability theory. Different from the existing models and methods, the established model can well describe the dynamics behaviors of the actual MR damper, and the proposed control method has better adaptability, convergence speed and precision. Finally, a simulative investigation is performed to validate the effectiveness and feasibility of the proposed controller, compared to existing BP-PID control and the passive suspension, the vehicle acceleration of SAS with this proposed controller is respectively improved by 10% and 30%.

A study on a vehicle semi-active suspension control system based on road elevation identification.

A semi-active suspension system can effectively improve vehicle ride comfort and handling stability, and the active detection of road information is key to achieving semi-active suspension. To improve the road elevation perception ability of vehicles, this study proposes a continuous multiple scanning recursive matching algorithm based on a single-line LIDAR sensor. Radar recursive scanning is used to obtain the multiple superposition data of echo signals, and coordinate matching is realized between historical scanning data and current scanning data. Simultaneously, the sensor height deviation and pitch angle deviation of the sensors are regressed to obtain an accurate pavement elevation. Considering the control effect of the active vehicle suspension, a vehicle suspension model with seven degrees of freedom is established. The semi-active suspension controller is constructed using a diagonal recursive neural network algorithm, and the neural network weight is trained using a genetic algorithm. In addition, a preview diagonal recursive neural network control strategy for semi-active suspension, based on the combination of road elevation information, is proposed. The results of a hardware-in-the-loop co-simulation, which was conducted based on the Simulink control model and dSPACE real-time simulation, revealed that the ride comfort and stability of the vehicle were improved owing to a preview of the elevation information of the road ahead and the active adjustment of the shock absorber of the suspension system.

An Optimization Algorithm of Time-Delayed Feedback Control Parameters for Quarter Vehicle Semiactive Suspension System

Time-delayed feedback control is commonly used on the vehicle semiactive suspension system to improve ride comfort and safety. However, its performance on the suppression of road random excitation is less significant than that on the suppression of simple harmonic excitation. Therefore, this paper proposes a strategy of time-delayed feedback control with the vertical displacement of wheel and the method of optimizing its parameters based on equivalent harmonic excitation. The optimal parameters of the time-delayed feedback control are obtained in this way for the vehicle semiactive suspension system in its effective frequency band. The results of numerical simulation verify that the time-delayed feedback control with vertical wheel displacement and its parameter optimization based on equivalent harmonic excitation can significantly improve the ride comfort and stability. Its performance is much better than that of the passive suspension system.

Reinforcement-Learning-Based Vibration Control for a Vehicle Semi-Active Suspension System via the PPO Approach

The vehicle semi-active suspension system plays an important role in improving the driving safety and ride comfort by adjusting the coefficients of the damping and spring. The main contribution of this paper is the proposal of a PPO-based vibration control strategy for a vehicle semi-active suspension system, in which the designed reward function realizes the dynamic adjustment according to the road condition changes. More specifically, for the different suspension performances caused by different road conditions, the three performances of the suspension system, body acceleration, suspension deflection, and dynamic tire load, were taken as the state space of the PPO algorithm, and the reward value was set according to the numerical results of the passive suspension, so that the corresponding damping force was selected as the action space, and the weight matrix of the reward function was dynamically adjusted according to different road conditions, so that the agent could have a better improvement effect at different speeds and road conditions. In this paper, a quarter–car semi-active suspension model was analyzed and simulated, and numerical simulations were performed using stochastic road excitation for different classes of roads, vehicle models, and continuously changing road conditions. The simulation results showed that the body acceleration was reduced by 46.93% under the continuously changing road, which proved that the control strategy could effectively improve the performance of semi-active suspension by combining the dynamic changes of the road with the reward function.

Research on Vibration Reduction of Half-Vehicle Active Suspension Sys-tem Based on Time-delayed Feedback Control with Wheel Displacement

This paper proposes parameter controlling optimization of the time-delay feedback that is based on "equivalent harmonic excitation" in effective frequency band towards optimization of delay feedback control parameters for vehicle semi active suspension system. In this way, the optimal values of delay feedback control parameters based on different types of delay feedback control (displacement, velocity and acceleration) of wheels in the effective frequency band are obtained. Finally, through the stability analysis of vehicle semi-active suspension system based on different types of wheel delay feedback control and the numerical simulation analysis of time-domain response of suspension system performance evaluation index, the superiority of the time-delay feedback control strategy based on wheel displacement and the effectiveness and feasibility of the equivalent harmonic excitation optimization strategy are verified. Therefore, it provides a theoretical reference for the selection of time-delay feedback control strategy and the optimal design of time-delay feedback control parameters of vehicle active and semi-active suspension system.

Characterization and quarter car analysis with magnetorheological fluid damper using modified algebraic model (mAlg)

Magnetorheological (MR) dampers have received the ever-increasing attention of many researchers considering their wide range of applications ranging from large seismic control of structures to prosthetics in the medical field. One such application is in semi-active vehicle suspension with MR damper. Modeling the dynamic behavior of MR damper is an intriguing challenge and many mathematical models are put forth to address this task. In this work, the MR damper is initially developed and characterized using in-house prepared MR fluid. This study aims at using a modified algebraic model (mAlg) for modeling the hysteretic behavior of the MR damper using experimental force data. Also, the study uses a Genetic algorithm toolbox to find optimal parameters for the mAlg model, and the accuracy of mAlg is visualized with various plots. The work also aims at analyzing the response of the quarter car model with MR damper to three kinds of road excitations using Simulink.