Full-vehicle Suspension Research Articles

Fractional-Order PIλDμ Control to Enhance the Driving Smoothness of Active Vehicle Suspension in Electric Vehicles

The suspension system is a crucial part of an electric vehicle, which directly affects its handling performance, driving comfort, and driving safety. The dynamics of the 8-DoF full-vehicle suspension with seat active control are established based on rigid-body dynamics, and the time-domain stochastic excitation model of four tires is constructed by the filtered white noise method. The suspension dynamics model and road surface model are constructed on the Matlab/Simulink simulation software platform, and the simulation study of the dynamic characteristics of active suspension based on the fractional-order PIλDμ control strategy is carried out. The three performance indicators of acceleration, suspension dynamic deflection, and tire dynamic displacement are selected to construct the fitness function of the genetic algorithm, and the structural parameters of the fractional-order PIλDμ controller are optimized using the genetic algorithm. The control effect of the optimized fractional-order PIλDμ controller based on the genetic algorithm is analyzed by comparing the integer-order PID control suspension and passive suspension. The simulation results show that for optimized fractional-order PID control suspension, compared with passive suspension, the average optimization of the root mean square (RMS) of acceleration under random road conditions reaches over 25%, the average optimization of suspension dynamic deflection exceeds 30%, and the average optimization of tire dynamic displacement is 5%. However, compared to the integer-order PID control suspension, the average optimization of the root mean square (RMS) of acceleration under random road conditions decreased by 5%, the average optimization of suspension dynamic deflection increased by 3%, and the average optimization of tire dynamic displacement increased by 2%.

Event-Triggered Consensus Control of Agent-Based Full-Vehicle Suspension Systems

Event-Triggered Consensus Control of Agent-Based Full-Vehicle Suspension Systems

Event-Triggered Vibration Control for Active Full-Vehicle Suspension Systems Based on Preview Information

Event-Triggered Vibration Control for Active Full-Vehicle Suspension Systems Based on Preview Information

Advanced Vertical and Lateral Coupling Dynamics Control for a Four In-wheel Motor Drive Electric Vehicle

This paper presents an advanced vertical and lateral coupling dynamics control for stabilizing the vertical and lateral motion of a four in-wheel motor drive electric vehicle. The novelty is to investigate the possibilities of enhancing the lateral stability of electric vehicle through the correct control of their suspension system, and further improve the suspension system performances using direct yaw control (DYC) without having a contradictory effect between the vertical and lateral controllers. There are two main objectives; the first is to improve ride comfort, road holding and vehicle lateral handling performance simultaneously by using a new combined full vehicle suspension system, and the second is to strengthen electric vehicle lateral handling performance by using a sliding mode technique for controlling the direct yaw moment. For vehicle suspension system control, we are seeking to design a skyhook control to control the suspension damper and a sliding mode control to stabilize the position of the sprung masses of the in-wheel damper vibration absorber (DVA). To solve the problems caused by the chattering phenomena and ensure the exponential stability of the sprung mass, the continuous singular terminal sliding-mode controller is selected to design the sliding mode control used as a DVA controller. Simulation results show that the coordinated control between DYC and combined full vehicle suspension system under several turns' maneuvers and under random road excitations, can stabilize electric vehicle lateral motion, enhance the vehicle ride comfort, road holding, enhance the rollover resistance performance and satisfy the main suspension performances simultaneously.

A reinforcement learning backstepping‐based control design for a full vehicle active Macpherson suspension system

This paper presents a reinforcement learning backstepping-based control scheme for the design of a full vehicle active suspension system such that both the superior ride comfort and stabilization are achieved. It is well known that the traditional backstepping control scheme is suitable to solve higher order nonlinear system based on the strict-feedback form; however, the disadvantage of the procedure requires computing the derivatives of virtual control signals, which is a very complex task. Therefore, a reinforcement learning scheme using the deep deterministic policy gradient (DDPG) control strategy is developed to replace the process of finding virtual control force in backstepping method. It not only avoids the complexity of analytically calculating the derivatives of the virtual control signals, but also retains the systems robustness when there exist random disturbances from road irregularities. To verify the performance of the proposed active suspension control scheme, the random road unevenness profiles according to ISO 8608 is considered as vertical and lateral disturbance input excitation of a full-vehicle suspension system. Compared with conventional passive suspension system and backstepping control scheme, the proposed approach can be demonstrated to not only effectively improve ride comfort under random road excitation, but also improve the transient response and robustness.

New Integrated Full Vehicle Suspension System for Improvements in Vehicle Ride Comfort and Road Holding

New Integrated Full Vehicle Suspension System for Improvements in Vehicle Ride Comfort and Road Holding

Reference governed ADRC approach to manage the handling-comfort contradiction in a full-vehicle suspension

This paper aims to add to the discourse surrounding the development of a new approach to managing the trade-off between the ride-comfort and road-handling experiences induced by car suspension systems. Indeed, at present, management of the handling-comfort contradictions in such a large system using traditional algorithms requires precise modeling and large calculations, for example, model predictive control (MPC) or different models of road disturbances and a genetic representation of the solution domain, such as genetic algorithms. The proposed algorithm takes advantage of the adaptive properties of the active disturbance rejection control (ADRC) to construct a reference governor for the full-car suspension system. Resultant from the proposed algorithm, the required calculations are significantly reduced when compared to the MPC and the performance of the system is constantly monitored. The ADRC focuses on maintaining ride-comfort while the reference governor adjusts the reference signal to maintain the road-handling ability. The results demonstrate how the reference governor optimizes the input reference signals to prevent the suspension deflection from exceeding its imposed limits in instances when required to maintain the greatest degree of road-handling, while simultaneously acting neutrally when the suspension travel is far from the strokes.

Modeling and Analysis of Active Full Vehicle Suspension Model Optimized Using the Advanced Fuzzy Logic Controller

The suspension system plays a major role in automobiles to improve passenger comfort, passenger safety and road handling. It isolates the body of a vehicle from road disturbances. The full vehicle would be subjected to disturbances from all four wheels or a full suspension model of the vehicle and, thus, a full-suspension model of the vehicle should be added to the idea of an enhanced control preview. The input data for the fuzzy logic controller (FLC) is the velocity and acceleration of the front and rear wheels. Controller outputs are considered to be active forces that improve driver comfort, safety and road handling characteristics. The objective of this work is to model and analyse an active full vehicle suspension. The model is optimized using advanced FLC to improve driver comfort, safety and road handling. The mathematical model for the active full vehicle suspension model has been derived. The necessary background for the Simulink fuzzy logic and FLC has been presented. All the simulations are carried out using MATLAB/SIMULINK, a high-performance numeric computation and visualization software package. The fuzzy logic-controlled active values have been compared with ordinary passive simulated values for road profiles. The result of the simulation show that the designed advanced FLC has improved ride comfort by effectively reducing the vehicle body displacement. There is also an appreciable reduction in velocity and acceleration with no increase in suspension travel.

A Monte Carlo Parametric Sensitivity Analysis of Automobile Handling, Comfort, and Stability

This paper investigates the bandwidth sensitivity of automobile handling, comfort, and stability based on Monte Carlo sensitivity simulations. Performed bandwidth sensitivity simulations include the effects of vehicle geometry and suspension parameters on lateral acceleration, roll angle, front/rear sideslip angles, and yaw rate angle, including both time- and frequency-domain sensitivity analyses. To replicate actual automobile responses, a full-vehicle roll-oriented suspension seven-degree-of-freedom (7-DOF) model was developed and implemented considering a 2-DOF planar two-track model with a nonlinear Pacejka tire model. During the Monte Carlo simulations, 10 mm and 20 mm amplitude sine-wave excitations were used for the left and right sides, respectively, and the frequency was uniformly sampled over the range of 0–30 Hz. Simultaneously, each investigated vehicle parameter varied by ±25% relative to the reference model parameters. These simulations illustrate the sensitivity of the lateral acceleration, roll angle, yaw angle, and sideslip angles to their parameter variations. The results confirm that the road excitation frequency, tire properties, vehicle geometry, and suspension parameters significantly influence the vehicular lateral and roll stabilities when considering the lower and higher peaks and the frequency bandwidths of the lateral and roll stabilities. Interestingly, the longitudinal location of the center of gravity and the tire properties can achieve more significant peak lateral stability responses, as represented by the front and rear sideslip angles and the frequency bandwidth, compared to the other vehicle parameters at high frequencies. Choosing the correct tire properties and vehicle geometry, as well as suspension characteristics, plays an essential role in increasing the vehicular lateral stability and the rollover threshold. Variations in the studied parameters allow for higher vehicular stability when a vehicle is driven on random road surfaces.

Active and Passive Suspension System Performance under Random Road Profile Excitations

Passive suspensions are designed to satisfy the conflicting criteria of riding comfort and vehicle handling. An active suspension system attempts to overcome these compromises to provide the best performance for vehicle control. Different types of mathematical models have been used to study the suspension system of a vehicle. The quarter vehicle model is used for initial investigation. Later, the half vehicle and full vehicle models are used for the study, which is closer to the actual model of a vehicle suspension. In this paper, the behavior of a suspension system is analyzed using the full vehicle model. In the current work, the dynamic equation and their state-space formulation are presented for the full vehicle model to understand the system prior to the controller design. The open-loop response of the full vehicle suspension system, when subjected to various road excitations, is also studied. The procedure of modeling a SIMULINK model for passive suspensions system is discussed in detail. Design of the simple Proportional Integral Derivative (PID) feedback and feed-forward controller is presented for the active suspension system using transfer functions. Closed-loop transfer functions are also derived and their responses are plotted. To analyze the rollover behavior simulation for cornering is also performed in the current study.

A comprehensive comparison of the vehicle vibration energy harvesting abilities of the regenerative shock absorbers predicted by the quarter, half and full vehicle suspension system models

Regenerative shock absorber has been studied intensively for generating electricity from motion energy that would have been otherwise dissipated and wasted in the form of heat. Integration of the regenerative shock absorber with the vehicle suspension system can incorporate the interaction between the wheels and vehicle body, resulting in more accurate power output results. This paper presents the modellings of quarter, half and full vehicle suspension system models integrated with regenerative shock absorbers based on the same baseline vehicle. The time domain and frequency domain analyses enable a comprehensive comparison of all three suspension system models to be conducted in terms of the effects of vehicle speeds, position of vehicle center of gravity, road classifications (road class A, C and E) and driving speed cycles. The results suggest that the shift of vehicle center of gravity position does not affect the results of any suspension system models. All three suspension system models can respond well to road classification change and rougher road can yield higher power output. The quarter vehicle suspension system model does not present accurate power output results in the low frequency range. Moreover, it also behaves poorly with the vehicle speed variation, which limits its use to Highway Fuel Economy Test Driving Cycle. The half vehicle suspension system model resembles full vehicle suspension system model really well regardless of frequency range, vehicle speed variations and road classifications, when the transverse road profile is neglected.

Novel Method of Forecasting Performance of Full Vehicle Suspension by Decoupling Analysis and Vibration Sensing Experiments

Novel Method of Forecasting Performance of Full Vehicle Suspension by Decoupling Analysis and Vibration Sensing Experiments

Implementation of an Electromagnetic Regenerative Tuned Mass Damper in a Vehicle Suspension System

High cost and significant power absorption do not allow exploiting modern active control strategies for improving vehicle suspension performance. Meanwhile, the semi-active control policies are not able to overcome a weighted unsprung adverse effect, which represents a cornerstone of the implementation in-wheel motors for a new type of electric vehicle. This paper discusses and analyses the implementation of a proposed energy-harvesting based tuned mass damper (TMD) to be implemented in electric vehicles. In this manner, a full vehicle suspension model embedded with four TMDs was created to simultaneously enhance the car comfort and road-holding responses with a corresponding large-scale energy harvesting. In the proposed 11-DOFs (degrees-of-freedom) vehicle model, the full-vehicle body was suspended using suspension systems, including the compacted back-iron based design of an electromagnetic TMD. The performed simulations indicated the considerable advantage and potentialities of using the TMDs based suspension. In terms of the RMS (root-mean-square), the car body acceleration was reduced by 21.7%, while the road-holding was enhanced by 5.7%. Moreover, the proposed regenerative electromagnetic tuned mass damper (ETMD) allows for harvesting vibration energy up to 58 W for a vehicle driven on a road class D and a speed of 30 m/s.

Effect of magnetorheological damper parameters on dynamic responses of a full-vehicle suspension system

This paper investigates how magnetorheological (MR) damper parameters affect the dynamic response of a full-vehicle suspension system in much detail. The constitutive mechanical model and characteristics of MR damper are firstly obtained and analyzed

Active Suspension System Control With Decentralized Event-Triggered Scheme

This article concerns the problem of improving ride comfort of a full-vehicle active suspension system through an observer-based decentralized event-triggered H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller. The observer-based controller is adopted to cope with the situation that states information of vehicles are not available. To reduce the observer-based controller computing frequency, a decentralized event-triggered data transmission scheme is provided, and lower bounds on the minimum interevent time are guaranteed. Based on the proposed controller, the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance of an active full-vehicle suspension system can be obtained. Finally, simulations in the bump and random road conditions are shown to demonstrate the effectiveness of the derived algorithm.

Modelling and ride analysis of a hydraulic interconnected suspension based on the hydraulic energy regenerative shock absorbers

Abstract The suspension system is an important part which can mitigate the influences of vibration caused by road roughness where these vibrations are traditionally dissipated by shock absorbers. From the view of energy recovery, a hydraulic interconnected suspension based on the energy regenerative shock absorbers (HIS-HESA) is proposed to improve ride comfort, road holding ability and energy recovery ability simultaneously. This paper mainly focuses on the modelling and ride analysis of a 7-DOF full vehicle suspension model integrated with the HIS-HESA. The mathematical model of the HIS-HESA is described based on the relationship between the pressure drop and the flow rate of every hydraulic element. The characterization of the HIS-HESA is given based on a parametrical analysis under a sinusoidal excitation. Further, the traditional shock absorber and the single HESA have been compared terms of suspension dynamics and energy recovery. Thereafter, the simulation is implemented to compare the vehicle dynamics (body acceleration, tire dynamic load and power regenerated) using HIS-HESA with that of the traditional suspension. The simulation results suggest that the HIS-HESA can attenuate the vibrations to maintain a good ride comfort besides it can also regenerate energy to power electrical equipment on the vehicle. The analysis also indicates that the influence of external resistance within HIS-HESA provides the possibility regarding the semi-active control of the HIS-HESA which will be the research focus in future development.

Active Full-Vehicle Suspension Control via Cloud-Aided Adaptive Backstepping Approach.

This paper is concerned with the adaptive backstepping control problem for a cloud-aided nonlinear active full-vehicle suspension system. A novel model for a nonlinear active suspension system is established, in which uncertain parameters, unknown friction forces, nonlinear springs and dampers, and performance requirements are considered simultaneously. In order to deal with the nonlinear characteristics, a backstepping control strategy is developed. Meanwhile, an adaptive control strategy is proposed to handle the uncertain parameters and unknown friction forces. In the cloud-aided vehicle suspension system framework, the adaptive backstepping controller is updated in a remote cloud based on the cloud storing information, such as road information, vehicle suspension information, and reference trajectories. Finally, simulation results for a full vehicle with 7-degree of freedom model are provided to demonstrate the effectiveness of the proposed control scheme, and it is shown that the addressed controller can improve the performances more than 80% compared with passive vehicle suspension systems.

Electrohydraulic Active Suspension Fuzzy-Neural Based Control System

A design of a new controller via a combination of fuzzy controller and artificial neural network (ANN) force tracking solution for a full vehicle suspension system with nonlinear electrohydraulic actuator dynamics is proposed. The comparison between the new Fuzzy-ANN force tracking controller designed with passive suspension system and PID-ANN controller previously developed is presented. Simulations and results obtained show that the Fuzzy-ANN combined controller can improve the stability problems caused by disturbances and road conditions, providing a superior passenger comfort.

Modelling and Simulation of Full Vehicle Model with Variable Damper Controlled Semi-Active Suspension System

The main objective of the variable damper controlled vehicle suspension system is to reduce the discomfort identified by passengers which arises from road roughness and to increase the ride handling related with the rolling, pitching and heave movements. This imposes a very fast and accurate variable damper to meet as much control objectives, as possible. The method of the proposed damper is to reduce the vibrations on each corner of vehicle by providing control forces to suspension system while travelling on uneven road. Numerical simulations on a full vehicle suspension model are performed in the Matlab Simulink toolboxes to evaluate the effectiveness of the proposed approach. The obtained results show that the proposed system provides better results than the conventional suspension system.

Energy harvesting sensitivity analysis and assessment of the potential power and full car dynamics for different road modes

Abstract Automobiles are dissipating a considerable amount of vibration energy that is worth of being harvested where it can be exploited in different applications. For a full vehicle suspension assembly, the conflict between the potentially harvested energy and vehicle dynamics represented by ride quality and road safety and handling was comprehensively illustrated for different input modes. The discrepancy between the bounce input mode and the roll input mode was also sufficiently clarified based on an extensive parametric analysis covering the design parameters and the operational parameters as well. Comprehensive simulations were then conducted to estimate the amount of wasted energy in vehicle suspension system for different types of cars (passenger, bus, truck, and off-road vehicle), besides the potential harvested power was quantified for different standard driving cycles (NEDC, WLTP, HWFET, and FTP). Based on that, a 7-DOF full car suspension model was implemented in Matlab/Simulink environment and induced by different levels of road irregularities. The findings of this paper showed that the vibration intensity levels changed clearly in the complex input mode that reflects a realistic view of the real vehicle dynamics on the roads compared to the ideal results from the bounce input mode. Our results also indicate that a potential power up to 420 W can be collected considering standard driving patterns and roll mode input. The analysis indicates that the overloaded vehicles are suitable for the energy harvesting system based on the harvestable energy per unit cost.