Vehicle Suspension Control Research Articles

A comprehensive development methodology for testing and evaluating algorithms for a vehicle suspension control system

Introduction. Full-scale tests remain the most important quality indicator of the developed design solutions. At the same time, high-performance simulation computational systems are becoming more and more relevant, which can significantly reduce field tests of newly developed prototypes of vehicles. The task of building a transparent connection between full-scale and virtual tests is always relevant for a high-quality and effective study of the tested object behavior. This article touches on topical engineering issues in the development of complex assessment techniques for controlled vehicle systems. The purpose of the study was to solve the problem of the cumulative assessment of various control algorithms for the suspension system for solving the integration problem of comparing control algorithms, regardless of their implementation. The results of solving this problem are recommendations for improving the vehicle movement algorithms in various conditions and modes. Methodology and research methods . The article provides a rationale and general description of a comprehensive methodology for a controlled suspension system for a vehicle chassis, a sequence of planning experiments and the analysis of the results achieved. The sequence of construction of the estimated “conflict diagram” (Carpet plot) from the test data is given. The analysis of the results is presented and considered in the diagram as an example. Scientific novelty and results . The approaches outlined in the article were used by the authors at the initial stages of the controlled chassis suspension system development, which made it possible to improve the quality and efficiency of the achieved result in the shortest possible time. The developed and approved comprehensive test method and methods for assessing the controlled chassis suspension system is a scientific novelty, since such methods and approaches have not been used before. Practical signifi cance . The developed complex test methodology and assessment methods are used at FSUE “NAMI” at the initial stages of designing controlled chassis suspension systems.

Research on Fuzzy Logic Algorithm and Analogue Experiment on Active Suspension Control of Vehicle

A seven-degree of freedom whole body model with an active suspension system is described in the paper. First, construction of fuzzy control system is obtained. One fuzzy control discipline is designed. The fuzzy controller for vertical motion, fuzzy controller for pitch motion and roll motion is established. Second, controller for logical operation is designed, and the sketch of the composed fuzzy control system is presented. In addition, simulation analysis is obtained. The simulation results indicate that the ride comfort and the control stability is ameliorated by the proposed controller. Finally, simulation analogue of experiment is gained and the simulation environment of electronically controlled air suspension is constructed.

Simultaneous estimation of state and unknown road roughness input for vehicle suspension control system based on discrete Kalman filter

This study presents an improved discrete Kalman filter for simultaneously estimating both all state variables and the unknown road roughness input for a vehicle suspension control system that plays a key role in the ride quality and handling performance while driving the vehicle. The suspension system is influenced by the road roughness input, which causes undesirable vibrations associated with vehicle instability. It is therefore important to estimate the road roughness and state variables information when designing the model-based controller for the vehicle suspension control system associated with the vehicle’s vertical dynamics. However, the implementation of conventional estimation theories for the suspension control system is challenging because the road roughness acts as an unknown input and is difficult to be measured or estimated while driving. This study presents an improved Kalman filter with unknown input, which can simultaneously estimate the state variables and road roughness without any prior information about the vehicle suspension control system. The proposed road roughness input estimator is evaluated by using an in-vehicle test bed with a laser-type profilometer. Finally, the state estimation performance of the proposed estimator for a vehicle suspension control system is validated by using CarSim software.

Learning-based vehicle suspension controller design: A review of the state-of-the-art and future research potentials

Abstract In this paper, a review of the literature on vehicle suspension control with an emphasis on learning based algorithms is presented. An elaborated discussion on the potentials of learning based controllers is also given. Some of the most well-known active and semi-active suspension controllers are elicited from the literature, and their pros and cons are reported. By categorizing the existing suspension control techniques and considering their functionalities, it is tried to make a ground for indicating the high potential of learning strategies for this task. In this context, several advantageous features of statistical learning and computational intelligence methods are enumerated, which can play a key role in the future of vehicle suspension control. In the authors’ view, the necessity of considering learning strategies for suspension control lies in the fact that, over the past two decades, tremendous effort has been exerted on developing smart and autonomous vehicles to reduce the need for human-machine interaction. Given the fact that the final goal of automotive industrialists is to design efficient and safe autonomous vehicles, it is impossible to neglect the pivotal role of probabilistic artificial intelligence and statistical learning algorithms. In short, by reading this review paper, one can find out (1) the state-of-the-art of the conducted researches on suspension controllers, (2) the potential of learning strategies and their applicability to vehicle suspension control, and (3) the important open questions which deserve further investigation to come up with robust, stable and accurate learnable controllers. The outcome of this paper can be of use for practitioners working on designing smart and autonomous vehicles.

Multi-Criteria Synthesis of Frequency-Modulated Discrete Control of Semi-Active Vehicle Suspension - Part 2 Multi-Objective Synthesis

The paper discusses obtaining of a control law of semi-active vehicle suspension realizing compromise between requirements for ride comfort and vehicle stability on road pavement. The problem is solved as multi-objective synthesis based on a selection from the Pareto set of the optimal compromise solution by using the Game theory’s strategy.

Multi-Criteria Synthesis of Frequency-Modulated Discrete Control of Semi-Active Vehicle Suspension - Part 1 Analysis and Control Strategies

The paper discusses the contradiction influence of system damping coefficient in the different excitation’s frequency diapasons on the raid comfort and the vehicles stability on road. It is analyzing the discrete “on-off” control laws for the semi-active suspension included in a model reduced to the vehicle wheel and accounting the vertical dynamics of the vehicle so-called “Quarter car model”. Based on analysis of the frequency characteristics it is propose a frequency modulation of the control realized by a signals filtration.

Physical Parametric Model of an Automotive Electrohydraulic Semiactive Damper

A full mathematical model is developed to formulate the nonlinear characteristics of an automotive electrohydraulic semiactive damper. This multidisciplinary physical parametric model considers the force equilibrium, flow continuity with flow losses due to the volumetric change and pressure difference, total flow through the valve system under different control modes, and dynamics of the floating piston which are balanced by the pressures of the fluid and gas. Both computer simulation and bench testing of the damper demonstrate that the damper has four levels of damping characteristics: “hard mode”, “hard rebound and medium-soft compression mode”, “medium-hard rebound and soft compression mode” and “soft mode”. The considerable consistency between the simulation and experimental results verifies that the mathematical model accurately captures the physical damping characteristics of the damper. Thus, the developed physical damper model is experimentally validated. The obtained full parametric damper model with mode controls is valuable for accurate and reliable damper development and crucial for the next step in vehicle system dynamics simulation and suspension control system synthesis.

Stochastic sliding mode control of active vehicle suspension with mismatched uncertainty and multiplicative perturbations

AbstractThe purpose of this paper is to investigate the stochastic sliding mode controller design for uncertain model of vehicle suspension. The Itô stochastic model of quarter‐car is considered applying both parametric stochastic perturbations and mismatched uncertainty of road disturbance. To tackle with uncertainties of model a non‐semi‐martingale stochastic sliding dynamic is obtained employing a proportional‐integral switching surface. By means of linear matrix inequalities (LMIs) and stochastic extension of Lyapunov method, a sufficient condition is derived to guarantee the mean‐square stability of the stochastic dynamics in the specified switching surface for all admissible mismatched uncertainties. Furthermore, the synthesized sliding mode controller guarantees the reachability of the determined sliding surface. A simulation study is performed to evaluate the effectiveness of stochastic sliding mode control approach.

Basic principles of vehicle suspension control

The paper is devoted to the description of the basic operation principles of control systems over suspension (cushioning) system elements of a vehicle. The basic operation algorithms, as well as the basic principles of change of properties of suspension or cushioning components under different vehicle driving conditions, are presented. The list of sensors and signals, which shall be present in the system to ensure its effective operation, is proposed. The results of experimental analysis of the pneumatic elastic element (air bellows) stiffness and the results of computer simulation of the vehicle behavior when turning are additionally presented.

An Active Vehicle Suspension Control Approach with Electromagnetic and Hydraulic Actuators

An active vibration control approach from an online estimation perspective of unavailable feedback signals for a quarter-vehicle suspension system is introduced. The application of a new signal differentiation technique for the online estimation of disturbance trajectories due to irregular road surfaces and velocity state variables is described. It is assumed that position measurements are only available for active disturbance suppression control implementation. Real-time signal differentiation is independent of detailed mathematical models of specific dynamic systems and control force generation mechanisms. Active control forces can be supplied by electromagnetic or hydraulic actuators. Analytical and simulation results prove the effective and fast dynamic performance of the online signal estimation as well as a satisfactory active disturbance attenuation on a quarter-vehicle active suspension system.

An enhanced adaptive neuro-fuzzy vehicle suspension control in different road conditions

Suspension system is an important part of vehicle whose main role is to separate the vehicle body from road induced vibrations. This system can also provide vehicle stability and proper performance. Design and control of a suspension system that can adapt to different road conditions with high flexibility is essential. In this study, data were collected from three types of road conditions with different roughness coefficients in various forward speeds for training a suspension model. Primarily, dynamic equations were derived for a linear full model suspension system. The model is then implemented numerically in MATLAB software. After designing fuzzy controller for active control of actuators, the performance of passive and fuzzy suspension systems in different road conditions were evaluated. The results showed performance improvement of suspension system with fuzzy controller. Then, with the use of fuzzy system simulation data, two adaptive neuro-fuzzy controllers namely grid partitioning and subtractive clustering were trained. Finally, four methods were evaluated and the results showed that decrease in linear deflection and acceleration of vehicle body is higher in adaptive neuro-fuzzy controller by subtractive clustering compared to other systems.

Design of a fast real-time LPV model predictive control system for semi-active suspension control of a full vehicle

This article is concerned with the control of a Semi-Active suspension system of a 7DOF Full Vehicle model, equipped with four Electro Rheological (ER) dampers, taking into account their incipient dissipativity constraints. Herein, a real-time, fast, advanced control structure is presented within the Model Predictive Control framework for Linear Parameter Varying (LPV) systems. The control algorithm is developed to provide a suitable trade-off between comfort and handling performances of the vehicle in a very limited sampling period (Ts=5ms), in view of a possible realtime implementation on a real vehicle. The control structure is tested and compared to other standard fast control approaches. Full nonlinear realistic simulation results illustrate the overall good operation and behaviour of the proposed control approach.

Adaptive predator–prey optimization for tuning of infinite horizon LQR applied to vehicle suspension system

This paper puts forward an adaptive predator–prey optimization algorithm to solve the weight selection problem of linear quadratic control applied for vibration control of vehicle suspension system. The proposed technique addresses the two key issues of PSO, namely (a) the premature convergence of the particles, and (b) the imbalance between exploration and exploitation of the particles in finding the global optimum. The main principle behind this optimization algorithm is that the inertia weight is adaptively updated based on the success rate of the particles to increase the convergence, and the predator–prey strategy is reinforced to avoid the particles getting trapped in a local minimum thereby, guaranteeing convergence of the particles towards the global optimal solution. The convergence of the particles towards the global minimum is guaranteed on the basis of a passivity argument. Moreover, the strength of this new adaptive optimization technique to tune the gains of linear quadratic regulator is validated experimentally on a laboratory scale active vehicle suspension system for improved ride comfort and passenger safety.

A fuzzy-based dynamic inversion controller with application to vibration control of vehicle suspension system subjected to uncertainties

Uncertainty or the model error always exists in depicting technique systems. In many cases, the model error is implicitly the time-varying tendency such as in the semi-active railway vehicle suspensions using magneto-rheological damper, where the hysteretic response and time varying of physical parameter value of the magneto-rheological fluid due to system temperature variation are inherent features. To exploit well these systems, a becomingly compensative and adaptive mechanism needs to be set up to deal with both uncertainty and external disturbance. In this study, a new fuzzy-based dynamic inversion controller for semi-active railway vehicle suspensions using magneto-rheological dampers subjected to uncertainty and external disturbance is proposed. The fuzzy-based dynamic inversion controller faces uncertainty and disturbance individually. Regarding external disturbance, a disturbance observer is designed to estimate the compensative quantity. While for the model error influence, a combination of the inference ability of an adaptive fuzzy system and the competence to reach and keep the system stability states of sliding mode control is established via a model so-called fuzzy sliding mode control. First, an optimal sliding mode controller is designed, which is then used as a framework for building the adaptive fuzzy system. Based on Lyaponov theory, adaptive update law for the adaptive fuzzy system is discovered to adjust the sliding mode control adaptive to the system status. Surveys via quarter and half train-car vehicle suspension models including a real system of semi-active railway vehicle suspensions using magneto-rheological damper have been performed, which reflected the positive ability of the proposed method to stamp out vibration.

Optimisation and Control of Vehicle Suspension Using Linear Quadratic Gaussian Control

Abstract The paper deals with the optimal design and analysis of quarter car vehicle suspension system based on the theory of linear optimal control because Linear Quadratic Gaussian (LQG) offers the possibility to emphasize quantifiable issues like ride comfort or road holding very easily by altering the weighting factor of a quadratic criterion. The theory used assumes that the plant (vehicle model + road unevenness model) is excited by white noise with Gaussian distribution. The term quadratic is related to a quadratic goal function. The goal function is chosen to provide the possibility to emphasize three main objectives of vehicle suspensions; ride comfort, suspension travel and road holding. Minimization of this quadratic goal function results in a law of feedback control. For optimal designs are used the optimal parameters which have been derived by comparison of two optimisation algorithms: Sequential Quadratic Program (SQP) and Genetic Algorithms (GA's), for a five chosen design parameters. LQG control is considered to control active suspension for the optimal parameters derived by GA's, while the main focus is to minimise the vertical vehicle body acceleration

Vibration Analysis and Control of Locomotive System

Abstract Vibration is an undesirable phenomenon of ground vehicles like locomotives and vibration control of vehicle suspension system is an active subject of research. The main aim of the present work is to modeling and analysis of locomotive system. The simplified equations for dynamical locomotive are firstly established. Then the dynamical nature of the locomotive without control is investigated, and also active control suspension and passive control suspension are compare and discussed. The obtained simulation shows that suspension of the locomotive with feedback control could decrease the locomotive vibration. According to the above control strategy along with angular acceleration it also reduces the possibility of vibration of the locomotive body, to improves the stability of vehicle operation.

Multimode Coordination Control of a Hybrid Active Suspension

In order to effectively realize the damping control and regenerative energy recovery of vehicle suspension, a new kind of hybrid active suspension structure with the ball screw actuator and magnetorheological (MR) damper is put forward. Firstly, for the analysis of the suspension performance, a quarter dynamic model of vehicle hybrid suspension is established, and at the same time, the mathematical models of MR damper and ball screw actuator are founded. Secondly, the active mode with damping switching control of the hybrid suspension and the semiactive mode with feedback adjustment of the electromagnetic damping force of the hybrid suspension are analyzed. Then, the multimode coordinated control system of the hybrid suspension is designed. Under the cyclic driving condition, the damping performance and energy consumption characteristics of the hybrid suspension are simulated by MATLAB/Simulink software. Finally, the bench tests of the hybrid suspension system are done. The simulation and experimental results show that compared with passive suspension, the root mean square of the sprung mass acceleration of the hybrid suspension with the active mode and semiactive mode is, respectively, reduced by 39% and 16% under the random road. The damping effect of the hybrid suspension system is obvious.

Design of Hardware-In-Loop Simulation Platform for Air Suspension Systems

With the development of control algorithms and structural features in the control system, the hardware-in-loop simulation technology has been widely used after unremitting research and exploration on the basis of off-line simulation. In this paper, the dSPACE real-time simulation system is used to design and develop a hardware loop simulation experiment platform for an air suspension. CarSim vehicle model and suspension control algorithms can be run in the real time. Based on the dSPACE realtime simulation platform mentioned above, a real-time monitoring interface and control program are developed to complete the test of the sliding mode control method of the 1/4 air suspension.

Semi-active adaptive optimal control of vehicle suspension with a magnetorheological damper based on policy iteration

This article attempts to clarify the question of what the essential difference between the optimal and “clipped-optimal” control is that the Hamilton–Jacobi–Bellman or Hamilton–Jacobi–Isaacs partial differential equation is linear or nonlinear. An adaptive optimal control based on policy iteration to the constrained semi-active vehicle suspension system with a magnetorheological damper is presented. The problem of improving the optimal performance of semi-active control suspension system is converted to L2-gain optimal control problem. A two-player policy iteration scheme is employed to solve the Hamilton–Jacobi–Isaacs equation by use of neural networks to approximate optimal policies and value functions in the admissible global region. Simulation results demonstrate that the adaptive optimal controlled semi-active vehicle suspension system outperforms greater than that of the clipped-LQR controlled.

Modified active disturbance rejection control for non-linear semi-active vehicle suspension with magneto-rheological damper

This paper presents a novel idea processing the complex non-linear dynamics of a magneto-rheological (MR) damper and the external road disturbance based on the linear extended state observer (LESO) technology, and further verifies its reasonability by application of linear active disturbance rejection control (LADRC) in the quarter-car non-linear semi-active suspension system. In order to optimize the body acceleration and dynamic tyre load to improve the ride comfort and road-handling ability, a modified active disturbance rejection control, the double linear active disturbance rejection control (DLADRC), is further proposed based on the idea of the hybrid skyhook–groundhook control strategy. LESO is used to estimate the total disturbance including the external road disturbance and the internal non-linear dynamic of the MR damper. For effectiveness validation of the proposed control scheme, comparison results with the existing linear quadratic regulation (LQR) control, hybrid skyhook–groundhook control and adaptive control strategies are presented for the same quarter-car semi-active suspension. It is shown from the simulation comparisons among these several control strategies that the semi-active suspension system with DLADRC has a better control performance on the ride comfort and road-handling ability corresponding to the body acceleration and dynamic tyre load.