Vehicle Suspension Research Articles

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.

LQR-Based Suspension for Heavy Vehicles Considering the Time-Varying Characteristics of Vehicle–Road Interaction

The rapidly increasing demand for heavy vehicles in the transportation sector has led to more severe road damage and significantly higher road maintenance costs. Investigation of active suspension system incorporating vehicle–road interaction (VRI) can provide effective means to reduce the road damage and improve the ride comfort of vehicles. In this paper, an active vehicle suspension controller based on the strongly stable and robust linear–quadratic regulator (LQR) principle is developed for the time-varying VRI system. The coupled system is modeled by a quarter-car traveling on the road modeled by an Euler–Bernoulli beam resting on a viscoelastic foundation. Two types of road irregularities, deterministic sine wave and random, are considered in the numerical studies. A time-frozen technique, by which the linear time-varying system is converted to a time sequence of time-invariant systems, is applied to solve for the coupled responses. Three variables, the dynamic tire load, vehicle body acceleration, and suspension relative displacement, are used to assess the effectiveness of the LQR-based controller in comparison to the passive suspension system. The performance of the active control is investigated for different vehicle speeds, vehicle loads, and road profiles. Numerical studies show that the controller can effectively reduce the road damage and improve the ride comfort, with a slight increase in the suspension relative displacement. This work lays a useful foundation in the problem formulation and system parameter influences for future vehicle suspension design and road damage mitigation including VRI.

A Deep-LSTM-Based Fault Detection Method for Railway Vehicle Suspensions

The timely detection of faults that occur in industrial machines and components can avoid possible catastrophic machine failure, prevent large financial losses, and ensure the safety of machine operators. A solution to tackle the fault detection problem is to start with modeling the condition monitoring signals and then examine any deviation of real-time monitored data from the baseline model. The newly developed deep long short-term memory (LSTM) neural network has a high nonlinear flexibility and can simultaneously store long- and short-term memories. Thus, deep LSTM is a good option for representing underlying data-generating processes. This paper presents a deep-LSTM-based fault detection method. A goodness-of-fit criterion is innovatively used to quantify the deviation between the baseline model and the newly monitored vibrations as opposed to the mean squared value of the LSTM residual used in many reported works. A railway suspension fault detection case is studied. Benchmark studies have shown that the deep-LSTM-based fault detection method performs better than the vanilla-LSTM-based and linear-autoregression-model-based methods. Using the goodness-of-fit criterion, railway suspension faults can be better detected than when using the mean squared value of the LSTM residual.

Vision based road profile estimation for preview-controlled vehicle suspension systems

In this paper, a vision-based road profile estimation method was studied for the control of semi-active and active suspension systems. For the purpose, a monocular camera was used to collect data from the road tests to develop a logic to convert the camera measurements into the road profile data. For the generation of the road profile, alignment of the different sets of camera measurements and their coherence were expressed. Importance of the sensor and process noise removal were shown in recognition of the high frequency content of the road profile, which was a particular interest of the study. Additionally, a density-based clustering algorithm was taken into account to cluster the measured points vertically, to remove the process and sensor noise. The density-based clustering method reduced the noises and allowed detection of the high and low frequency contents of the road.

Analytical Study on Mechanical Energy Recovery and Utilization of New Energy Vehicles

The pursuit of energy efficiency and sustainability in the automotive industry has become increasingly urgent in response to growing environmental concerns. Herein, this paper focuses on the critical challenge of energy dissipation in new energy vehicles, particularly during braking and suspension vibrations. The paper presents two innovative energy recovery solutions aimed at reducing energy losses and enhancing sustainability. In the realm of sustainable transportation, this study critically evaluates the optimization strategies for braking energy recovery in new energy vehicles. A key recommendation is the integration of a permanent magnet synchronous motor combined with an advanced fuzzy control system. Such an amalgamation not only heightens energy efficiency but also substantially extends the driving range of electric vehicles. Beyond braking energy, the research casts light on an often-overlooked energy source: the vibrational energy from vehicle suspensions. By introducing an innovative electromagnetic damper design coupled with the strategic incorporation of piezoelectric materials, the study unveils avenues to both improve suspension dynamics and transform vibrational energy into usable electrical power. While there are current technological and economic challenges, the ongoing innovations in the design and control processes of new energy vehicles highlight the profound potential within this domain. The insights offered in this context further emphasize the critical need to expand the horizons of sustainable transportation design and management approaches.

Non-Invasive Identification of Vehicle Suspension Parameters: A Methodology Based on Synthetic Data Analysis

In this study, we introduce an innovative approach for the identification of vehicle suspension parameters, employing a methodology that utilizes synthetic and experimental data for non-invasive analysis. Central to our approach is the application of a basic local optimization algorithm, chosen to establish a baseline for parameter identification in increasingly complex vehicle models, ranging from quarter-vehicle to half-vehicle (bicycle) models. This methodology enables the accurate simulation of the vehicle dynamics and the identification of suspension parameters under various conditions, including road perturbations such as speed bumps and curbs, as well as in the presence of noise. A significant aspect of our work is the ability to process real-world data, making it applicable in practical scenarios where data are obtained from onboard sensor equipment. The methodology was developed in MatLab, ensuring portability across platforms that support this software. Furthermore, the study explores the application of this methodology as a tool for denoising, enhancing its utility in real-world data analysis and predictive maintenance. The findings of this research provide valuable insights for vehicle suspension design, offering a cost-effective and efficient solution for dynamic parameter identification without the need for physical disassembly.

Design of sustainable energy harvesters using a 3D car suspension system model and half-width speed bump

This study aims to not only design a vibration energy harvester integrated in a three-dimensional (3D) multi-particle system but also investigate the longitudinal and lateral body sway and the effect of front and back wheel interlocking caused by the eccentric loading of the vehicle. Using multidimensional vehicle suspension system vibration modes for analysis, this study evaluates the impact of lateral and longitudinal eccentricity on the displacement of the four-suspension system wheel axes. In addition, this study discusses the effect of discontinuous half-width sinusoidal speed bump on power generation and maximum power generation capacity under good ride comfort conditions. To maximize the efficient electrical power from the car's suspension system through the use of energy harvesters, we have employed the simulated annealing algorithm, a robust global optimization technique. The objective function chosen for this optimization is the root-mean-square (RMS) electrical power, represented as WTT(RMS). In addition to this, we have considered the comfort experienced by passengers, incorporating the ride comfort efficiency into the objective function during the optimization process. As a result of this optimization, a 3D car model equipped with four energy harvesters has been fine-tuned to achieve a significant increase in induced electrical power, ultimately reaching an impressive 0.2 W.

Optimizing Hydro-Pneumatic Inerter Suspension for Improved Ride Comfort and Handling Stability in Engineering Vehicles Using Simulated Annealing Algorithm

This study introduces a novel hydro-pneumatic inerter suspension (HPIS) system for engineering vehicles, aiming at enhancing ride comfort and handling stability. The research focuses on addressing the limitations of conventional suspension systems by incorporating an inerter element into the vehicle suspension. The unique aspects of HPIS, such as nonlinear stiffness and nonlinear damping characteristics of the hydro-pneumatic spring, are explored. Firstly, a half-car dynamic model of the HPIS suspension is established, and an improved simulated annealing algorithm is applied to optimize the suspension parameters. Then, we compare the dynamic performance of different HPIS structures, specifically parallel and series layouts. For practical analysis, a simplified three-element HPIS suspension model is used, and the suspension parameters are optimized by a simulated annealing algorithm at speeds of 10 m/s, 15 m/s, and 20 m/s. Key findings reveal that compared to the traditional suspension system of S0, the front and rear suspension working space of S1 decreased by 40%, 40.1%, 40.2% and 30.7%, 30.8%, 30.9%, while with the body acceleration and pitch acceleration deteriorated by 3.1%, 3.2%, 3.3% and 63.4%, 63.8%, 64.0%. However, the S2 can improve all the dynamic performance and offer better ride comfort and handling stability.

Nonstationary time-frequency characteristics of vehicle suspension systems based on evolutionary power spectral density

Improving the ride comfort for vehicles that travel at varying speeds is a nonstationary problem and has been an increasingly important topic for suspension system research. Accurate identification of frequencies associated with the resonant responses is needed for effective design of active suspension control strategies. However, traditional time-frequency (TF) methods have resolution limitations in either the time domain or the frequency domain. This paper proposes a new methodology to employ the evolutionary power spectral density (EPSD) to describe the responses of vehicles in the time-frequency domain. The key to calculate the responses in nonstationary cases is to derive the nonuniform modulation function which is obtained by the pseudo excitation method. To illustrate the applicability of the proposed method, an example of a seven-degree-of-freedom vehicle model is investigated in which the nonstationary excitations acting on the wheels are computed by the nonuniform modulation function and a precise integration method. Results show that resolutions obtained by the EPSD are more precise than the traditional TF methods with less than 0.2 Hz of bandwidth in both the lower frequency range at the first natural frequency of 1 Hz and in the higher frequency around 10 Hz. Moreover, the changing of the resonant frequency with varying speeds provides the insights, from the perspective of human body’s sensitivity to frequencies of vibration, to improve the ride comfort for vehicles under nonstationary driving conditions.

Disturbance observer-based sliding mode control of active vertical suspension for high-speed rail vehicles

Disturbance observer-based sliding mode control (SMC) on the active vertical suspension (AVS) is developed to suppress the car body’s rigid and flexible vibration to improve ride comfort for a high-speed rail vehicle. A vertical-dynamics-intended vehicle model is foremost built with the bounce, pitch, and bending mode of the car body involved. Two sliding surfaces and disturbance observers are then designed for SMC, which only require the car body states, obviating the bogies’ states. The observer is successful in estimating the effect of unknown track irregularities perturbation as well as externally straightforwardly excitations on the car body with good accuracy. Control efficacy is verified through comparison with passive cases and sky-hook controls. With modal damping below 2% in passive cases, the mode shape function, especially with large displacement at the suspension support, would enlarge the car body acceleration. Moreover, the longitudinal traction rod can significantly multiply the flexible vibration at certain speeds. Comparative studies indicate that SMC provides satisfactory outcomes in the rigid and bending vibration suppression when all the car body’s three modes are considered in the sliding surface. However, it requires a high-frequency response actuator and allows a tighter tolerance of the control time delay than the sky-hook control.

A nonlinear model predictive control for air suspension in hub motor electric vehicle

The hub-motor electric vehicle (HM-EV) is considered as an ideal configuration for electric vehicles (EVs). However, the electromechanical coupling effect deteriorates HM-EV ride comfort, which limits its widespread application in EVs. In this study, the HM-EV dynamic system with air springs is proposed to intervene in vehicle attitude and ride comfort. The HM-EV dynamic model with air spring, considering the electromechanical coupling effect, is established and the test validation is investigated. Then quasi-infinite horizon nonlinear model predictive control (QIH NMPC) is designed to improve the longitudinal and vertical dynamic performance. The dynamic performance of passive suspension, air suspension based on QIH NMPC, air suspension based on MPC, and PID control receptively, are compared under several random road scenarios. Finally, the results indicated that the proposed control algorithm can improve ride comfort, reduce motor vibration, and improve longitudinal and vertical dynamic performance.

Design Analysis and Optimization of Coil Spring for Three-Wheeler Vehicles Using Composite Materials

The quest for lightweight, efficient, and corrosion-resistant coil springs for vehicle suspension systems has led to the exploration of alternative materials beyond traditional steel. This study delves into the potential of composite materials, particularly carbon/epoxy and carbon/carbon nanotube/epoxy, as replacements for conventional steel coil springs in light vehicles. Through a comprehensive analysis of mechanical properties under static and dynamic loading conditions, the study demonstrates the superior performance of composite springs compared to their steel counterparts. After optimization, the deflection of the carbon/carbon nanotube/epoxy and carbon/epoxy springs decreased to 15.003 mm and 18.703 mm, respectively, and the maximum shear stress decreased by 64.63% and 62.2%, respectively. Likewise, strain energies increased to 2.3644 and 3.5616, respectively. The springs were also studied under dynamic conditions, and the result showed these springs have the ability to perform in dynamic conditions. The carbon/carbon nanotube/epoxy composite emerged as the frontrunner, exhibiting remarkable improvements in shear stress, fatigue life, strain energy, and deformation properties. The study highlights the ability of carbon/carbon nanotube/epoxy composite springs to significantly reduce weight, enhance efficiency, and extend fatigue life, making them a promising alternative for next-generation vehicle suspension systems.

Feasibility of Modernizing the Acceptable International Roughness Index Value

The U.S. National Highway System has set a standard for acceptable pavement roughness, measured by the international roughness index (IRI) at less than 2.68 m/km (170 in./mi). This value corresponds to a present serviceability rating (PSR) of 2.5, where half of the highway drivers perceive the pavement ride quality as unacceptable with a repair need. For over 3 decades, public transportation agencies in the U.S. have used this IRI value to determine when pavement surface rehabilitation is needed. However, with advancements in vehicle suspension systems improving ride quality, the current acceptable IRI value corresponding to 2.5 PSR has been questioned. To our knowledge, studies in the literature have yet to explore this issue. This study aims to evaluate the feasibility of modernizing the acceptable IRI value through nationwide, large-scale field testing, which is typically expensive and time-consuming. The IRI-present serviceability index (PSI) equation that is capable of converting the acceptable IRI value into the estimated 2.5 PSR (i.e., the PSI) was selected and calibrated by applying test quarter-car parameters synthesized through a literature review. Then, the calibrated IRI-PSI equation was used to find a new acceptable IRI value that was evaluated for the statistical significance and the financial benefits of the new value. The evaluation results suggest a need for a nationwide field test to modernize the current acceptable IRI value. Public transportation agencies can easily adapt the technical approach we used to calibrate the IRI-PSI equation without altering their current IRI measurement systems.

A novel semi-active control of an integrated chassis and seat quasi-zero stiffness suspension system for off-road vehicles

This article introduces an innovative semi-active suspension system for off-road vehicles, incorporating a quasi-zero stiffness suspension to enhance driver comfort. The system includes a central pneumatic spring, double-acting pneumatic linear actuators for adjustable stiffness, and magnetorheological dampers for controlled damping. Using Lyapunov stability theory, a static output feedback control law is designed to address uncertainties in road profiles, driver body parameters, and actuator saturation, relying on measured variables as feedback. Performance constraints focus on driver head acceleration, suspension displacement, and dynamic tire load. The control law problem is converted into a convex optimization problem with linear matrix inequalities. The new semi-active QZSS system is theoretically tested via Matlab simulations and validated through hardware-in-the-loop testing. Comparative analysis between passive QZSS and the new semi-active QZSS on different roads, and vehicle speeds closely aligns with simulation results, with minor disparities attributable to network discrepancies and signal interruptions. Impressively, the semi-active QZSS system reduces driver head vertical acceleration between 26.53 and 35.0% compared to passive air QZSS, showing potential for significantly improving ride comfort, reducing vibration transfer, and enhancing driver wellbeing with minimal energy requirement.

A contrastive characterization of pure Mg and AZ91D alloy based on the testing of mechanical, corrosion, wear, and erosion properties

Abstract Magnesium alloy of grade AZ91D is utilized for a variety of applications in aircraft design and frames, as well as vehicle engine radiators, bumpers, and suspension components to reduce the weight of automobiles. This research compared the mechanical, corrosion, wear, and erosion resistance of pure Mg to that of AZ91 alloy. The corrosion media was NaCl, NaOH, and MgSO4, and the weight loss method was utilised to evaluate corrosion. The pin-on-disc configuration was utilized to assess the dry sliding wear mechanism of the Pure Mg and AZ91D alloy. Pure monolithic Mg and AZ91D magnesium alloy have a low resistance to wear as a result of an increase in contact temperature brought about by a shift of operational conditions. Erosive wear is caused when solid particles in a liquid or air jet strike a surface. Significantly influencing the erosive wear are particle velocity, impact angle, and erodent particle size. In this work, the erosive wear of AZ91D was studied using an Air jet erosion tester. SiO2 was used as the eroding material, and the flow rate of the eroding material and air was 5 gm min−1. The erosive factor experiments are designed using Taguchi orthogonal array (L16). The erosive factor response is erosion rate and primarily regulated by three factors as angle (30°, 45°, 60°, and 90°), time (5 and 10 min) and, contact pressure (1 and 2 bar). The results of the experiments showed that the rate of wear increased with increasing pressure, and that the angle of impact of the jet at 60° caused the most wear of any of the tested angles. Analysis of variance (ANOVA) shows that time is the most important factor in determining erosive rate for AZ91D. SEM is used to investigate the structure and morphology of worn-out materials, and its findings are then confirmed.

Development of a Novel Suspension System for Electric Vehicles Based on Mechanical Principles

Abstract The electric vehicle industry has witnessed significant growth in recent years, prompting heightened research interest in its various components. The suspension system, serving as a critical power-transmitting device between the frame and the axle, has garnered particular focus. This system is pivotal in meeting the dual performance objectives of ensuring driving smoothness and enhancing maneuvering stability. Accordingly, this study investigates the structural types of suspension systems and advances the design of a suspension guiding mechanism specifically tailored for electric vehicles. At the same time, the dynamic model of active suspension is constructed, and the algorithm for optimizing and establishing the active suspension system for electric vehicles is used. The simulation experiments on the suspension system, the control optimization method of the system in this paper’s car body spring loaded mass acceleration response, dynamic deflection ring, and the control input are stable between -0.4~0.5m/s², -0.005~0.01m and the suspension system’s between -0.7~0.6N, respectively. Moreover, the car body displacement and speed are gradually stabilized at about ±0 compared to the motion speed. In this paper, the suspension system can effectively solve the problem of automobile damping control and reduce the impact suffered by the body so as to improve the smoothness of the body in the process of driving and the operation of the stability of the new for the development and improvement of the suspension system in the electric vehicle industry to provide a reliable method.

Performance analysis of fuzzy-LQR and fuzzy-LQG controllers for active vehicle suspension systems

Suspension systems in vehicles are crucial to both ride quality and driving security. The challenge of creating an effective control mechanism for automotive active suspension systems is addressed in this work. In the event of unforeseen road disturbances, the active suspension systems are intended to deliver a more pleasant ride and good handling. Fuzzy-Linear Quadratic Gaussian (FLQG) and Fuzzy-Linear Quadratic Regulator (FLQR) controllers adapting to road disturbances are proposed to enhance vehicle comfort through the reduction of the driver's overall body acceleration. The simulation findings demonstrate that the FLQR and FLQG controllers are efficient in adjusting the automotive suspension configuration under varying road profiles compared to those of the conventional LQR and LQG controllers.

Development and Evaluation of Artificial Neural Networks for Real-World Data-Driven Virtual Sensors in Vehicle Suspension

Development and Evaluation of Artificial Neural Networks for Real-World Data-Driven Virtual Sensors in Vehicle Suspension

Modeling and Simulation of Semiactive and Active Suspension System using Quarter Car Model

A passive suspension system is used by the automotive industry to control the motion of the vehicle. Nowadays, semiactive and active suspension systems are a requirement of commercial vehicles to improve performance characteristics and road comfort. The objective of the paper is to present a comprehensive analysis of passive, semiactive, and active suspension systems. The fuzzy logic controller is used to present the active suspension system. The characteristic of the shock absorber (damper) is non-linear and hysteresis in nature. Hence, a Magneto-rheological (MR) damper-based Bouc-Wen model is utilized to present the semiactive suspension. The comparative analysis of vehicle suspension characteristics has been carried out by using a bump road profile. The modeling of the Bouc-Wen model and quarter car system is carried out in the Simulink environment. The simulated results show that the semiactive and active suspension systems can be a better option for vehicle suspension systems to provide passengers with road comfort.

Study of the operation of active suspension with magnetic fluid-less shock absorbers

The article presents the structure of an active suspension system for a commercial vehicle aimed at enhancing system performance. Solutions for integrating electromagnetic dampers into an intelligent active suspension system are identified. The behavior of the suspension system under challenging road conditions is examined. A block diagram of the active suspension system with a controller is provided. The article is published based on the findings of a research project conducted as part of a grant competition for scientific research projects by the teaching staff of Saint Petersburg State University of Architecture and Civil Engineering (SPbGASU) in 2024. Keywords magnetic shock absorbers, electromagnetic shock absorbers, suspension, damping, modeling