Suspension Parameters Research Articles

Effect and Mechanism of Metakaolin Powder (MP) on Rheological and Mechanical Properties of Cementitious Suspension.

The effects of metakaolin powder (MP) on the microscopic rheological properties and macroscopic flow parameters of cementitious suspension under various water–cement ratios were investigated. By analyzing the changes in the bonding strength coefficient and water film thickness (WFT), the mechanism of MP on flow and rheological parameters can be explored. Further, the effect of MP on mechanical properties was explained from the perspective of water absorption kinetics and hydration activity contribution rate. The incorporation of MP can reduce the flow rate and flow spread and increase the compressive strength, plastic viscosity, yield stress and thixotropy, and the effects of MP were distinctive under various W/CM ratios. The bonding strength coefficient and WFT increased and decreased with increasing MP replacement content, respectively. The regression analysis results revealed that the bonding strength coefficient and WFT were the most important factors influencing the macroscopic flow parameters and rheological parameters, which indicated that MP influenced the rheology and flowability of cementitious suspension by affecting the flocculent structure and particle distance. Compared with WFT, the bonding strength coefficient had a stronger effect on these parameters. The MP improved the compressive strength by reducing the average pore size and porosity and increasing the pore uniformity and hydration activity contribution rate of hardened paste, and this improvement was enhanced by increasing curing age.

Non-intrusive determination of shock absorber characteristic curves by means of evolutionary algorithms

The fault detection in the components of the suspension system of road vehicles is of great importance. The optimal performance of the suspension system has a big influence on the safety and stability of a vehicle. Vehicle inspection services make use of different methods of fault diagnosis of shock absorbers without the need to remove them from the vehicle. These methods generally provide an average value of the damping coefficient or a value related to the efficiency of the damper. Next, acceptance or rejection criteria are used to evaluate the condition of the damper. Consequently, there is currently no objective criterion for detecting the malfunctioning or faulty condition of shock absorbers. In this work, a novel methodology capable of obtaining the complete force–velocity characteristic curve of the shock absorber is proposed. For this purpose, the importance of using an appropriate tyre model to obtain the suspension parameters is first studied. In addition, the displacements of the sprung and unsprung masses and the excitation of the system are obtained experimentally. Next, the points that model the complete characteristic curve of a shock absorber are obtained by means of an optimization method based on evolutionary algorithms. Real tests have been conducted on a complete vehicle suspension test bench to verify the effectiveness of the proposed methodology.

Pitching vibration suppression of cab system based on the suspension longitudinal coupling effects

<p indent="0mm">The pitching vibration of truck cabs can easily cause driving diseases, such as sciatica and cervical spondylosis, which can seriously disrupt a driver’s normal life. To effectively suppress the pitching vibration of the cab system, a cab’s longitudinal coupled suspension system is proposed. First, the configuration and mechanism of the coupling vibration suppression effect were thoroughly described. The dynamic model of the driver-seat-cab system was then established and verified. The effects of suspension parameters on vibrations were investigated, and a method for matching the parameters for pitch vibration suppression was proposed. Finally, the vibration suppression efficiency of the suspension system was compared and analyzed based on an example. The results showed that compared with the cab-uncoupled suspension system, the RMS (root-mean-square) values of the cab pitch, the driver’s head pitch, and longitudinal acceleration under random road conditions are reduced by more than 28.0%. The RMS values of the cab, the seat, and the driver’s organs vertical acceleration are reduced by approximately 2.0%. Hence, the proposed suspension system can effectively suppress the pitching vibration of the cab system to ensure vertical comfort and significantly improve ride comfort.

Parametric synthesis of car suspension

Problem. When driving a vehicle with comfortable suspension settings, there is a high probability that such adjustments may, firstly, cause discomfort to the driver and passengers, and secondly, when cornering, there is a high probability that the vehicle will overturn. A stiffer suspension leads to discomfort when driving on bumps. To choose the optimal parameters of the car's suspension, it is necessary to take into account the various parameters of the car's suspension, its settings and the features of the road surface. Goal. Solving the problem of choosing the values of the varied parameters of the car suspension - the coefficients of stiffness of the elastic elements and the average values of the damping coefficients of the shock absorbers, which provide a comfortable state of the driver and passengers while driving. Methodology. The approaches adopted in the work to solve the problems are based on the algorithmic method of parametric synthesis of dynamic systems. Results. The obtained maximum values of generalized coordinates, speeds and accelerations of the sprung part of the car body, as well as the minimum values of functionalities, with the help of ratios are possible to estimate the values of weights of additive functionality based on MathCAD software package. With the help of the algorithmic method of solving the problem of parametric synthesis of a dynamic system it is possible to it automate. Analysis of the process with the specified coefficients allows to detect high efficiency of damping of vertical oscillations of the under-sprung part of the car body. The amplitude of the linear displacement of the center of mass of the body does not exceed 0,02 m, and the amplitude of the generalized veloc-ity of the centre of mass of the sprung part of the housing does not exceed 0,08 m/s-1. Originality. The obtained parameters allow to minimize the time for selection of average values when designing the vehicle suspension. Practical value. The results can be recommended when studying the design features of vehicle suspensions. Thanks to the optimization of the MATLAB software package, modeling with different suspension parameters is possible.

Machine Learning Road Recognition Based on Wavelet Decomposition

Driving road conditions have a great impact on vehicles and personnel. According to road conditions, reasonable adjustment of components such as suspension and electronic control unit parameters can effectively improve ride comfort and handling stability. This paper studies the method of road Recognition from the perspective of machine learning, and compares the Recognition effect of BP neural network and SVM. Using wavelet decomposition, a time-frequency analysis method, the original signal is decomposed into different frequency band signals, and the difference between different road surfaces can be amplified. The commonly used statistics are screened by Fisher’s criterion to obtain excellent data of each dimension of the sample. The method can achieve an Recognition accuracy of nearly 100% in the simulation experiment. In the vehicle experiment, the four kinds of road surfaces are well distinguished, and the comprehensive accuracy is about 82%.

The influence of shock absorber characteristics’ nonlinearities on suspension Frequency Response Function estimation and possibilities of simplified characteristics modelling

The paper shortly presents shock absorber design evolution and resulting achieved characteristics. The way in which suspension performance is evaluated is described giving information about models used for suspension parameter tuning during simulation testing of suspension transmissibility (FRF - Frequency Response Function) for most important suspension assessment criteria. More detailed information about models of shock absorber (damper) nonlinearities of characteristics allows for description of methods of linear and nonlinear suspension models FRF estimation. Testing linear suspension model is possible with the use of analytical transfer function formulas which were used to verify methods for estimation FRF using estimated power spectral density functions of excitation and response signals. Designing appropriate input signal allowing to get useful response signals was necessary to for the success of this research. Proposed FRF estimation method was used for linear estimation of nonlinear suspension for a given range of working condition. It was demonstrated that there is no single value of a damping coefficient which would make the linear model responses similar to the responses of the nonlinear one. Then the bilinear model was proposed, giving good damper static nonlinear characteristic.

Methodology of Force Parameters Justification of the Controlled Steering Wheel Suspension

The methodology for selecting the main force parameters of nonlinear non-conservative suspension for the main performance characteristics of wheeled vehicles has been developed based on the longitudinal-angular oscillations. The following has been established: a) change limits of static deformation of the elastic suspension system and its other parameters at which the basic operational characteristics for various ranges of amplitude change are satisfied; b) the amplitude of the initial perturbation of oscillations depending on the shape of the inequality and its entry speed; c) the influence of the main characteristics of damping devices on the amplitude-frequency characteristics. The results of this work can be a basis for the choice of such parameters of the considered controlled suspension, which ensure the stability of the vehicle along the curved sections of the road, its controllability, etc.

Interval fuzzy robust non-fragile finite frequency control for active suspension of in-wheel motor driven electric vehicles with time delay

This paper proposes a fuzzy non-fragile finite frequency H∞ control algorithm for the active suspension system (ASS) of the electric vehicles driven by in-wheel motors with an advanced dynamic vibration absorber (DVA). Firstly, an interval type-2 Takagi-Sugeno (T-S) fuzzy model is established to formulate the nonlinear time-delay ASS with the uncertainties of sprung mass, unsprung mass, suspension stiffness, and tire stiffness. Secondly, a differential evolution (DE) algorithm is adopted to optimize the parameters of vehicle suspension and DVA. Thirdly, a non-fragile finite frequency H∞ control controller is developed under the consideration of controller perturbation and input delay to improve the comprehensive performance of the chassis under the finite frequency external disturbances. Finally, simulation tests are carried out to verify the effectiveness of the proposed controller.

Optimization Design for Suspension System Based on Response Surface Method and NCGA Algorithm

For effective and quick selection of hard point coordinate parameters of suspension to improve the handling stability of vehicles, an optimization method was put forward to some certain suspension system by combining the response surface method and NCGA algorithm. A dynamics simulation model was established first to the Macpherson suspension system of some certain mini-van and the sensitivity analysis was carried out to hard point coordinates of the corresponding suspension to find the coordinate parameters whose sensitivities are higher; moreover, an approximate mathematical model was established between the wheel alignment parameters and the selected coordinate parameters in accordance with the response surface method and the corresponding accuracy verification was carried out; and the positioning parameters were grouped rationally and the unified objective function was established by utilizing the direct weighting method; in addition, optimization design was carried out to the established objective function by combining the neighborhood cultivation genetic algorithm (NCGA). Results indicate that the optimized positioning parameter variables are reduced in different degrees so as to further improve the handling stability of vehicles and verify some certain effectiveness of our methods.

An interval-based multi-objective robust design optimization for vehicle dynamics

This study presents an Interval-based Multi-objective Robust Design Optimization (IB-MORDO) algorithm applied to a vehicle dynamic problem. The proposed algorithm optimizes a full 15 degrees-of-freedom (15-DOF) vehicle model, subjected to a double-lane change (DLC) maneuver under random road profiles, to attain driver comfort and safety. This study does not make assumptions about uncertain parameter statistics; instead, the uncertainties are quantified using a non-probabilistic α-cut level interval analysis. These uncertainties are applied to the system parameters and design variables to ensure robust results. After the optimization process, the root mean square (RMS) vertical acceleration at the driver’s seat resulted in a robust solution of 1.041 m/s2 and a parameter interval radius (IR) equals to 0.631 m/s2, whereas the RMS lateral acceleration at the driver’s seat resulted in a solution of 1.908 m/s2 with an interval radius of 0.168 m/s2. Unlike the Robust Optimization, the algorithm proposed herein considers uncertainties at system parameters and design variables without assuming any statistical data. HIGHLIGHTS An Interval-based Robust Multi-objective Optimization procedure is proposed and tested on a 15-DOF vehicle model. Αn α-cut level methodology is used to deal with the uncertainty propagation. Resulted optimal suspension parameters minimize center and interval radius of driver’s vertical and lateral accelerations.

Maneuver-based deep learning parameter identification of vehicle suspensions subjected to performance degradation

A novel parameter identification method was proposed for vehicle suspensions subjected to performance degradation. The proposed method does not require the measurement of the stiffness and damping coefficients of suspensions. Instead, it uses vehicle states to calculate the stiffness and damping coefficients based on an efficient multibody model and inverse dynamics. First, a full-vehicle system was modelled using a semirecursive multibody formulation, and the dynamic properties of suspensions, chassis frame, and tires were considered. Second, dynamic simulations on a bumpy road were performed, and vehicle state data were collected. A deep neural network (DNN) model, whose inputs and outputs were vehicle states and suspension parameters, was developed. The DNN model can estimate the stiffness and damping coefficients based on vehicle states measured by sensor networks. The parameter identification was achieved by deep learning of the relationship between vehicle states and suspension parameters in a given maneuver. Finally, the model accuracy was investigated in terms of different DNN inputs, data samples, and hidden layers. The results showed that the DNN model predicts accurate stiffness and damping coefficients in real time. This maneuver-based parameter identification method can be used for the condition-based monitoring or fault diagnosis of vehicle suspensions subjected to performance degradation.

Vibration characteristics analysis and suspension parameter optimization of tractor/implement system with front axle suspension under ploughing operation condition

To improve the riding comfort and driving safety of the tractor system, it’s necessary to build a vibration model of wheeled tractor/implement system to analyze its corresponding vibration characteristics. A discrete element model of plough-soil coupling system was developed in this work to obtain the tillage resistance and its effectiveness is verified through experiment. Then, the vibration model of wheeled tractor/implement system with front axle suspension under ploughing condition was constructed and the corresponding vibration characteristics of the tractor system under road transportation, farmland transportation and plough operation conditions were simulated. It’s demonstrated that the simulated vibration responses agree well with the measured data and the validity of the proposed model is proved. The simulation results show that the natural frequency of the tractor system almost remains constant under the three working conditions above and the natural frequencies of vertical vibration for front axle, cabin, driver seat and implement are 2.09 Hz, 2.84 Hz, 2.84 Hz and 2.09 Hz, respectively. The existence of front axle suspension will deteriorate the ride comfort of driver but improve the handing stability obviously. The farmland road roughness and tillage resistance can reduce the vibration responses of the wheeled tractor/implement system with front axle suspension significantly. With the increase of tillage speed or depth, the vibration responses of the tractor system rise tremendously. When the tillage speed or depth is constant, the largest vertical vibration acceleration exists on the front axle. In addition, the multi-objective optimization of stiffness and damping parameters for the front axle suspension is implemented through particle swarm algorithm and the optimal stiffness and damping are recommended to be 60 kNm−1 and 8.919 kNsm−1, respectively.

Modal parameters-based hunting stability analysis of high-speed railway vehicles considering full range of equivalent conicity

The balance of vehicle parameters to avoid both the carbody and bogie hunting instabilities existing at different stage of vehicle operation is a long-standing problem. However, most of the existing researches focus on a single form of hunting instability and only take specific value of equivalent conicity as the worst case of wheel-rail contact relationship. To face this challenging problem, this paper studies the hunting stability of high-speed railway vehicles from the perspective of modal parameters based linearized analysis. The root locus analysis is carried out first to observe the modal information and hunting stability. The continuous modal tracking method is exploited to understand the variation regularity of each mode under the speed parametric excitation, especially when the frequency coupling occurs. Two objective functions related to the minimal damping ratio are proposed to indicate the severity of carbody and bogie hunting instabilities, respectively. The proposed objective functions consider the full range of running speed and wheel-rail contact conicity during operation. Starting from the objective functions, the sensitive analysis and a vector evaluated genetic algorithm are implemented to optimize the suspension parameters. Finally, the optimal solution of the suspension parameters is obtained after a generation of 20. The research method presented in this paper deepens the understanding of hunting motion and improves the vehicle stability in a simple, efficient and effective way.

Modal vibration decomposition method and its application on multi-mode vibration control of high-speed railway car bodies

The vibration of a railway car body is a superposition of the vibrations of its various modes. It is typically easy to obtain the physical vibration of the car body using sensors in an in situ or a simulated test vehicle. However, it is difficult to determine the modal vibration of the body and its contribution. There are no effective multi-mode vibration control methods for the car bodies. This study proposes a modal vibration decomposition method (MVDM) based on singular value decomposition (SVD) and least squares fitting (LSF). Accordingly, the physical vibration of a railway car body is decomposed into modal vibrations. A method for calculating the modal contribution factor (MCF) is presented, and the dominant flexible modes of the car body are determined and considered the target for the vibration control method. Several pieces of equipment are considered as dynamic vibration absorbers (DVAs) to control the multi-mode vibration of the car body using the dynamic vibration absorption theory and determine the installation parameters of the individual equipment. Finally, the effectiveness of vibration control is verified through dynamic simulations. The results demonstrate the effective decomposition of the physical vibration of the car body into various modal vibrations using the MVDM. This provides accurate data for the MCF calculation and determination of the flexible modes of the car body. The proposed method reduces the vibration of the target modes and improves the ride quality of the railway vehicle. At the optimal damping ratio, the vibration of the DVA-based equipment itself is acceptable. This allows for multi-mode vibration control without requiring extensive modification to the car body structure or suspension system parameters of the vehicle.

Modelling and analysis of passenger rail vehicle for the improvement of critical speed using MR damper based semi-active suspension

Developing economies focus to enhance train speed by introducing high speed corridors and upgrading existing rail infrastructure. Higher speed has adverse impact on vehicle stability and ride comfort. Therefore, in order to improve critical speed and ride comfort magneto-rheological (MR) based dampers are used. Here, the lateral dynamics of an Indian passenger rail vehicle is expressed with 17 degrees of freedom model and after validation, it is used to examine the effect of suspension parameters such as damping and stiffness on critical speed. Moreover, a sensitivity analysis is performed and it is found that critical speed is the most sensitive to secondary lateral damping coefficient. Therefore, these dampers are replaced with MR fluid dampers to evaluate improvement in stability and critical speed. The modified Bouc-Wen model is formulated to characterise the behaviour of the MR damper. Herein, two distinct controllers: disturbance refusal and damper force tracking control algorithms are employed to govern the entire system. Measured random track irregularities are applied as an input to simulate the system. The results reveal that the semi-active suspension improves the critical speed by 19.38 km/h (9.89%) when compared to the existing passive suspension, and significantly reduces the vibration responses of the carbody in a wide frequency spectrum at higher speeds of the train.

Optimal Design of Suspension System of Four-wheel Drive Baja Racing

In order to match the four-wheel drive system of Baja racing, improve the handling stability and driving comfort of the car, and optimize the parameter design of the suspension. Establish a suspension system model in ADAMS, conduct motion simulation, analyze important suspension parameters, modify the suspension hard points according to the analysis results, and optimize the suspension parameters. Finally, a set of excellent suspension parameters is obtained, and the performance of the suspension system can be improved. The suspension parameters of the simulated racing car have been determined, and other performance parameters have also been improved through hard-point modification. Using ADAMS to perform motion simulation of the suspension system saves time and can efficiently realize the optimal design of the suspension system.

Suspension parameters design for robust and adaptive lateral stability of high-speed train

An adequate hunting stability margin is required through the optimisation and matching of bogie suspension parameters for high-speed trains. Moreover, the dynamics design is particularly important for the robust lateral stability to adapt to wheel–rail wear and track deformation. The hunting stability margin of vehicles, as well as the wheel–rail contact state adaptability should be taken into account. In this regard, the robust hunting stability Pareto optimisation of bogie suspension parameters for different wheel–rail wear stages is executed. A method for the centralised optimisation of key bogie suspension parameters based on vehicle lateral robust stability is presented, and the principle of two typical parameters matching for high-speed vehicles is summarised. In addition, in order to make the vehicle automatically adapt to different wheel–rail geometry contact states without any sensors and control systems, a new idea of frequency-dependent stiffness (SDF) of yaw damper is proposed to ensure the lateral stability margin especially in extreme wheel–rail contact states, which is verified through the vehicle linear system stability and ride comfort comparative analysis. Finally, the adaptive stabilisation mechanism of the vehicle with the frequency-dependent stiffness of yaw damper is clarified.

Optimization and Control of Vehicle Vertical System with Suspended In-Wheel Motor

This paper presents an optimization and control approach for vehicle vibration system with suspended in-wheel motor to reduce the vertical negative effects. Vibrations caused by the motor unbalanced radial force arising from road surface can be mitigated through the proposed ap-proach. A four quarter in-wheel motor suspension system with dynamic vibration absorber is established, and analytical switch reluctance motor (SRM) model is derived using Fourier series. Cuckoo search based optimal matching method between suspension and vibration isolator pa-rameters is designed to improve the vibration performance while reducing the external disturb-ance effect on the motor air gap with typical road excitations. On the basis of the optimal matching results, a hybrid control strategy is proposed for the in-wheel motor suspension, and the sus-pension and isolator dampers are considered as the semi-active device to assign the hybrid con-trol force according to model responses. Simulation results indicate that the optimized model can achieve better vibration characteristics, and the hybrid controller can improve the riding comfort and handling stability effectively.

Effect of suspension parameters towards the fabrication of BSCCO films by electrophoretic deposition

Superconductor Bi-Sr-Ca-Cu-O (BSCCO) thin films were fabricated on silver by electrophoretic deposition (EPD) method. By investigating the effects of solvents and I2 additives on the properties of suspension prepared of BSCCO powder, the particle charging mechanism is analyzed. Studying the effect of different solvents on the structure of BSCCO powder, isopropanol is the best dispersion solvent. Through the optimization of the I2 concentration, the results show that the optimal concentration of I2 is 0.08 mg ml−1. The processing parameters critically influencing the morphology of BSCCO films are identified and optimized to obtain uniform films with high packing density of BSCCO particles. After heated at 820 °C for 20 h, the smoothest surface morphology, high c-axis orientation, and highest critical temperature(Tc) of 82 K are obtained from the film prepared with optimized suspension.

Adaptive Fuzzy PID Control Strategy for Vehicle Active Suspension Based on Road Evaluation

The paper proposes a fuzzy proportion integral differential (PID) control strategy based on road estimation to meet the different performance requirements of active suspension for comfort and safety under different road conditions in view of the uncertainty of vehicle suspension parameters and random road perturbations. First, flexible neural tree (FNT) is used to estimate the vertical disturbance of road within uncertain vehicle parameters in which the Fourier transform of the autocorrelation function is used to fit the road power spectrum density (PSD). In order to compensate for the delay and realize the real-time estimate of road conditions, an online fuzzy evaluation strategy for road condition is developed by integrating the fitted road PSD and the real-time suspension performance. After that, an adaptive fuzzy PID control strategy is developed based on the adaptive suspension control performance, which is supposed to realize the adaptive adjustment of control parameters for different road conditions. The simulation experimental results show that the online fuzzy evaluation strategy can effectively reflect the change in road condition, and the proposed adaptive fuzzy PID control strategy can work for adjusting the parameters adaptively, according to the changes in road conditions and therefore meet the control performance requirements under different road conditions.