Vehicle Suspension Components Research Articles

Artificial neural network infused quasi oppositional learning partial reinforcement algorithm for structural design optimization of vehicle suspension components

Abstract This paper introduces and investigates an enhanced Partial Reinforcement Optimization Algorithm (E-PROA), a novel evolutionary algorithm inspired by partial reinforcement theory to efficiently solve complex engineering optimization problems. The proposed algorithm combines the Partial Reinforcement Optimization Algorithm (PROA) with a quasi-oppositional learning approach to improve the performance of the pure PROA. The E-PROA was applied to five distinct engineering design components: speed reducer design, step-cone pulley weight optimization, economic optimization of cantilever beams, coupling with bolted rim optimization, and vehicle suspension arm optimization problems. An artificial neural network as a metamodeling approach is used to obtain equations for shape optimization. Comparative analyses with other benchmark algorithms, such as the ship rescue optimization algorithm, mountain gazelle optimizer, and cheetah optimization algorithm, demonstrated the superior performance of E-PROA in terms of convergence rate, solution quality, and computational efficiency. The results indicate that E-PROA holds excellent promise as a technique for addressing complex engineering optimization problems.

Validation of the CAE model set for a passenger car suspension according to loading criteria

BACKGROUND: Development of numerical methods and technology of computer-aided engineering, used in vehicle design, has reached its high level. Results of virtual experiments cannot be totally relied upon without verifying results obtained with the developed mathematical model. That is why the present paper concentrates on the relevant issue of validation of the CAE models, applicable for vehicle suspension components dynamic load analysis.
 AIMS: Goal of the research is adequacy confirmation of developed requirements to preparation of simulation models, applicable for dynamic load and fatigue analysis, by means of numerical simulation with validation analysis.
 METHODS: CAE models validation is carried out with a comparative method of results obtained from either laboratory or proving ground testing and simulation of a physical object. Strain gauging results are taken for the comparison. The Models are prepaired with using MBS and FEM technologies.
 RESULTS: Validation showed of validation show a good convergence of modelling and experiment results, that confirm adequacy of developed requirements to creation of CAE models, applicable for load and fatigue analysis of vehicle suspension components. The selected convergence evaluation criteria have not been used in similar papers yet and have shown an effective outcome of quantitative and qualitative comparison of loading condition of suspension parts in a variety of boundary conditions of mechanical system simulation.
 CONCLUSIONS: Validated CAE models of a passenger car suspension, developed accelerated loading cycle, the model design and dynamic loading simulation approach can be used for chassis parts load analysis and fatigue prediction during early stages of development and as support of testing.

Investigation of the Hydrolytic Stability of Polyurethane Applied to Vehicle Suspension Components

Process parameters such as temperature and humidity, as well as formulation are the key factors in the manufacture of a polymeric component through a polyurethane prepolymer. These define the reaction kinetics, bonding and the resulting chemical interactions which determine the final characteristics of the material. One of the expected skills of polyurethane, when applied to components used in contact with water, is hydrolysis resistance. Consequently this research focused on exposure of a polymerized TDI (toluene diisocyanate) polyether polyurethane to different proportions of the curing agent, MOCA (4,4'-methylene-bis), in an environment susceptible to reactions with water at 70 °C. In this case, this material is applied in the manufacture of coil spring solid axle with trailing arms and Panhard rod suspension bushings. Mechanical tests and DSC (differential scanning calorimetry), TGA (thermogravimetry) and FT-IR (Fourier transform infrared) evaluations of the samples and prepolymer are conducted for the characterization of the different formulations, showing the negative relationship of the curing agent proportion parameters with the hydrolysis resistance. Here depolymerization of urethane and ether groups, as well as lower retention of yield stress are verified. These findings can subsidize developing predictive models for performance and lifetime of polyurethanes.

Application and Comparison of Uncertainty Quantification Methods for Railway Vehicle Dynamics with Random Mechanical Parameters

This paper aims to investigate uncertainties in railway vehicle suspension components and the implement of uncertainty quantification methods in railway vehicle dynamics. The sampling-based method represented by Latin Hypercube Sampling (LHS) and generalized polynomial chaos approaches including the stochastic Galerkin and Collocation methods (SGM and SCM) are employed to analyze the propagation of uncertainties from the parameters input in a vehicle-track mathematical model to the results of running dynamics. In order to illustrate the performance qualities of SGM, SCM and LHS, a stochastic wheel model with uncertainties of the stiffness and damping is firstly formulated to study the vertical displacement of wheel. Numerical results show that SCM, which can be easily implemented by means of the existing deterministic model, has explicit advantages over SGM and LHS in terms of the efficiency and accuracy. Furthermore, a simplified stochastic bogie model with three random suspension parameters is also established by means of SCM and LHS to analyze the critical speed, which is affected obviously by the parametric uncertainties. Finally, a stochastic vertical vehicle-track coupled model with parametric uncertainties is built comprehensively on the basis of SCM, by which the impact behavior of wheel-rail interaction under a rail defect is investigated and the dynamic response of vehicles under the track irregularity is explored in terms of the Sperling index. It concludes that the uncertainties of parameters have a significant influence on P2 force and Sperling index from the view of the running quality.

Meta-model Effects on Approximate Multi-objective Design Optimization of Vehicle Suspension Components

Meta-model Effects on Approximate Multi-objective Design Optimization of Vehicle Suspension Components

Effect of Suspension Parameter Uncertainty on the Dynamic Behaviour of Railway Vehicles

The paper describes a study carried out by Dipartimento di Meccanica Politecnico di Milano, aimed at investigating how uncertainty in railway vehicle suspension components can be treated in the framework of vehicle design and performance assessment in respect to vehicle dynamics. In railway vehicle suspensions, sources of parameter uncertainty may arise from inaccuracy in the modelling of a vehicle component or from a scatter in the behaviour of nominally identical components, on account of the variability implied by the component manufacturing process. The approach proposed in this paper, completely new to the railway field, is to use statistical methods having different complexity (and entailing a proportional computational effort), to analyse the propagation of uncertainty from the parameters input in the vehicle mathematical model to the results of running dynamics, in terms of the assessment quantities used for verification and evaluation of train performances. The problem is treated by numerical means, being the dependency of simulation outputs from the input parameters typically non-linear, and not defined in an analytical form.

Modelling of suspension components in a rail vehicle dynamics context

Suspension components play key roles in the running behaviour of rail vehicles, and therefore, mathematical models of suspension components are essential ingredients of railway vehicle multi-body models. The aims of this paper are to review existing models for railway vehicle suspension components and their use for railway vehicle dynamics multi-body simulations, to describe how model parameters can be defined and to discuss the required level of detail of component models in view of the accuracy expected from the overall simulation model. This paper also addresses track models in use for railway vehicle dynamics simulations, recognising their relevance as an indispensable component of the system simulation model. Finally, this paper reviews methods presently in use for the checking and validation of the simulation model.

Experimental durability assessment and life prediction of vehicle suspension components: A case study of steering knuckles

The recent emphasis on more reliable life predictions for fatigue-critical parts in ground vehicles would result in a reduction in costly and time-consuming traditional component testing practices. This paper aims at implementing experimental and predictive durability approaches to vehicle suspension components. Forged steel and cast aluminium steering knuckles were chosen as typical components. The fatigue behaviours of components were investigated via constant-amplitude load-controlled fatigue tests. Finite element models of the knuckles were analysed using linear and non-linear methods. Nominal stress, local stress, and local strain life prediction approaches were employed and compared with experimental results to evaluate the accuracy and validity of these approaches. The strengths and shortcomings of the applied models and the alternative analysis techniques are discussed. It is shown that among the contemporary life prediction procedures used in the automotive industry, the local strain approach in conjunction with the plasticity-corrected simple elastic analysis procedure yields reasonable life predictions that are typical of more complex and much more time-consuming non-linear analysis. A number of complexities such as material property variability, variable-amplitude and multiaxial loadings, manufacturing parameters, and environmental effects on durability assessment are also discussed.

Simulation of the perceptible feed-forward and feed-back properties of hydraulic power-steering systems on the vehicle’s handling behavior using simple physical models

Today, often complex component-oriented simulation models are used to study the influences of hydraulic power-steering systems on the vehicle’s handling properties. In these simulation models, we have a detailed description of the vehicle suspension components (links, joints, springs, etc.) extended by complex component simulation models of tires, bushings, and of course also by power-steering models. These power-steering models contain a detailed physical description of the complex mechanical and hydraulics properties of the system, like friction in seals, aspects of hydraulic power supply, etc. On the other hand, there is a need for simple model approaches used for basic assessments and system development. These simple models should represent all the essential properties of the vehicle’s handling behavior, without the need for the large-scale parameter setup and compute-time requirements of the more complex models. For many applications in handling, we use the class of single-track two-wheel bicycle-type vehicle models. With some nonlinear extensions, these models can represent the complete operating conditions of the vehicle. The parameterization of these models can be achieved online while driving or offline by analysis and identification, on the basis of some standard test maneuvers. In these models, all properties of steering, suspension and tire are condensed to the cornering stiffness or side-force map, a separation e.g. of the steering system influence does not take place. This article shows how modeling of a hydraulic power-steering system can be done to represent the essential feed-forward and feed-back properties, and how this model can be integrated to the complete vehicle’s description. This new model approach gives a better insight into the four-pole properties of steering systems and introduces a separation between the steering system and the suspension even in simple model classes.

A Review of Modelling Methods for Railway Vehicle Suspension Components

SUMMARY The dynamic behaviour of railway vehicles has been the subject of study for over a century but the advances in computing technology in the last few years have led to a very rapid development in the use of numerical techniques for solving railway vehicle dynamics problems. As these techniques have developed, and have been applied to ever more complex problems, the modelling of the vehicle components has increased in importance. Mathematical models of railway vehicles may now include components such as swing links, air-springs, trailing arm suspensions, load sensitive friction dampers, rubber bushes with hysteresis etc, all of which require sophisticated modelling techniques to produce accurate results. This paper looks at the developments that have taken place in this area, the background to the need for sophisticated models, the improvements in accuracy that can result and some of the difficulties in applying these techniques to the modelling of real situations.