Genetic algorithm-based optimum vehicle suspension design using minimum dynamic pavement load as a design criterion

Sun, Lu; Cai, Ximing; Yang, Jun

doi:10.1016/j.jsv.2006.08.040

Cited by 90 publications

(48 citation statements)

References 24 publications

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“…This means a good handling maneuver and enhanced vehicle lateral stability and safety. In other side, these improvements are highly promising from the point of view of road damage, so we can save the costs associated with repairing transportation infrastructure networks [22]. At similar Rms values of suspension working space, the controllable MR-damper is reduced the vehicle body acceleration by 6% over the conventional passive suspension.…”

Section: Figures 4(c)-(e)mentioning

confidence: 99%

Automotive Ride Comfort Control Using MR Fluid Damper

El-Kafafy¹,

El-Demerdash²,

Rabeih³

2012

ENG

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In this paper, the performance of automotive ride comfort using Bouc-Wen type magneto-rheological (MR) fluid damper is studied using a two degree of freedom quarter car model. The sliding mode control is used to force the MR damper to follow the dynamics of ideal sky-hock model. The model is tested on two excitations, the first is a road hump with severe peak amplitude and the second is a statistical random road. The results are generated and presented in time and frequency domains using Matlab/Simulink software. Comparison with the fully active, ideal semi-active and conventional passive suspension systems are given as a root mean square values. Simulation results, for the designed controller, show that with the controllable MR damper has a significant improvement for the vehicle road holding then its lateral stability as well as road damage in comparison with passive, fully active and ideal semi-active suspension systems.

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Section: Figures 4(c)-(e)mentioning

confidence: 99%

Automotive Ride Comfort Control Using MR Fluid Damper

El-Kafafy¹,

El-Demerdash²,

Rabeih³

2012

ENG

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“…To demonstrate the effectiveness of the proposed method, performance comparison of suspension obtained by PSO and GA is done. The quarter vehicle optimum suspension parameters are listed in Table 2, where the optimum parameters are obtained by PSO for the case of Ni=2000 with Np=70, and the parameters obtained using GA for the same passive suspension system of heavy vehicle are referred to the literature [11]. Fig.3 shows the time history of the vehicle suspension systems behavior for the bump road profile given in Eq.…”

Section: Resultsmentioning

confidence: 99%

“…From a cost-effectiveness of tyre-terrain systems perspective, on the other hand, the dynamic tyre load applied on the pavement is also important performance requirements especially for the heavy vehicles [7][8][9][10].It has been recognized from several years ago that pavement damages are related to the dynamic tyre load through a fourth power law [7]. That is to say, a 10% increase in the dynamic tyre load will cause an approximately 50% increase in pavement damage [11]. Considering the massive maintenance cost of road pavement, an approach for road friendliness optimization of heavy vehicle suspension using dynamic tyre load as a design criterion has been developed.…”

Section: Introductionequation Chapter 1 Sectionmentioning

confidence: 99%

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Road friendliness optimization of heavy vehicle suspension based on particle swarm algorithm

Wang¹,

Lv²,

Li³

2015

Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering

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Abstract. In this paper, an optimization design method based on the Particle Swarm Optimization (PSO) technique is proposed for the enhancement of the passive suspension system performance of heavy vehicles. The optimization problem based on a quarter-vehicle model aims to minimize the dynamic tyre load subject to constraints on the natural frequency of the unsprung mass. PSO is applied to solve the optimization problem for obtaining optimum parameters, such as the suspension damping coefficient, spring and tyre stiffness. In order to assess the obtained design parameters, the suspension performance is estimated in time and frequency domains for different road excitations. The results show that the proposed method can obtain the optimum designed parameters quickly compared with the previous designed parameters using the genetic algorithm for the same passive suspension system, which will provide important parameters for the subsequent revised design. This paper provides a feasible way for the optimization design of a new type of suspension system.

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“…Genetic algorithm (GA) is chosen as the optimizing method of suspension structure parameters and control ones of PID controller for the active suspension [2,[9][10][11]. During optimization procedure, GA iteratively manipulates populations of these chromosomes using reproduction, crossover and mutation operations, and evaluates suitability of each solution using a fitness function.…”

Section: Optimization Based On Gamentioning

confidence: 99%

Optimal Design of Structure and Control Parameters of Active Suspension Based on PID Control

Chen

Xiao

2011

Communications in Computer and Information Science

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Abstract. The objective of this research is to propose an optimal design of structure and control parameters for the active suspension based on proportionalintegral-derivative (PID) control. The novelty lies in optimized parameters including suspension structure ones and control ones of PID controller. Taking a quarter-vehicle model as an example, structure and control parameters for the active suspension are synchronously optimized based on genetic algorithm (GA) with the suspension quadratic performance index taken as the fitness function. Optimization result shows that the comprehensive performance of the optimized active suspension proposed is effective and feasible.

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Genetic algorithm-based optimum vehicle suspension design using minimum dynamic pavement load as a design criterion

Cited by 90 publications

References 24 publications

Automotive Ride Comfort Control Using MR Fluid Damper

Automotive Ride Comfort Control Using MR Fluid Damper

Road friendliness optimization of heavy vehicle suspension based on particle swarm algorithm

Optimal Design of Structure and Control Parameters of Active Suspension Based on PID Control

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