Robust design of a passive linear quarter car suspension system using a multi-objective evolutionary algorithm and analytical robustness indexes

Loyer, B.; Jézéquel, L.

doi:10.1080/00423110802613394

Cited by 12 publications

(3 citation statements)

References 8 publications

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“…The algorithm ranks the fitness value of the population through non-dominant ranking, uses the crowding degree distance to ensure the population diversity, selects the parent population through elite strategy, and generates the child population through heredity and variation and so on until the set evolutionary algebra is reached. It finds the optimal solution using an iterative process by simulating natural selection and survival of the fittest, as well as other biological concepts [27].…”

Section: Optimization Design Methods and Optimization Resultsmentioning

confidence: 99%

Sensitivity Analysis and Optimization of the Hydraulic Interconnected Suspension Damping System of a Small Rescue Craft

Wang,

Du,

Xiong

et al. 2023

JMSE

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Component parameters directly affect the dynamic characteristics of suspension systems in small rescue craft. To study and improve the vibration reduction performance of a new suspension system, sensitivity analysis and genetic algorithm (GA) optimization were performed for a three-degree-of-freedom (3-DOF) vibration reduction suspension system. The system performance was analyzed using AMESim multi-condition simulations, and the sensitivity of the system to parameters that affect its dynamic characteristics was analyzed. Furthermore, the parameters were optimized using the GA. The simulation results indicated that the hydraulic cylinder inner diameter, the piston rod diameter, the accumulator volume, the accumulator pre-charge pressure, and the damper valve aperture size all influenced the working performance of a small salvage vessel. The optimization results showed that the stability of the ship was improved by 60% and that the main hull acceleration root mean square value decreased by 2.24% as a result of the optimization. The stability and riding comfort of the small salvage ship were improved, and there was an evident stability optimization effect. The comprehensive performance of the salvage ship was significantly improved.

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Section: Optimization Design Methods and Optimization Resultsmentioning

confidence: 99%

Sensitivity Analysis and Optimization of the Hydraulic Interconnected Suspension Damping System of a Small Rescue Craft

Wang,

Du,

Xiong

et al. 2023

JMSE

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“…Moreover, it is well recognized in the literature, that solutions obtained from deterministic optimization are more sensitive to uncertainties on the suspension parameters [7]. To overcome this limitation, multi-objective robust optimization has been successfully employed in the design of suspension systems [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Robust Optimization of Road Vehicle Suspension Considering the Variation of Tire Vertical Stiffness

Yang¹,

Ballo²,

Previati³

et al. 2019

J. Model. Optim.

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Tire vertical stiffness is influenced by many factors. The inflation pressure, tire dimension, and usage of run-flat tire are considered in this paper. Robust multi-objective optimization technique is used to optimize the suspension performance considering the variation of the tire vertical stiffness. Three objective functions, discomfort, road holding, and working space are used to evaluate the dynamic behavior of the suspension considering a two-degree-of-freedom quarter-car model excited by a random road profile. The Pareto-optimal solutions in terms of suspension spring stiffness and damping coefficient are obtained and compared with the one computed by means of a deterministic approach. Solutions obtained by means of the robust optimization method are proven to be less sensitive to the possible variations of the tire vertical stiffness without influencing significantly the expected performance.

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“…Henceforth, the research on MOEAs attracted more and more researchers. Up to now tens of MOEAs have been proposed [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Evolutionary Algorithm Based on the Fuzzy Similarity Measure

Dai

Wang

2010

KEM

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Evolutionary algorithm has gained a worldwide popularity among multi-objective optimization. This paper proposes a novel multi-objective evolutionary algorithm based on the fuzzy similarity measure. First, the best solution of every objective among the multi-objectives is obtained and they are regarded on as the referenced vector. Second, the fuzzy similarity measure between every individual and the referenced vector is solved and the fuzzy similarity measure is acted as fitness of the individual. Moreover, the pareto optimal sets are solved by means of adaptive genetic algorithm. The variety of population is kept by means of adaptive probability of crossover and mutation. At last, the algorithm is used to optimize the design parameters of cylinder helical compression spring. Simulation examples show the effectiveness of the approach proposed.

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Robust design of a passive linear quarter car suspension system using a multi-objective evolutionary algorithm and analytical robustness indexes

Cited by 12 publications

References 8 publications

Sensitivity Analysis and Optimization of the Hydraulic Interconnected Suspension Damping System of a Small Rescue Craft

Sensitivity Analysis and Optimization of the Hydraulic Interconnected Suspension Damping System of a Small Rescue Craft

Robust Optimization of Road Vehicle Suspension Considering the Variation of Tire Vertical Stiffness

Multi-Objective Evolutionary Algorithm Based on the Fuzzy Similarity Measure

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