Design optimization of multi-link suspension system for total vehicle handling and stability

Fujita, Kikuo; Hirokawa, Noriyasu; Akagi, Shinsuke; Hirata, Takanori

doi:10.2514/6.1998-4787

Cited by 11 publications

(3 citation statements)

References 5 publications

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“…Otherwise, if f is the performance maximum value criterion of g (Equation (2)), then a substitute differentiable criterion has to be found to allow the robustness of the criterion to be investigated by means of an analytical development. A known Lp spaces theory result is (4) where p denotes a real (or a natural) integer strictly greater than 1. Therefore, for large values of p, the criterionG…”

Section: Differentiability Of the Performance Criteriamentioning

confidence: 99%

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

Loyer

Jézéquel

2009

Vehicle System Dynamics

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This paper deals with the robust design of a passive vehicle suspension system. A robust design methodology based on a multi-objective evolutionary algorithm (MOEA) is used to handle the tradeoff between the considered conflicting performance requirements under uncertainty and feasibility constraints. A constrained multi-objective optimisation problem is formulated and the notion of Paretooptimality is used to increase the quality of the candidate design solutions obtained at each generation by the MOEA. To save computation time, a simplified physical model (quarter car) is considered and the optimisation is performed in the frequency domain, using relevant transmissibilities of the system. The robustness is directly investigated by means of analytical robustness indexes. Time-consuming a posteriori methods, like designs of experiments or Monte Carlo analysis, are therefore avoided. A set of non-dominated solutions is obtained. Thus the designer not only selects a special design, in accordance with the wanted vehicle configuration, but also includes the robustness of each performance requirement in his final decision.

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Section: Differentiability Of the Performance Criteriamentioning

confidence: 99%

“…These objective functions are positive quantities to be minimised. As proposed in [4], constraints are handled by means of exponentially progressive penalty factors. The MOEA stops when a predefined maximum number of generations is reached.…”

Section: Formulation Of a Constrained Multi-objective Problemmentioning

confidence: 99%

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

Loyer

Jézéquel

2009

Vehicle System Dynamics

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“…7 One major aim of this article is to investigate the effect of the anti-roll bar upon vehicle dynamics. Fujita et al 8 discussed the design of vehicles using multi-link suspension system with the aim of totally optimizing vehicle's handling and stability. The variation of toe angle and camber angle, roll center position, roll angle of the body under the steady-state circular turning and vertical vibration are selected as objective functions.…”

Section: Introductionmentioning

confidence: 99%

Optimization of semi-trailing arm suspension for improving handling and stability of passenger car

Kazemi

Shirazi

Ghanbarzadeh

2012

Proceedings of the Institution of Mechanical Engineers, Part K:

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Semi-trailing arm is an extended form of two suspension systems trailing arm and swing axle that compromises advantages and disadvantages of those systems. In this article, using Bees algorithm optimization method, the characteristic parameters of a semi-trailing arm suspension system to optimize the handling and stability performances of a passenger car are determined. Two types of objective functions, namely off-line and on-line, are defined. In off-line objective function, variation of camber, toe angle, and wheel track due to roll are considered. In the on-line objective function, handling and stability performance of a moving vehicle in a standard J-turn maneuver are considered. A nine degreeof-freedom non-linear vehicle model consists of semi-trailing arm and MacPherson suspensions in rear and front axle, respectively, is considered. The optimized suspension systems obtained from both off-line and on-line objective functions are utilized in making two accurate vehicle models in ADAMS-Car for experimental field test. A comparison between the behaviors of the two vehicles shows that despite the simplicity of optimization with off-line objective functions relative to on-line1, it returns the satisfactory results and improves both the handling and stability performances.

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Multi-Objective Optimization in the Conceptual Phase of Vehicle Development

Šagi

Lulić

2012

Concurrent Engineering Approaches for Sustainable Product Development in a Multi-Disciplinary Environment

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Design optimization of multi-link suspension system for total vehicle handling and stability

Abstract: ABSTRACT

Cited by 11 publications

References 5 publications

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

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

Optimization of semi-trailing arm suspension for improving handling and stability of passenger car

Multi-Objective Optimization in the Conceptual Phase of Vehicle Development

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