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The optimization of vehicle suspension kinematic/compliance characteristics is of significant importance in the chassis development. Practical suspension system contains many uncertainties which may result from poorly known or variable parameters or from uncertain inputs. However, in most suspension optimization processes these uncertainties are not accounted for. This study explores the use of Chebyshev polynomials to model complex nonlinear suspension systems with interval uncertainties. In the suspension model, several kinematic and compliance characteristics are considered as objectives to be optimized. Suspension bushing characteristics are considered as design variables as well as uncertain parameters. A high-order response surface model using the zeros of Chebyshev polynomials as sampling points is established to approximate the suspension kinematic/compliance model.

Practical vehicle contains many uncertainties which may result from poorly known or variable parameters or from uncertain inputs. These uncertainties can be presented by fuzzy parameters, random parameters or interval parameters. A new uncertain analysis method is applied to the case in which the vehicle system contains both random parameters and interval parameters. This new uncertain method is a systematic integration of the Polynomial Chaos (PC) theory which accounts for random uncertainty and Chebyshev inclusion function theory which accounts for interval uncertainty. A multi-body vehicle model with both random parameters and interval parameters is used as a numerical model and vehicle handling is investigated in details. The Monte Carlo method combined with the scanning method is used to demonstrate the effectiveness of the proposed method for vehicle handling.

Interval inverse problems can be defined as problems to estimate input through given output, where the input and output are interval numbers. Many problems in engineering can be formulated as inverse problems like vehicle suspension design. Interval metrics, instead of deterministic metrics, are used for the suspension design of a vehicle vibration model with five degrees of freedom. The vibration properties of a vehicle vibration model are described by reasonable intervals and the suspension interval parameters are to be solved. A new interval inverse analysis method, which is a combination of Chebyshev inclusion function and optimization algorithm such as multi-island genetic algorithm, is presented and used for the suspension design of a vehicle vibration model with six conflicting objective functions. The interval design of suspension using such an interval inverse analysis method is shown and validated, and some useful conclusions are reached.