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Optimum Response of a Nonlinear Passive Vehicle Suspension System under Random Road Excitations

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<div>The objective of the present article is to design a nonlinear passive suspension system for an automobile subjected to random road excitation which generates a performance as close to a fully active suspension system as possible. Linear Quadratic Regulator (LQR) control is used to synthesize an active suspension system. The control forces corresponding to the nonlinear passive suspension and the active suspension are equated, and the parameters are optimized as the performance error between the two systems is reduced. The nonlinear equations of motion are reduced to equivalent linear equations, where the system states are a function of the vehicle response statistics, by using the equivalent linearization method. The performance of the optimized nonlinear model and the linear model are compared with the performance of the LQR control active suspension system. The nonlinear model performs better than the linear system with chosen parameters. The optimized system achieves almost an equal response to the active suspension system for ride comfort and road holding over the specified velocity range. The optimum response of a passive suspension system with nonlinear suspension elements is achieved using a novel optimization method. This method provides design flexibility, and it has great engineering importance for application in the design of various vibration control devices.</div>
Title: Optimum Response of a Nonlinear Passive Vehicle Suspension System under Random Road Excitations
Description:
<div>The objective of the present article is to design a nonlinear passive suspension system for an automobile subjected to random road excitation which generates a performance as close to a fully active suspension system as possible.
Linear Quadratic Regulator (LQR) control is used to synthesize an active suspension system.
The control forces corresponding to the nonlinear passive suspension and the active suspension are equated, and the parameters are optimized as the performance error between the two systems is reduced.
The nonlinear equations of motion are reduced to equivalent linear equations, where the system states are a function of the vehicle response statistics, by using the equivalent linearization method.
The performance of the optimized nonlinear model and the linear model are compared with the performance of the LQR control active suspension system.
The nonlinear model performs better than the linear system with chosen parameters.
The optimized system achieves almost an equal response to the active suspension system for ride comfort and road holding over the specified velocity range.
The optimum response of a passive suspension system with nonlinear suspension elements is achieved using a novel optimization method.
This method provides design flexibility, and it has great engineering importance for application in the design of various vibration control devices.
</div>.

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