Abstract
This work aimed to improve the vehicle body stability and the ride comfort of the tracked military vehicle crew. For this purpose, magnetorheological fluid dampers were used. This process has made the theoretical model of the tracked platform a semi-active suspension system. This modification allows for the application of different control laws to these systems. The usage of the continuous skyhook control law assumes the influence of three fictitious viscous dampers. Their force in this conceptual model is replicated by the magnetorheological dampers of the suspension in the real system. However, the continuous skyhook control law does not take into consideration the nonlinear stiffness characteristics. In this paper, the continuous skyhook control law has been appropriately modified. The modification takes into consideration the nonlinearity of the stiffness characteristics. Applying the modified continuous skyhook control law improves the stability of the vehicle body and the vehicle crew’s ride comfort. All these goals had to be introduced due to the modernization of the tracked military vehicle suspension by replacing the torsion bars with spiral spring packages with nonlinear characteristics.
Highlights
The semi-active systems in recent years have gained significant interest
The LPV model predictive control can be used to provide a suitable trade-off between comfort and handling performances [1]
Artificial neural networks are used to synthesize control laws in semi-active suspension systems [2]. Another type of artificial intelligence used in controlling such suspensions is fuzzy-logic control [3], as well as recurrent neural networks [4]
Summary
The semi-active systems in recent years have gained significant interest. The main reason for it is to improve a vehicle’s ride comfort [1]. The LPV model predictive control can be used to provide a suitable trade-off between comfort and handling performances [1]. Artificial neural networks are used to synthesize control laws in semi-active suspension systems [2]. Another type of artificial intelligence used in controlling such suspensions is fuzzy-logic control [3], as well as recurrent neural networks [4]. Many types of filters can be used in semi-active suspension systems. Various algorithms have been tested, first, in quarter-car models [11,12,13]. The quarter-car model of the 2S1 tracked platform was tested to perform research in this work
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