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Inicio  /  Agriculture  /  Vol: 14 Par: 3 (2024)  /  Artículo
ARTÍCULO
TITULO

Model Development for Off-Road Traction Control: A Linear Parameter-Varying Approach

Adam Szabo    
Daniel Karoly Doba    
Szilard Aradi and Peter Kiss    

Resumen

The number of highly automated machines in the agricultural sector has increased rapidly in recent years. To reduce their fuel consumption, and thus their emission and operational cost, the performance of such machines must be optimized. The running gear?terrain interaction heavily affects the behavior of the vehicle; therefore, off-road traction control algorithms must effectively handle this nonlinear phenomenon. This paper proposes a linear parameter-varying model that retains the generality of semiempirical models while supporting the development of real-time state observers and control algorithms. First, the model is derived from the Bekker?Wong model for the theoretical case of a single wheel; then, it is generalized to describe the behavior of vehicles with an arbitrary number of wheels. The proposed model is validated using an open-source multiphysics simulation engine and experimental measurements. According to the validated results, it performs satisfactorily overall in terms of model complexity, calculation cost, and accuracy, confirming its applicability.

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