The aim of this paper is to present the dynamic behaviour modelling performed for a forklift truck and the validation of this model. The intention is to develop a permanent tool allowing both common and critical driving situations (especially that of lateral tip-over) to be simulated for this type of vehicle. The medium-term aim is to use this model as a tool to facilitate designing, training and preparing safety standards with a view to reducing the number of accidents related to this machine, which, on average, still cause nearly 10 deaths each year. This paper describes the forklift truck mechanical model and the tyre model. A Pacejka's lateral tyre model was used and integrated into the forklift truck model. The interacting forces and moments between the wheels and the ground are, therefore, computed at all times. Test bench-measured data, characteristic of the dynamic behaviour of several tyres, were used to identify the parameters of the Pacejka model. We studied the limits of this model adapted in this case to tyres with characteristics different from those of the car sector. Track testing was performed using a safe-test forklift truck. The purpose of these tests was to measure trajectory characteristics (velocity, position, acceleration and slip angle) and to compare them with model-based predictions, allowing validation of the robustness and accuracy of this model. Situations involving partial (up to 15 • ) tip-over were included. The quantities measured during testing were compared with the calculation results obtained for identical driving configurations. There was a close calculation/measurement correlation when performing a wide 'J-turn' (with and without tip-over) when following circular or slalom trajectories. The calculation/measurement correlation was less close when the forklift truck performed a sharp 'J-turn', for example. Model limits can be derived from the observations, data processing and calculations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.