MBS-modelling of a heavy truck : Modelling and model validation
As a result of the accelerating demands for faster development within the heavy vehicle industry, computer aided simulations have become a more important tool in the development process. Simulations can offer faster evaluation of loads acting on the vehicle and more cost effective fatigue life predictions than physical testing, since physical prototypes are not needed for load measurements or fatigue tests. However, accurate fatigue life predictions without physical verification are today a difficult task with many uncertainties, yet simulations are still an important part of modern product development.The objective of this work is to investigate the accuracy of a virtual model of a physical truck. The thesis focuses only on load simulation accuracy, leaving the material uncertainties aside. The vehicle model is built using Adams/Car with two different complexities of the frame model. A part of the work is to investigate how the frame model complexity affects the accuracy of the results.The virtual truck is simulated in a virtual test rig that excites the model with displacement on the wheel hubs to represent the forces induced when the truck is driven on the test track. The process to make a drive signal to the test rig is iterative. Simulations are also performed with the virtual model equipped with tires and driven on a virtual 3D road.Model performance is evaluated using TDDI (Time Domain Discrepancy Index) and pseudo-damage. TDDI evaluates the results in the time domain and the pseudo-damage considers the potential fatigue damage in the time series. A value of the TDDI below 0.3 and between 0.5 and 2 for the pseudo-damage is found good. The accuracy is approximately the same as can be repeated by different test engineers driving the same test schedule with the same vehicle.When iterating using the cab and the front and rear end of the frame as response feedback, the results for the model with the simple frame model show good values of TDDI and pseudo damage for the front end of the frame and the cab. Though the axles and the mid of the frame show poor results. The rear end of the frame does not reach the model performance targets, getting a too low value of the pseudo-damage while the TDDI value is good. The vehicle model with the complex frame shows similar results, when using the same response feedback, although the frame model is not optimized.The full vehicle model driving on 3d-road does not, at present, deliver accurate results. However, the relative damping for the beams, representing the leaf springs, has turned out to highly affect the results. The leaf spring model thus need to be optimized. The complex frame model is not showing results good enough to justify the extra modelling time. The accuracy of the full-vehicle model can be considerably improved by optimizing the model/-s of the wheel suspension and the complex frame model.
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