Mariusz Pyrz

Motorcycle motion is largely influenced by the road geometry, which alters the allowable accelerations in longitudinal and lateral directions and influences the vertical wheel loads. Recently, a method for three-dimensional road reconstruction and its incorporation into transient and quasi-steady-state (QSS) minimum lap time simulations (MLTSs) has been proposed. The main purpose of this work is to demonstrate how significantly different results from a minimum lap time optimal control problem can be obtained when using inappropriate elevation data sources in the track reconstruction problem, and how the road model reconstructed using poor input data can lead to misleading conclusions when analyzing real vehicle and driver performances. Two road models derived from high- and low-resolution digital elevation models (DEMs) are compared and their impact on the optimal maneuver of a racing motorcycle is examined. The essentials of track identification are presented, as well as vehicle positioning on the 3D road and the generalized QSS motorcycle model. Obtained 3D and 2D road models are analyzed in detail, on a case example of the Road Atlanta racetrack, and used in minimum lap time simulations, which are validated by the experimental data recorded on the Supersport motorcycle. The comparative analysis showed that great care should be taken when selecting the elevation dataset in the track reconstruction process, and that the 1 m resolution local DEMs seem to be sufficient to obtain MLTS results close to the measured ones. The example of using the 3D free-trajectory QSS minimum lap time problem to localize the track segments where real driver actions can be improved is also presented. The differences between simulation results on different road models of the same racetrack can be large and influence the interpretation of optimal maneuver.

In this work, the minimum-lap-time problem is investigated using a quasi-steady-state model. The prior research approach has been modified by introducing experimentally based controls’ constraints to consider some effects of vehicle inertia and human physical limitations. The differences between the theoretical and recorded experimentally g-g diagrams are analysed, and a semi-empirical g-g diagram is proposed as an approximation for the usage of most motorcycle riders. The effect of the braking technique (optimum and using front brake only) is discussed on a variable radius ‘U’ trajectory example. A new system of OCP state equations is proposed, and optimal trajectories are computed for several test scenarios for open and closed-loop tracks. The simulation result for the closed-loop track is compared with the experimental data from a GPS-based data acquisition system. The standard and proposed approach are compared, and conclusions are drawn.

The paper presents the crashworthiness optimization of a thin-walled frame applied as energy-absorbing element in a car structure. Crushing parameters of S-frame are modeled using the macro-element methodology. This method is implemented in the Visual Crash Studio software that enables very fast simulation of structural behavior during the impact. The objective is to determine the optimal dimensions of the frame cross-section to achieve the maximal energy absorption. Moreover, the selection of the best angle between the frame segments is investigated. In the formulation of the optimization problem, constraints related to the progressive collapse of deformation zones, required by the macro-element modeling, have been introduced. An Evolutionary Algorithm was applied to search the best solution. A real-life example of thin-walled S-frame is investigated in numerical examples. An attempt to find the solution by solving a sequence of simpler problems with reduced number of design variables is investigated. This approach is compared to the best result obtained for the problem including all design variables at the same time. This study illustrates the potential of the optimization in early-design stages of the vehicle development process and prepares perspectives for the optimization of complex energy-absorbing systems.