RESEARCHES REGARDING THE DEVELOPMENT OF A MATHEMATICAL MODEL TO OPTIMIZE THE OPERATION OF THE ANTI-LOCK BRAKING SYSTEM

This paper presents a simplified model of a passenger-car’s ABS (Anti-Lock Braking System). For simplicity purpose, a “quarter-car” planar model was considered: a wheel in rotation movement and a mass in translational movement (the vehicle mass supported by that wheel). In these conditions, a very simple dynamic model was obtained, having only two degrees of freedom (DOFs): the wheel rotation and the translation of the “quarter-car” mass. The mathematical model consists in the motion equations of the wheel and “quarter-car” mass and in the equations describing the comportment of the driver, controller, hydraulic module and brake. The model was transposed in a Matlab-Simulink model, offering the possibility to simulate many times how the ABS works if the constructive parameters, road conditions or driver inputs are changed

RESEARCHES REGARDING THE DEVELOPMENT OF A MATHEMATICAL MODEL TO OPTIMIZE THE OPERATION OF THE ANTI-LOCK BRAKING SYSTEM

This paper presents a simplified model of a passenger-car’s ABS (Anti-Lock Braking System). For simplicity purpose, a “quarter-car” planar model was considered: a wheel in rotation movement and a mass in translational movement (the vehicle mass supported by that wheel). In these conditions, a very simple dynamic model was obtained, having only two degrees of freedom (DOFs): the wheel rotation and the translation of the “quarter-car” mass. The mathematical model consists in the motion equations of the wheel and “quarter-car” mass and in the equations describing the comportment of the driver, controller, hydraulic module and brake. The model was transposed in a Matlab-Simulink model, offering the possibility to simulate many times how the ABS works if the constructive parameters, road conditions or driver inputs are changed

Universities as an External Knowledge Source for Industry: Investigating the Antecedents’ Impact on the Importance Perception of Their Collaboration in Open Innovation Using an Ordinal Regression-Neural Network Approach

Within the highly complex ecosystem of industry-university collaboration in open innovation, three specific antecedents typically characterize the patterns of their interaction, i.e., motivations, barriers, and channels of knowledge transfer. However, an investigation of the extent to which these antecedents of opening up innovation impact the perceived importance of universities as an external knowledge source to the industry is still missing in the literature. Based on a research framework developed from a review of the literature, a two-stage ordinal regression, and neural network approach was performed to investigate this impact. In the first stage, the hypotheses of the proposed research framework were tested based on an ordinal regression, and those antecedents that significantly impacted the importance perception were revealed. In the second stage, an artificial neural network analysis was carried out to capture the complex relationships among the significant antecedents and the important perception of universities as an external knowledge source to the industry. On the whole, the findings of our study expand the existing open innovation literature and contribute to a more articulate view of the collaboration between industry and university in this field by providing a first perspective on which of the three antecedents has a significant impact on this perception and how such an impact can be predicted