Modelling, failure modes prediction and optimization of gear shifting mechanism, Application to heavy vehicle transmission systems

Abstract: The transmission system has a key role to drive a vehicle transmitting power from engine to rotational motion at wheels. Gear shifting mechanism inside the gearbox is a crucial part of the transmission system. Particularly in case of heavy vehicles gear shifting needs to be more frequent and quick for the low energy consuming and high performing vehicles. In addition to this, highly growing change of technology from fuel consuming vehicles to electric vehicles puts a higher demand on the gear shifting mechanism. Development process of new design of the gear shifting mechanism must be fast to meet the future demands. In this regard two models of the gear shifting mechanism are developed. Sensitivity analysis and failure modes prediction are studied. The gear shifting process is optimized based upon the developed models by using genetic algorithm.   A generic synchronizer modelled with five degrees of freedom and comprising three rigid bodies is studied to understand the gear shifting process. To get insight into the complete gear shifting process, detailed kinematic description of the phases and sub-phases is given. Nature of bodies’ interaction is studied. A mathematical model is developed based on Constrained Lagrangian Formalism. The developed model is validated against test rig data. After sensitivity analysis, optimization is performed based upon the developed model. Synchronization time and speed difference at end of the main phase of synchronization process are chosen as objective functions. Parameters are cone angle, cone coefficient of friction, applied shift force, blocker angle, blocker coefficient of friction, cone radius, gear moment of inertia and ring moment of inertia. Several cases of the synchronization process are studied under different scenarios of master/slave and different operating conditions. Further analysis of results obtained from Pareto optimization clarifies the degree of influence of the input parameters.   To identify the failure modes, the gear shifting mechanism is modelled on GT-Suite software. System response characteristics are chosen to observe the failure modes. At failure modes occurrence limits of values of design parameters are identified. With these limits genetic algorithm based routine is applied to the optimization. The synchronization time is selected as an objective function to be minimized. At first step seven parameters are considered as varying parameters for optimization. At second step seventeen design parameters are optimized for six cases at master/slave settings with conditions of nominal, road grade and driveline excitation. Because of the minor differences between the optimization results average values of the parameters are taken as optimal values for all cases. It is shown that the obtained optimized values of design parameters are robust with respect to different driving conditions.