Modelling, failure modes prediction and optimization of gear shifting mechanism, Application to heavy vehicle transmission systems
Doktorsavhandling, 2019

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.

failure modes prediction.

gear shifting

GT-Suite modelling

optimization

Synchronizer

constrained Lagrangian formalism

sensitivity analysis

lecture hall ED, building EDIT Hörsalsvägen 11, Gothenburg, Sweden
Opponent: Professor Kjell Andersson, Department of Machine Design Royal Institute of Technology Sweden

Författare

Muhammad Irfan

Chalmers, Mekanik och maritima vetenskaper, Dynamik

Modelling of Heavy Vehicle Transmission Synchronizer using Constrained Lagrangian Formalism

In Proc. of the International Conference on Engineering Vibration, Ljubljana, 7 - 10 September ; [editors Miha Boltežar, Janko Slavič, Marian Wiercigroch]. - EBook. - Ljubljana: Faculty for Mechanical Engineering, 2015,; (2015)p. 28-37

Paper i proceeding

Dynamics and Pareto Optimization of a Generic Synchronizer Mechanism

Rotating Machinery, Hybrid Test Methods, Vibro-Acoustics and Laser Vibrometry, Vol 8,; (2016)p. 417-425

Paper i proceeding

Performance improvement of a transmission synchronizer via sensitivity analysis and Pareto optimization

Cogent Engineering,; Vol. 5(2018)p. 1-46

Artikel i vetenskaplig tidskrift

Failure modes and optimal performance of a generic synchronizer

The 5th Joint International Conference on Multibody System Dynamics,; (2018)p. 1-22

Paper i proceeding

M. Irfan, V. Berbyuk and H. Johansson, "Minimizing synchronization time of a gear shifting mechanism by optimizing its structural design parameters,", Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, (submitted for publication).)

Optimizing the gear shifting mechanism of heavy vehicles

Automotive industry face a big challenge to reduce carbon dioxide emissions and to sell competitive trucks that comply with current and future emissions standards. The engine design, drivetrain and other transmission systems components must be further developed. The gear shifting mechanism which is a part of drivetrain needs also to be updated.

The transmission system including gear shifting mechanism has a key role to drive a vehicle which transmits power from engine to rotational motion at wheels. Particularly in case of heavy vehicles gear shifting needs to be more frequent and quick for the low energy consuming and high performing vehicles. The gear shifting process is optimized based upon the developed models and genetic algorithm with particular settings (master/slave) and conditions (nominal, road grade and excitation).

To support development of the gear shifting mechanism, detailed description of kinetics and kinematics are needed. To this end, a mechanical system with 5 degrees of freedom modelling a generic synchronizer consisting of engaging sleeve, synchronizer ring and gearwheel is considered. Due to design of the different components and their interactions the synchronizing process is described in terms of different phases; presynchronization, main synchronization, blocker transition and engagement. The four main phases are further divided into sub-phases.

To model the whole process in a unified manner, Constrained Lagrangian Formalism (CLF) turns out to be a suitable method in which the interactions between components (sleeve, synchronizer ring and gearwheel) are described by unilateral or/and bilateral constraints imposed on generalized coordinates of the system during different phases. The generic synchronizer computational model is adapted to available experimental setup and validated using obtained measurement data.

For heavy vehicles, particularly under certain circumstances, avoiding failure modes of the gear shifting mechanism is also a challenge. A model of the gear shifting mechanism is developed in GT-Suite software. Failure modes are identified via sensitivity analysis by using four system response characteristics.

The gear shifting process is optimized based upon the GT-Suite model with particular settings and conditions. Three conditions of nominal, road grade and vibrational motion of the master are studied in six cases by considering the sleeve and the gear as a master (constant rotational speed) alternatively. The optimization is performed for each case to find out minimum gear shifting time based on variations of the structural design parameters. Seventeen structural design parameters of the sleeve, the ring and the gear are considered to be optimized. The optimization results are plotted in correlations of synchronization time and structural design parameters. Minimum synchronization time is found almost same in all cases. It is concluded from closeness of the optimization results, average of the parameter values can be considered as optimized values for all cases. At the end, robustness of the optimized structural design parameters are analyzed with respect to the road grade, amplitude and frequency of excitation.

Ämneskategorier

Maskinteknik

ISBN

978-91-7597-846-8

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4527

Utgivare

Chalmers tekniska högskola

lecture hall ED, building EDIT Hörsalsvägen 11, Gothenburg, Sweden

Opponent: Professor Kjell Andersson, Department of Machine Design Royal Institute of Technology Sweden

Mer information

Senast uppdaterat

2019-02-22