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Modelling of Power Losses of Transmission Synchronizers in Neutral Position
Technical Paper
2018-01-1228
ISSN: 0148-7191, e-ISSN: 2688-3627
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Abstract
Developing an energy-efficient powertrain system is a solution for environment-friendly vehicles. Furthermore, it also enhances the performance of vehicles. In powertrain system, transmission plays an important role in terms of vehicle dynamic performance and energy consumption. Therefore, a lot of researches have been conducted on modelling power losses inside the transmission. Basically, the power losses in transmission consist of bearing losses, drag torque losses on gear blank that is immersed in the oil and gear mesh losses due to the sliding frictional force on gear flank. According to some experiments in the latest literatures, power losses of synchronizers cannot be neglected, when its shift sleeve is in neutral position. Principally, power losses of synchronizers in neutral position mainly come from load independent drag torque. The drag torque is generated by the shear torque of lubrication in the gap (or gaps) between synchronizer ring and synchronizer cone, which are rotating at different speed. In this paper, a drag torque model of synchronizer units in neutral position is built up based on mechanism of tribology lubrication. Several factors are considered in the model, for example, synchronizer geometry (cone angle, face width, etc.) and lubrication factors (viscosity, oil volume, etc.). Furthermore, the power losses of synchronizer under different oil injection methods are considered and separately discussed in the paper. In the end, validations are conducted. The amplitude and tendency of simulation results agree well with test data. In the future, the model of synchronizer power losses in neutral position will be further modified and it is planned to apply it into a study case for a manual transmission.
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Shen, Y., Liu, Z., and Rinderknecht, S., "Modelling of Power Losses of Transmission Synchronizers in Neutral Position," SAE Technical Paper 2018-01-1228, 2018, https://doi.org/10.4271/2018-01-1228.Data Sets - Support Documents
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