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There are several commercial off-the-shelf software available to study transmission and driveline dynamics. Many of these software require a faithful representation of the transmission topology in order to carry out the analyses. These modeling techniques utilize several redundant degrees of freedom which may not be necessary for studying low frequency (< ~30 Hz) dynamics and may be computationally inefficient. The dual-clutch model has been proposed as a generic 2-DOF model that overcomes some of these drawbacks. In this paper, the dual-clutch model is initially derived from first principles, starting with the equations of motion for a planetary automatic transmission. The model coefficients - the inertia matrix and the matrix of clutch coefficients - are then derived using a more intuitive approach based on energy considerations.

In this paper, loads acting on driveline components during an entire proving ground (PG) durability schedule are used to demonstrate the methodology of optimizing driveline performance reliability using both physical and computational methods. It is well known that there is an effect of driver variability on the driveline component loads. Yet, this effect has not been quantified in the past for lack of experimental data from multiple drivers and reliable data analysis methods. This paper presents the data reduction techniques that are used to identify the extreme driver performance and to extrapolate the short-term measurement to long-term data for driveline performance reliability. The driveline loading variability is made evident in the rotating moment histogram domain. This paper also introduces the concept for a simulation model to predict the driveline component loads based on a complete proving grounds schedule. A model-to-test correlation is also performed in this paper.

The performance of a large-volume production torque converter is slightly different from those of development prototype due to the core leakage flow. The sealing gap between the stator crown and pump or turbine core of the production converter is usually larger than that of prototypes because of fabrication method and tolerances. In this work, the core leakage flow of torque converter was investigated using CFD. The core region was modeled and coupled together with other three major components of a converter. Studies show that for a particular converter the core leakage flow could result in a 3.6% stall torque ratio reduction and a 2% peak efficiency decrease. The effects of sealing gap dimensions were also studied. Computational investigations in this work indicated that the variation of input K factor with input torque level observed in dyno tests is due to the cavitation in the torque converter.

To improve vehicle launch feeling, the powertrain torque output needs to be largely increased. Compared with modifications to engine, transmission, and axle, one of the most inexpensive ways of achieving this goal is to modify the torque converter to get a higher stall torque ratio. In other applications, in order to lower engine speed for better fuel economy, and to match with a higher output engine, a converter with higher torque capacity (lower K factor) is also often desired. In some case of small-volume production, the torque converter modifications are limited to the stator only in order to reduce the manufacturing cost. In the present study, the engineering CFD simulations were used to develop new stators for stall torque ratio and K factor improvement. The flow fields of both baseline and modified torque converters were simulated. The overall performances of the converter were calculated from the flow field data, and correlated with the dyno test data.

Once a vehicle powertrain is designed and the first prototype is built, extensive on-board instrumentation and testing needs to be carried out at the proving grounds (PG) to generate load histograms for various components. The load histograms can then be used to carry out durability tests in the laboratory. When a component in the vehicle powertrain is changed, the load histograms need to be generated again at the proving grounds. This adds much time and money to the vehicle's development. The objective is to develop a virtual powertrain model that can be simulated through a powertrain endurance driving cycle in order to predict torque histograms and total damage. The predictions are then correlated against measured data acquired on a test vehicle that was driven through the same driving cycle at the proving grounds.

An impinging-flow based methodology of enhancing the heat transfer in the grooves of a lockup clutch is proposed and studied. In order to evaluate its efficacy and reveal the mechanism, the three-dimensional flow within the groove was solved as a conjugate heat transfer problem in a rotating reference frame using the commercial CFD code FLUENT. The turbulence characteristics were predicted using k-ε model. The comparison of cooling effect was made between a simple baseline groove pattern and a typical flow-impingement based groove pattern of the same groove-to-total area ratio in terms of heat rejection ratio, maximum surface temperature, and heat transfer coefficient. It is found that more heat can be rejected with the impinging-flow based groove from the friction surface than with the baseline while the maximum surface temperature is lower in the former case.

Understanding planetary gear efficiency is more involved than understanding efficiency of external gears because of the recirculating power that is inherent in planetary gear operation. There have been several publications going back several decades on this topic. However, many of these publications are mathematical in their approach and tend to be overlooked by practicing engineers. This paper brings a new, more visual and more intuitive approach to the problem. It uses lever diagrams, which have been a standard tool in the transmission engineer’s arsenal for almost four decades, to visualize the power flow and develop analytical expressions for the efficiency of simple and compound planetary gears. It then extends the approach to more complex gear trains.