Jiahua Zhang

The increase in power density of hydrodynamic torque converters (HTCs) leads to a sharp rise in temperature within flow channels, affecting the reliability. In order to accurately predict the thermal effect and temperature distribution characteristics of the HTC internal viscosity oil, a multi-physics computational fluid dynamics (CFD) model is proposed. A specialized test bench was established, and the macro and internal flow temperature data were obtained. HTCs with different working conditions and wheel sets were studied. The results indicate that CFD model considering energy equation can accurately predict the overall hydrodynamic performance and the flow field temperature characteristics under different rotating conditions. The prediction error of the overall temperature rise is within 4.92%, and the flow field temperature prediction error of the stator is under 14.3%. The hydraulic characteristics is improved by 6.02%. The analysis of internal flow and energy exchange characteristics indicates the thermal effects and temperature distribution mechanisms caused by energy loss in the flow field within the HTC. The study provides an effective computational model for the prediction and control of the heat generation of the HTC and enhances the depth of research on the flow mechanism of inhomogeneous flow fields caused by thermal effects.

The purpose of this paper is to study the mechanism and improve the prediction accuracy of transient torque converter cavitation flow by the application of scale-resolving simulation (SRS) methods with particular focus on cavitation vortex flow. Firstly, the numerical analysis of the entire internal flow field of the torque converter was carried out using different turbulence models, and the prediction accuracy of the hydraulic characteristics of the adopted models was analyzed and validated via test data. Secondly, the cavitation and turbulence behavior in the internal flow field were analyzed, and the blade surface pressure according to different turbulence models was compared and validated through test data. Finally, the transient cavitation characteristics of the flow field were studied based on the stress-blended eddy simulation (SBES) model. The prediction accuracy of the cavitation flow field simulation of the torque converter is significantly improved using the SRS model. The maximum error of capacity constant, torque ratio and efficiency are reduced to 3.1%, 2.3%, and 1.3% at stall, respectively. The stator is more prone to cavitation than pump and turbine. The SBES model has the highest prediction accuracy in multiple measurement points, and the maximum deviation can reach 13.32% under stall. Attached cavitation bubbles and periodic shedding cavitation can be found in the stator, and the evolution period is about 0.0036 s, i.e., 279 Hz. The prediction accuracy of different models was compared and analyzed, which has important guiding significance for the high-precision prediction and analysis of fluid machinery.

The performance of torque converters, which use hydraulic oil as the working medium to transmit power, are severely affected by the operating temperature because various oil properties, such as viscosity, density and saturated pressure, vary drastically with temperature change. To study the thermal effect on the cavitation characteristics of viscous oil, we developed a full flow passage geometry and computational fluid dynamics (CFD) model with cavitation based on the finite volume method (FVM) to predict and analyze cavitation behavior and thermal effect in a torque converter. The results show that the critical cavitation number and critical cavitation temperature of the tested torque converter are 9.2 and 30 °C, respectively, and increasing the temperature reduces the cavitation number and induces the generation and intensification of cavitation. Besides, although higher temperature improves the transmission efficiency and capacity constant of the torque converter, it greatly magnifies the influence of cavitation on the hydrodynamic performance. In severe cases, it reduces the hydraulic performance by 9.3% and the flow velocity by 11.8% at 100 °C. Meanwhile, the cavitation flow field and the configuration of cavitation are also greatly affected by temperature. About 11.9% of the surface of the stator blade was covered by cavitation bubbles with the vapor volume fraction of 88.1% at 100 °C. Moreover, 30–60 °C is the optimum operating temperature range in terms of cavitations effect with no pronounced cavitation occurrence or that the cavitation degree is too weak to affect the performance in the mentioned temperature range.

Hydraulic torque converters are prone to cavitation due to their high impeller rotational speeds and their complex three-dimensional flow characteristics. Since the blades are the core components of torque converters, the shapes of the blades are important to the hydraulic performance and cavitation characteristics. Different cavitation computational fluid dynamics (CFD) models for a torque converter were developed to simulate the internal cavitation flow for different pump and turbine blade exit angles, and the influence of the blade angles on the cavitation characteristics and cavitation flow field in the torque converter was investigated. Experimental prototypes were produced and tested for verification. The results indicate that the pump and turbine blade exit angles had significant effects on the cavitation number of the torque converter. Increasing the pump and turbine blade exit angles promotes the generation and intensification of cavitation, resulting in severe changes in the shapes and locations of the cavitation bubbles due to changes in the fluid impact angles. Additionally, cavitation is quickly suppressed and the performance is improved when the blade exit angles are reduced within an appropriate range, in particular, that of the turbine blade. These research results can provide guidance for the design of a high-performance hydraulic torque converter cascade system and the suppression of cavitation for practical engineering applications.