Heat exchange performance optimization of a wheel loader cooling system based on computational fluid dynamic simulation

Abstract

This study establishes a thermal management model to improve the heat exchange performance and uniformity of the flow-field distribution in the engine compartment of a wheel loader. Flow-field analyses are performed for an XG956 wheel loader in a virtual wind tunnel using the combined engine compartment thermal management model and computational fluid dynamics. The Fluent calculations revealed various problems. For example, the inlet flow rate at both sides of the engine compartment is small, which accounts for about 8.5% of the total flow, and the flow uniformity of radiator becomes worse with the increase in the air flow. The original cooling system is improved based on the simulation results and then verified by field testing. A comparison of the test data with the simulations indicates that the values obtained using the thermal management model of the engine compartment are largely in agreement with the experimental values, with a maximum deviation of the heat transfer rate at the rated speed of 5.1%. The research method presented in this article could further help to increase the productivity of the non-road mobile machinery cooling system and lower design costs. The temperature of pressurized air, hydraulic oil, transmission oil, and engine cooling fluid decreased by 22.5%, 8.7%, 2.2%, and 8.4% in the improved loader, respectively.

Optimization of wavy fin‐and‐elliptical tube heat exchanger using CFD, multi‐objective genetic algorithm and radical basis function

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Comparative Study on CFD Turbulence Models for the Flow Field in Air Cooled Radiator

“…During the calculation, the fan rotates along the mesh section at a certain time step (0.01 s). When the change of mass flow rate in two consecutive circulatory iterations and all normalized residuals in mass and momentum conservation equations were less than 10 −4 for the differences, the solution was assumed to be converged [24][25][26][27]. The fan speed is the same as the experimental value.…”

Effect of transverse flow in porous medium on heat exchanger simulation optimization

“…The physical property parameter settings are as follows: The hot pressurized air side was 120°C; the dynamic viscosity was 22.84 × 10 −6 kg/m•s; the density was 2.656 kg/m 3 ; the coefficient of thermal conductivity was 0.0325 w/m•k. The cold side was glycol cooling fluid; the dynamic viscosity was 7.14 × 10 −4 kg/m•s; the density was 1013 kg/m 3 ; coefficient of thermal conductivity was 0.4043 w/m•k (Song et al 2014;Yu et al 2018). In this research, the k-ε turbulence model was used for simulation by Fluent, and the transport equation of the standard k-ε model is as follows (Yu et al 2018):…”