With the ever increasing consumer goods demand and increasing e-commerce sector, seeing truck-trailers dominate today’s roads and motorways is no strange sight. The large surface areas coupled with high operational speeds means these heavy goods vehicles produce high resistive forces, hence consuming significantly more fuel in comparison to an average family car. With increasing fuel costs truck-trailer designers are challenged to build more fuel efficient vehicles while still providing maximum cargo space. In order to be in motion, truck-trailer units must be able to overcome resistive forces such as aerodynamic drag, rolling and gravitational resistance, drivetrain resistance etc. With aerodynamic drag being the biggest resistive force at higher velocities, shape optimisation of truck-trailer units has proven to be the most effective and efficient method of making these vehicles more aerodynamic and hence, more fuel efficient. Boundary layer separation at sharp edges causes flow disturbance and creates negative pressure regions, which create more drag. By increasing the curvature of an edge the boundary layer separation can be minimised. By optimising the shape of a truck-trailer unit, the overall aerodynamic drag can be reduced.
The following study utilises modern computational techniques such as computational fluid dynamics (CFD) to closely examine the effects of the aerodynamic performance of the truck-trailer unit. The local and global variations in the flow parameters have been studied. Various truck-trailer configurations with changing dimensional parameters such as overall length, height and width was studied along with the geometrical shape parameters using both qualitative and quantitative analytical techniques. The obtained data and the conclusions drawn from the studies were used to develop a parametric model in order to introduce a novel aerodynamic prediction tool, which is expected to aid the truck-trailer design process.
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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