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The main objective of this work is to present an adjoint-based methodology to address combined optimization of drag force and cooling flow rate of an industrial vehicle. In order to cope with cooling effect, the volumetric flow rate is treated through a newly introduced cost function and the corresponding adjoint source term is derived. Also an alternative strategy is presented to tackle aerodynamic vehicle design improvement that relies on a so-called indirect force computation. The overall optimization is treated as a Multi-Objective problem and an original approach, called Optimize Both Favor One (OBFO), is introduced that allows selective emphasis on one or another objective without resorting to artificial cost function balancing. Finally, comparative results are presented to demonstrate the merit of the proposed methodology.

A benchmark study was conducted to assess the capability of an open source CFD based process to accurately simulate the physics of the flow field around various vehicle types. The ICON FOAMpro process was used to simulate the flow field of four baseline geometries of a Truck, CD-Car, B-Car and an SUV. Further studies were carried out to assess the effects of geometry variations on the predicted aerodynamic lift and drag. A Detached-Eddy Simulation (DES) approach was chosen for the benchmarks. In addition to aerodynamic lift and drag values, the results for surface pressure data, surface and wake flow fields were calculated. These results were compared with values obtained using Ford's existing CFD processes.

This paper presents a complete methodology for performing finite-volume-based detached-eddy simulation for the prediction of aerodynamic forces and detailed flow structures of passenger vehicles developed using the open-source CFD toolbox OpenFOAM®. The main components of the methodology consist of an automatic mesh generator, a setup and initialisation utility, a DES flow solver and analysis and post-processing routines. Validation of the predictions is done on the basis of detailed comparisons to experimental wind-tunnel data. Results for lift and drag are found to compare favourably to the experiments, with some moderate discrepancies in predicted rear lift. Point surface-pressure measurements, oil-streak images and maps of total pressure in the flow field demonstrate the approach's capabilities to predict the fine detail of complex flow regimes found in automotive aerodynamics.

The number of computational fluid dynamics (CFD) simulations performed during the vehicle aerodynamic development process continues to expand at a rapid rate. One key contributor to this trend is the number of analytically based designed experiments performed to support vehicle aerodynamic shape development. A second contributor is the number of aerodynamic optimization studies performed for vehicle exterior components such as mirrors, underbody shields, spoilers, etc. A third contributor is the increasing number of “what if” exploratory studies performed early in the design process when the design is relatively fluid. Licensing costs for commercial CFD solutions can become a significant constraint as the number of simulations expands.

Aerodynamic vehicle design improvements require flow simulation driven iterative shape changes. The 3-D flow field simulations (CFD analysis) are not explicitly descriptive in providing the direction for aerodynamic shape changes (reducing drag force or increasing the down-force). In recent times, aerodynamic shape optimization using the adjoint method has been gaining more attention in the automotive industry. The traditional DOE (Design of Experiment) optimization method based on the shape parameters requires a large number of CFD flow simulations for obtaining design sensitivities of these shape parameters. The large number of CFD flow simulations can be significantly reduced if the adjoint method is applied. The main purpose of the present study is to demonstrate and validate the adjoint method for vehicle aerodynamic shape improvements.