Integration of CFD-CHT Analyses to Develop Harley-Davidson Motorcycles
Authors: Gupta Alka , Rajaee Mojtaba 
Published: February 2023

With the ever-increasing demand to reduce the product development cycle, Harley-Davidson Motor Company (HDMC) utilizes diverse CAE (Computer-Aided Engineering) tools to develop its motorcycles. These CAE tools assist resolving fluid, thermal and/or structural design refinements and challenges while minimizing the need to use physical models or prototypes, to achieve our goal of a complete virtual product development cycle and decreased time-to-market. The growing computational power and resource availability enables the option to simulate more complex physics with higher resolution and accuracy. The compatibility of the various CAE tools available provide options to choose the best tool based on the physics required and integrate with other applications.

This paper demonstrates an automated integration of a compact and complex vehicle CFD (Computational Fluids Dynamics) – CHT (Computational Heat Transfer) analysis, which provides a predictive solution for flow-thermal state of the vehicle, exhaust system, rider ambient, and electronic component internals. The focus of this paper is the methodology that encompasses physics of these models, the associated meshes, and the automated integration of the two. The paper discusses the utilization of aforementioned software tools to support a highly advanced and complex vehicle CAE flow-thermal predictive solution. Furthermore, the paper talks about how to arrive at a robust and detailed prediction of thermal state of vehicle with its electronic component internals such as LED (light-emitting diode), PCB (printed circuit board), and IC (integrated circuit) semiconductors, all driven by a combined external and internal thermo-fluidic flow and electronic operation waste heat.

The paper exhibits the versatility of a single CAE model which combines a full vehicle external aerodynamics CFD model and a stripped down CHT model consisting of powertrain, exhaust, cooling system, rider, and partial bodywork which are significant to meet the analysis objectives. The early intervention of these CAE techniques in the motorcycle development process accelerates the component design evaluation by eliminating/modifying initial designs based on the analyses results and assists in making educated and well-informed decisions. The visual representation of the analysis findings provides extremely valuable information which are sometimes not possible to obtain in a physical test environment and can save re-testing time and avoid delays as the test community strives to get data from those systems and components.

Our integrated CFD-CHT analysis method is comprised of full vehicle external aerodynamics CFD module with the export of local air conjugate heat transfer coefficients and reference temperatures, following the import of solid surface boundary temperatures computed via the computational heat transfer (CHT) module, and the automated integration and boundary data exchange iterations between the two modules. CHT module computes solid surface temperature of all heat emitting, and / or absorbing, vehicle components such as exhaust / powertrain, starter motor, and all electronic heat producing components, as well as manikin riders and vehicle components that may be impacted by heat emitting components. All three modes of heat transfer, including vehicle ambient radiation boundary conditions, are being considered in the model. Internal details of electronic components including, and not limited to, MOSFET (metal-oxide semiconductor field-effect transistor) semiconductors, LEDs, Thermal Interface Material (TIM), heat sink, etc., are included in the CHT module. The automated integration of CFD-CHT modules results in a converged full vehicle thermo-fluidic state of the vehicle in a steady-state or pseudo-transient duty. Similar approach is undertaken for EVs (electric vehicles) with details to the electronic PCB, and its components, and the battery pack Li-Ion cell internal levels.