There are two golden rules to thermal design: start simple and start early. The heat-flow path from the junction to the ambient, usually air in the local environment, determines a component’s temperature. Controlling temperature is therefore a system design challenge. Designers should employ a top-down approach (see the table) that increases confidence in the thermal design as the design progresses.
HAND CALCULATIONS
Heat-transfer correlations abound for natural and forced convection inside pipes and ducts, airflow over flat plates, and other scenarios. However, we advocate using rules of thumb, because correlations give a false impression of accuracy and are more difficult, and hence error-prone, to use.1
The heat-transfer coefficient for a 0.2-m long plate varies from 5 Wm-2K when horizontal in natural convection to 15 Wm-2K for forced convection at 3 ms-1, often the upper limit due to flowgenerated noise. To add a contribution for thermal radiation, we recommend using 10 Wm-2K for natural convection and 10 to 20 Wm-2K for forced convection.
First, calculate the temperature of the air in the enclosure if it’s a sealed system or the airflow needed to provide an air temperature rise of 10°C to 15°C for a forced convection system. The resulting internal air temperature is then used to calculate the printed-circuit-board (PCB) temperature. Finally, a package thermal metric like junction-to-board resistance (θJB) is used to calculate component temperatures.
For simple systems, the total thermal resistance can be considered a series resistance sum from component to board, board to internal air, and internal air to ambient. Systems that are more sophisticated need to be treated as a network of resistances, requiring enough experience to know what assumptions to make about the resistance network itself, and then to calculate the resistance values.
Heat transfer is always three-dimensional, so hand calculations and rules of thumb are of limited applicability. In practice, boards aren’t uniform in temperature due to the distribution of the heat sources and non-uniformity of the flow. However, the main disadvantage is that these approaches provide little insight into how the system can be improved.
COMPUTATIONAL FLUID DYNAMICS
We suggest a top-down approach, building a simple computational fluid dynamics (CFD) model of the entire system at the earliest phase of the design to:
• Provide insight into the way the system behaves using 3D flow and temperature visualization
• Explore different cooling strategies early in the design cycle
• Serve as the platform for incorporating further detail as the design evolves
• Build confidence in the design as the fidelity of the thermal model increases.
CONCEPTUAL DESIGN
The duration of this phase is often very short, sometimes requiring just a few days. The CFD tool must support very rapid turnaround, from geometry creation to results in a couple of hours. CFD tools employ a computational mesh to split the model into many small control volumes (cells) over which the basic equations for flow and heat transfer are solved. Each cell provides predictions of temperature, air speed, and pressure.
To be useful in conceptual design, the meshing has to be 100% reliable with no effort required on the part of users to control mesh quality and density. This tends to rule out general-purpose CFD tools that use automatic (i.e., algorithmic) meshing techniques in favor of EC-specific (electronics cooling) software.
The focus at this stage in the design is to investigate the basic mechanisms involved in removing heat from the system. For aircooled electronics, the objective is to predict the system-level airflow. So what does the model need to include?
The first step is to create a simple box for the enclosure, with a 2D bounding- box representation of any vents. The array of small holes should be accounted for using a porosity and loss coefficient. CFD tools specific to EC should provide this capability by allowing the diameter, pitch, and layout of the holes to be defined.
Internal electromagnetic compatibility (EMC) screens should also be included. On top of that, it’s a good idea to include buoyancy in forced convection-cooled systems, because natural convection effects can influence the flow behavior. The inclusion of buoyancy should not cause a delay in obtaining simulation results.
Thanks to their low cost, axial fans are preferred for forced cooling. A 2D representation of an axial fan is typically adequate at this stage, if care is taken to measure the correct open area for the fan. At minimum, use a linear fan curve to represent the fan’s performance.
In general, it’s considered better to draw air through the box, exhausting hot air to the surroundings, since this produces a more uniform flow through the enclosure. While it reduces the risk of dead spots, the fan will run hotter, affecting longevity.
It may be tempting to specify the cheapest, smallest fan to cool the system. This usually isn’t a good idea, though, because fans are noisy when operating close to their maximum flow rate and their reliability is compromised. Instead, specify a fan that can deliver two or more times the airflow needed to cool the system and de-rate it by reducing its speed.