HeatSinkSim

HeatSinkSim

Changing Electronics Cooling

 

It has been a while since we have put out a Blog on electronics cooling and there is a very good reason for that – not much has changed, until now.

 

Progressive companies manufacturing electronic components and circuits consistently challenge the limits of component performance by offering increased functionality in a decreased product size. The associated increase in power density develops significant thermal energy that must be dissipated to maintain accurate long term performance. For components and circuits used in critical applications required to maintain operation such as continuous manufacturing operations and emergency communication systems, passive approaches for dissipating thermal energy are preferred.

 

But as we have demonstrated in previous blogs, traditional approaches for evaluating the thermal margin of safety are inherently conservative due to the significant assumptions made in calculating dissipation of thermal energy.  Consequently, assessing the thermal response of a new device is generally left until late in the design process – following form and function. From the designer’s standpoint, getting traction on thermal challenges early in the design process is difficult for a few reasons:

 

  • Estimating heat transfer rates before prototypes are available is not easy
  • Allowable thermal margins may be masked by inherent limitations even after prototypes are made
  • Waiting for sufficient testing can be a time-consuming and expensive process

 

If accuracy is required, predictive physics based computational analysis can be used but this requires access to skilled personnel, and sophisticated hardware and software. Any one of these could be a significant hindrance, but when all three are combined the resulting obstacle may become insurmountable for all but the largest companies.

 

A solution we developed following discussions with many of our customers, ranging from large multinational organizations to small individual developers, uses a computational simulation application (CApp) to explore the thermal behavior of power electronic devices. The CApp is HeatSinkSim which provides the accuracy of a physics based computational analysis with the ease of use of a spreadsheet – the first of a series of CApps to provide designers with the capability to examine the effect of heat sink design on thermal dissipation in power electronic components.

 

Heatsinksim

 

 

HeatSinkSim solves the conjugate heat transfer problem for a vertically oriented plate fin heat sink operating under natural convection. Heat transfer is analyzed as a combination of conduction, convection and radiation with a full solution to the associated thermal and fluid flow problem. Two levels of analysis are available: first, a parametric study of heat sink design, and secondly, an optional detailed analysis that provides highly accurate temperature distributions for the optimum design of heat sink. The second level of analysis is recommended when device specific limits on casing temperature and/or junction temperature are approached. The model was developed and validated in conjunction with detailed experimental measurements that have allowed inclusion of these automated warnings based on the level of accuracy expected from the analysis.

 

The user inputs the heat sink geometry, materials of construction and operating conditions.

 

SetUp

 

Once the desired geometry, materials and operating conditions are established the associated computational analysis file, including geometry development, meshing, physics set up and solver settings, is automatically generated and submitted for execution. The complexity of the conjugate heat transfer analysis requires significant computational resources to provide an accurate solution and thus HeatSinkSim has been configured to run on cluster computing hardware. The App automatically identifies the computational resources required to complete the analysis and distributes the analysis over the available nodes/cores. On completion of the analysis the user is automatically prompted to review the results and download a standardized report. To allow general access, AltaSim is making HeatSinkSim available for use on personal clusters as well as through secure connection to independent parallel computing resources to ensure confidentiality; further customization for individual users can be performed if needed.

 

 

Results

 

 

Access to the app and the hardware required to run the simulations is available through AweSim using a variety of payment options ranging from an annual license with unlimited use to pay-per-use options.

 

For more information on HeatSinkSim, contact Jeff Crompton at AltaSim Technologies (jeff at altasimtechnologies.com).

 

 

Heat Sink Design

Heat Sink Design

 

In last month’s Blog we discussed alternative techniques for increasing the amount of heat dissipation in electronic circuits and components. One of the most commonly used approaches to increase heat dissipation is the use of heat sinks. Heat sink design seeks to maximize the surface area in contact with the surrounding cooling medium, generally air in these applications, and is attached using thermal interface materials that have high thermal conductivity and fill the air gap between the component and the heat sink. Air velocity, direction of flow, choice of material, protrusion design and surface treatment are all factors that affect the performance of a heat sink. Heat sink design can take many forms:

  1. Plate-fins: A series of plates or sheets run along the entire length of the attachment area
  2. Pin-fins: Pins are arranged in a regular array and extend
  3. Flared plate fins: A series of non-parallel plates that run along the entire length of the attachment area

In this Blog we address heat sink design and provide guidelines for developing an optimum design for the case of natural convection.

 

A heat sink transfers thermal energy from a higher temperature device to a surrounding fluid medium which is generally air but could also be water, oil or a refrigerant depending on the application, for the purposes of the applications of interest here we will consider the fluid to be air. Thermal dissipation through the heat sink occurs by a conjugate heat transfer mechanism in which transfer of thermal energy occurs by a combination of conduction through the heat sink and into the fluid, convection of the surrounding fluid and radiation into the environment. In most situations, heat transfer across the interface between the solid surface and the coolant air is the least efficient within the system, and the solid-air interface represents the greatest barrier for heat dissipation, a heat sink lowers this barrier mainly by increasing the surface area that is in direct contact with the coolant.

 

Natural convection arises because the hot air has a lower density and thus rises under the buoyancy forces created. This flow can be represented by the dimensionless Grashof number, Gr, that represents the ratio of the buoyancy force to the viscous force acting on the fluid and is given by:

 

Gr        ~ Buoyancy force / Viscous forces

= g.β.(Ts-T).δ3 / ν2                 (1)

 

Where g is the gravitational acceleration (ms-2), β is the coefficient of volume expansion (1/K), Ts is the surface temperature (K), T is the ambient temperature (K), δ is the characteristic length of the geometry (m), and ν is the kinematic viscosity of the fluid (m2s-1). For vertical plates values of Gr > ~ 109 flow is turbulent.

 

Heat transfer into the fluid can be characterized by the Prandtl number, Pr, momentum diffusivity to thermal diffusivity:

Pr         = viscous diffusion rate / thermal diffusion rate

= (cp.µ) / k                               (2)

Where cp is the specific heat capacity (J/kg.K), µ is the dynamic viscosity (Pa.s) and k is thermal conductivity (W/m.K). The Prandtl number controls the relative thickness of the momentum and thermal boundary layers and is often tabulated with other fluid properties, for air and many other gases it is considered that Pr ranges between 0.7 and 0.8. When heat conduction is effective compared to convection: thermal diffusivity is dominant. When convection is effective in transferring energy from an area, compared to pure conduction: momentum diffusivity is dominant.

 

The optimum heat sink design is a balance of maximizing surface area while at the same time setting the spacing of the fines to allow maximum air flow and minimizing friction. Thus heat sinks with closely spaced fins are not suitable for natural convection. The optimum fin spacing for a vertical heat sink is given by:

Sopt = 2.714 (L/Ra1/4)                            (3)

Where L is the characteristic length and Ra is the Reynolds number.

 

The heat transfer coefficient for the optimum spacing is given by:

H = 1.31 (k/Sopt)                                   (4)

Consider the following example: A vertical surface at 80°C is to be cooled by a heat sink in air at an ambient temperature of 20°C. The plate has a width of 20 cm and a height of 30cm, the fins of the heat exchanger are 1mm thick, 30cm long and have a height of 10mm.

Geometry for Heat Sink Design

 

The average temperature of the air on the surface of the fin is 50°C: at this temperature the thermal conductivity, k, is 0.0279 W/m.K, the kinematic viscosity, ν, is 1.82 x 10-5 m2/s, Pr is 0.709 and assuming ideal gas behavior the coefficient of volume expansion, β, is 1/(Ts+T)/2) = 3.1 x 10-3. The characteristic length , L, is the length of the fin thus the Reynold’s number, Ra, is given by:

Ra        = Gr.Pr

 

The optimum spacing Sopt is then determined by equation 3 to be 8.03mm. For a fin thickness of 1mm the number of fins on the heat exchanger is ~22. The heat transfer coefficient can be calculated using equation 4 to be 4.54 W/m.K.

 

 

 

Approaches to Thermal Mitigation

Thermal Mitigation – Common Approaches

 Thermal mitigation for high power electronics

If the operating temperatures remain outside the prescribed thermal budget established for safe device and component operation we are now faced with two options: either reduce the power levels that may change device functionality or increase the dissipation of heat to reduce the standard operating temperatures.

 

In some cases changes to the operating power may be possible without a loss in functionality by using adaptive control algorithms that reduce the duty cycle when excessive temperatures are approached but this is not a universal solution and other measures must be taken. Reductions in the operating temperatures can be obtained by implementing additional paths for thermal conduction that increase dissipation of heat into the surrounding environment. Some of the more common approaches are listed below:

 

1. Printed circuit board design

  • Without applying additional thermal dissipation mechanisms it is to be expected that up to 80% of the heat will be dissipated through the PCB. As the lowest resistance pathway heat is preferentially conducted through the copper layers and dissipated into the surrounding environment or through additional connections. Simple increases in the percentage of copper in the layers, and especially the outer layers, can provide a significant increase in dissipation. Addition of thermal vias under high power components will lead to increased thermal transport into the PCB and the addition of thermal pads to the outer layer of the PCB can provide an effective mechanism for dissipation into the environment. However, these modifications are only likely to provide modest gains and thermal pathways with much reduced resistance have to be integrated to significantly modify the thermal footprint of an operating device or component.

2. Material selection

  • Many of the materials used to construct devices and components, eg copper, gold, silver and silicon, have thermal conductivities that are several orders of magnitude higher than those of the PCB and surrounding air domain. As outlined above increasing the thermal conductivity can be obtained by introducing additional features such that the air domain can become a limiting factor. This becomes most important in situations where an air gap exists between the hot component and a path for dissipation. Such gaps are to be expected either from the inherent roughness associated with surfaces or from tolerances in component fit up. This problem can be overcome by replacing the air gap with thermal interface materials that have thermal conductivities that can be 200x that of air.

3. Heat sinks

  • Heat sinks are passive heat exchangers that can dissipate large amounts of heat into the surrounding environment by either natural or forced convection. To take full advantage you still have to get the heat from the power components and dissipate it into the atmosphere which may require close control of material properties and airflow. Heat sinks are designed to maximize the surface area in contact with the cooling medium. Air velocity, choice of material, protrusion design and surface treatment are factors that affect the performance of a heat sink. To be most effective both mass flow rate and turbulence need to be maximized. The effectiveness of a heat sink depends on the temperature difference between the heat sink itself and the adjacent air. If the air is warm (right against the fins) then the heat sink must run hotter than it would with cooler air against the fins. The most effective heat sinks are attached to the component using thermal interface materials that both fill air gaps and act as a high conductivity path.

4. Forced air cooling

  • Forced-air cooling using a fan to blow air across hot components is very common and completely internal fans are used by many manufacturers. To be most effective the fan must blow air across the component to provide the best cooling; air leaving the fan blades is turbulent, and it swirls around vigorously as it leaves the fan blades. This allows the airflow to disrupt otherwise stagnant air therefore providing the maximum supply of cool air. If the fan is set to suck air across the surface the flow will be laminar, moving fastest in the centre, with comparatively little movement at the surface.

5. Water cooling

  • Water is the best heat removal media known, with a specific heat of 4.1813 (J / (g·K)), it requires more energy to raise a gram of water by one degree C (or 1 Kelvin) than any other material. Consequently if extremely high power is the goal, a water cooled heat sink is an option to be considered. Provided the thermal resistance from the junction to the heat sink is minimized, a small heat sink with moderate water flow will remove large amounts of heat.

6. Heat pipes

  • Heat pipes are most commonly used where a hot component must be cooled in a confined space. The heat pipe provides heat-transfer by combining both thermal conductivity and phase transition to efficiently manage the transfer of heat between two solid interfaces. A heat pipe is essentially two heat sinks, joined by a pipe; at the hot interface a liquid in contact with a thermally conductive solid surface turns into a vapor. The vapor then travels along the heat pipe to the cold interface and condenses – releasing the latent heat. The liquid then returns to the hot interface, and the cycle repeats. Newer versions make use of ‘micro-channels’ to dramatically increase the surface area at the hot end and allow the use of environmentally friendly coolants.

7. Other technologies – Two other technologies that may be of interest for cooling strategies are:

  • Thermoelectrics: The most commonly used thermoelectric material is bismuth telluride (Bi2Te3). These materials provide the option by which either a temperature difference creates an electric potential or an electric potential creates a temperature difference. These phenomena are known more specifically as the Seebeck effect (converting temperature to current), Peltier effect (converting current to temperature), and Thomson effect (conductor heating/cooling). Thus localized cooling can be directly obtained but heat dissipation from the thermoelectric material may still be required.
  • Piezo fans: Piezo-electric material produce changes in shape when subject to an applied voltage, or vice versa. When subject to an oscillating voltage an oscillating motion can be developed, that, when attached to structures that resonate at the applied frequency, can act as a fan for localized air flow thus enhancing local cooling.

 

In brief, options for reducing the temperature of devices and components require that additional paths with high thermal conductivity are added to increase dissipation of heat into the surrounding environment. This is most effectively obtained by modifying the materials of construction, adding heat sinks and increasing local air flow by natural or forced convection. The most commonly used of these approaches if the addition of heat sinks, further details on the design of effective heat sinks will be covered in the next Blog. In the meantime please feel free to contact us if you have questions about thermal analysis of electronics or feasibility studies in general, or if you would like to discuss thermal aspects of your application.

 

Improved Thermal Analysis for Electronics Cooling

So far we have explored preliminary ways to predict the temperatures in a circuit using simple thermal resistance network calculations. This post addresses improved thermal analysis for electronics cooling. Consistent exposure to high operating temperatures can lead to degradation of material properties and development of thermal stresses that can ultimately lead to device failure. The relationship between reliability and the operating temperature of a typical silicon semiconductor device shows that an increase in operating temperature corresponds to an exponential decrease in reliability and life expectancy of the device it is essential that the operating temperatures are maintained at specific levels.

To reduce the temperatures to an acceptable level three approaches are generally considered:

  1. Reconfigure the components, power settings and operating conditions to reduce the temperatures,
  2. Refine the thermal calculation to develop a more accurate prediction of the temperature distribution, or
  3. Identify potential mitigation techniques

 

The first option is at the discretion of the circuit and application designers and is therefore beyond the scope of these Blogs so let’s examine ways to improve the accuracy of the temperature calculation to make sure we can remain in the allocated thermal budget. While it is tempting to add complexity to the thermal resistance approach by adding more thermal resistance pathways this step alone will not increase the accuracy to the level required. As we have seen the inherent assumptions in the thermal resistance network approach, for example the use of convection coefficients, can significantly affect the accuracy of the solution.

 

Two other approaches of thermal analysis for electronics cooling exist that can provide a more accurate assessment of the thermal profile of a power electronics circuit.  First, Green function formulations simplify the problem to two dimensional modeling and are consequently fast but provide limited accuracy. Secondly, predictive physics based computational simulation techniques using finite difference, finite element or boundary–element techniques can explicitly solve heat transfer due to combined conduction, convection and radiation. These techniques provide high accuracy, incorporate multiple, independent heat sources and apply different boundary conditions to provide an accurate representation of a circuit’s behavior. The main drawbacks of these approaches are that the complexity of the problem set up often requires use by skilled personnel and they may require specific computational hardware to deal with the size of the analysis files. Despite these problems computational thermal analysis of power electronics circuits is widely available and provides critical information to alleviate thermal management problems.

 

Traditionally predictive physics based computational approaches have been used to analyze behavior at the system level when problems exist that may be too deeply ingrained to provide an optimum solution. Integration of computational analysis earlier in the concept and prototype phases can not only lead to improved performance but can also accelerate the rate at which products are developed. Generally computational analysis can be valuable in the following stages of product development:

 

1) Concept

  • Little detail of the circuit of component may be known but this allows the development of thermal analyses that are simple and quick to implement while still providing valuable information and advanced warning about potential problems. Features and layout can be examined at a stage in the product development where limited investment has been made so that costs for any required changes are minimal.

2) Prototype

  • Components may be represented by isolated blocks with assigned powers and details of board construction and leads may be simplified by using averaged properties. Individual material properties and thermal resistances for the components will generally be assigned at this stage.

3) Final design

  • Construction details of the board and components are typically included such that copper layers or thermal vias in the board are discretely identified, and individual construction details of the components including leads, solder balls and connectivity to the PCB. This analysis provides the most detailed description of the thermal behavior of the product of interest and most likely will require significant computational resources and time to complete the analysis.

The process of developing a predictive analysis involves the following steps:

  1. Geometry development
  2. Assign material properties
  3. Develop discrete mesh
  4. Integrate relevant physics and inputs
  5. Apply boundary conditions
  6. Solve the problem
  7. Analyze the results
  8. Modify set up to address problems or optimize design and operation

Virtual representation of the circuit by is obtained by discretizing the components into domains each having their respective geometric shape and spatial location, e.g. Figure 1. Some simplification or defeaturing of the geometry may be performed on features having no effect on the analysis or components not influencing behavior may be eliminated, eg fillets, fasteners and labels, while maintaining individual control over critical aspects of the geometry, eg vent size, spacing, pitch, shape etc.

 

thermal analysis for electronics cooling

Figure 1: Example of component geometry and surrounding spatial volume.

 

Connectivity between the various components is maintained and individual materials properties that may be a function of temperature are assigned to the respective components. Details such as individual copper layer, vias or interconnects can be defined if needed but it must be realized that inclusion of these details may affect the computational resources needed to run the model and may only be needed for more detailed assessments. Isolated powers are applied to individual components as defined by the device operation and the analysis can be set up to include any combination of thermal transfer due to conduction and radiation or fluid flow of the type needed to solve heat transfer due to convection

 

As the components heat up the heated fluid at the surface has a lower density and thus rises creating a natural convection current. The surrounding cooler fluid then moves to replace it thus creating a buoyancy effect. This cooler fluid is then heated and the process continues transferring heat energy from the bottom of the convection cell to the top. Alternatively air may be forced to flow over the components by fans producing defined flow rates.

Heat transfer within the solid domain is described by the standard heat equation:

Eq1

where, ρ is the density of the solid or fluid material, cp is the specific heat capacity, T is the temperature, and λ is the thermal conductivity.

In the fluid domain, the physics are described by the conservation of mass, momentum, and energy according to the following equations:

                                                                           Eq2

         Eq3

                                                                        Eq4

The viscous heating and pressure work terms are neglected in the energy equation.  In the above equations, ρ is the density, u is the velocity vector, p is the pressure, η is the dynamic viscosity, g is the gravitational acceleration vector, k is the thermal conductivity, T is the temperature, Q is a heat source term, and cp is the specific heat capacity.  The viscosity, thermal conductivity, and specific heat capacity are functions of temperature, while the density is a function of both temperature and pressure. The heat flux at the surface of the part due to radiation is modeled by:

                                   Eq5

where εemis is the emissivity of the surface, Gm is the mutual irradiation from other surfaces, Famb is the ambient view factor, σ is the Stefan-Boltzmann constant, Tamb is the far-away ambient temperature, and T is the temperature at the surface.  Gm is a function of the radiosity. In the presence of mutually irradiating surfaces, the ambient view factor and mutual irradiation can be automatically computed by most computational analysis packages.

Results of the analyses can provide significant information and understanding about the distribution of thermal energy in the circuit and the flow of air resulting from any natural or forced convection, e.g Figures 2 and 3. The effectiveness of potential solutions to problems can be rapidly evaluated by inserting additional features or heat conduction paths to identify the resultant thermal distribution.

 

Figure 2: Surface temperature distribution

Figure 3: Air flow velocity

Further refinement of the analysis can also provide valuable information about component case and junction temperatures that can aid in the design and development of appropriate heat dissipation techniques to ensure that operational conditions are maintained in the required range. Details of the individual component or board construction including leads and solder balls in the chips, and copper vias and planes in the board can also be integrated to provide a detailed analysis of the final design and identification of localized behavior. The more detailed the analysis the more accurate the temperature predictions but also the more complex the analysis is to set up.

 

Once properly calibrated and validated computational procedures have been developed the results of the analyses can be used to optimize designs and operating procedures with much greater tolerances than the preliminary resistance network procedures discussed in earlier Blogs. Alternatively trends and sensitivities can be easily explored to allow the effect of changes in design to be identified without the need to retrofit operational components with last minute fixes to problems uncovered in traditional testing and evaluation approaches. The higher level of fidelity and accuracy obtained with these computational approaches allows safe component and device operation close to the boundaries of the established thermal budget and a more comprehensive exploration of the safe operating space. Future Blogs will look at mechanisms to dissipate heat when normal operating temperatures exceed recommended values.

 

Please feel free to contact us if you have questions about thermal analysis for electronics or feasibility studies in general, or if you would like to discuss thermal aspects of your application.

 

Estimating heat transfer coefficients

Previously we have discussed ways to complete a feasibility thermal management analysis. For a given thermal budget, we want to determine whether the junction temperature will meet specifications for reliability and thermal runaway.

 

In electronic systems that rely on air flow for cooling, convection is of paramount importance.

 

Power dissipation due to convection is given by q = hA(ΔT), where q is the power dissipated (W), h is the heat transfer coefficient in

W/(m2K), A is the surface area exposed to the flow (m2) and ΔT = Tsurface – Tambient (⁰C).  The largest degree of uncertainty lies with Tsurface and h, so in the feasibility analysis we can solve for temperatures given a value for h.

 

Obtaining a heat transfer coefficient a priori is difficult, we suggest using a range of values representative of different conditions. Ultimately if high values of h are selected it suggest that the thermal behavior may need to be redesigned.

 

The table below provides approximate heat transfer coefficients for different conditions.  [H.S. represents Heat Sink.]

Case

Electronics Environment

Heat transfer model

Thermal solution over component

Approximate Heat Transfer Coefficient (in W/m2K)

Approximate thermal resistance (⁰C/W)

A

Handheld device with up to 2 mm air gap, operates when horizontal

Conduction through air

(worst case)

None

Treat as conduction in gap

50 – 100

B

Small module, no fan, orientation controlled (always vertical). Open top & bottom, chimney style convection

Natural convection h also depends on ΔT & height

Optimized plate fin heat sink (vertical base & fins)

For plate fin heat sinks, correlations are readily available*

3 – 6

(based on H.S. area)

1 – 5

C

Laptop

Single small fan

Optimized heat sink

25 – 100

(based on H.S. area)

1 – 20

D

Desktop

Multiple fans

Optimized heat sink

50 – 150

(based on H.S. area)

0.25 – 5

* White, Frank M., Heat and Mass Transfer, Adison-Wesley © 1991, p. 408-9.

 

 

With heat sinks it is important to remember that simply increasing the number of fins does not automatically lead to increased heat dissipation, as the fins approach each other the resistance to flow also increases, causing h to drop.  This is why in case B above, the systems cannot be optimized further.

 

For cases C and D, further effort may be needed to select an appropriate heat sink.  Some suppliers can provide an estimate of the thermal resistance associated with the heat sink based on a representative airspeed in Linear Feet per Minute (LFM). So you may be able to complete your system-level feasibility analysis by simply using a network of thermal resistances, without having to explicitly assume a heat transfer coefficient value.

 

Learn more about electronics cooling. and AltaSim’s support for electronics cooling analysis.

 

Popular Posts
COMSOL Tips & Tricks v5.3: Model Methods Feature

New to version 5.3: Model Method Feature
 

To help…

Free Medical Devices Simulation Webinar

Computational Simulation for Medical Devices
 
Jeff Crompton and Kyle…

COMSOL Conference 2016 Follow Up

Each year we invest some of our time at the…

Newsletter Registration:
Ask AltaSim: