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Ten tips to maximize confidence in component temperature prediction

Prioritize thermal management for component temperature prediction

The complexity of electronics increases power densities which, in turn, increases heat dissipation requirements. Good thermal design for reliability and efficiency is vital as designers manage growing power requirements.

As mentioned in our Ten tips for streamlining PCB thermal design post, temperature differences between components impact printed circuit board and electronic assembly performance and reliability. Accurately predicting temperatures during operational cycles is essential to understanding future performance and operation.

Why focus on component temperature prediction?

Whether the intention is to increase reliability, improve performance or avoid problems during operation, accurate prediction of component temperatures helps thermal designers of electronic assemblies achieve their intended goals.

Historically, component temperature correlated to reliability. Designers can leverage pre-production thermal simulations to grow confidence in the thermal management of their designs. Reliable, accurate prediction of component temperatures allows designers to understand how close the design values come to the maximum allowable temperature.

Ten tips for predicting component temperatures

  1. Model key components explicitly
  2. Use good power estimates
  3. Use the right package thermal model
  4. Use compact thermal models from early design
  5. Create your own models as required
  6. Use power maps
  7. Validate detailed models with experiments
  8. Design custom heatsink solutions
  9. Accurately capture thermal interface material resistance
  10. Provide accurate temperatures for mechanical stress prediction

Learn more about these ten tips in our high-level how to-guide.

Katie Tormala

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This article first appeared on the Siemens Digital Industries Software blog at https://blogs.stage.sw.siemens.com/electronics-semiconductors/2022/04/27/thermal-management-electronics-temperature-prediction/