Influence of the spider on loudspeaker thermal behavior: a predictive model based on lumped parameters

Villa L, Corsini C, Spatafora G, Mele D, Toppi R. Influence of the spider on loudspeaker thermal behavior: a predictive model based on lumped parameters. In: AES Convention 152. Audio Engineering Society; 2022. Paper 10567. Available from: https://aes.org/publications/elibrary-page/?id=21680

@inproceedings{Villa2022_21680,
  author = {Villa, Luca and Corsini, Chiara and Spatafora, Grazia and Mele, Davide and Toppi, Romolo},
  title = {{Influence of the spider on loudspeaker thermal behavior: a predictive model based on lumped parameters}},
  booktitle = {AES Convention 152},
  note = {Paper 10567},
  year = {2022},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=21680}
}

TY  - CPAPER
TI  - Influence of the spider on loudspeaker thermal behavior: a predictive model based on lumped parameters
AU  - Villa, Luca
AU  - Corsini, Chiara
AU  - Spatafora, Grazia
AU  - Mele, Davide
AU  - Toppi, Romolo
T2  - AES Convention 152
M1  - Paper 10567
PY  - 2022
DA  - 2022/05/06
UR  - https://aes.org/publications/elibrary-page/?id=21680
PB  - Audio Engineering Society
LA  - en
AB  - In the pre-design phase of a loudspeaker, rapid prediction of the loudspeaker thermal behavior is crucial. Voice coil (VC) temperature is not only influenced by the magnetic circuit materials and geometry, but also by thermal dissipation due to other speaker components e.g., the spider. The aim of this study is to develop a thermal model of the loudspeaker magnetic circuit that provides fast predictions of the VC temperature accounting for convective dissipation due to spider movement. An empirical method to evaluate the spider air permeability was presented and the related effects were implemented in the model. Life tests were performed on different loudspeakers to verify the accuracy of model results. Differences between predicted and measured VC temperatures were acceptable, suggesting possible application to the pre-design phase as the model can provide fast predictions without requiring high-performance hardware. 1 Introduction
ER  -