A novel thermoelectric CPU cooling system controlled by artificial intelligence

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dc.authoridumut, ilhan/0000-0002-5269-1128
dc.authorwosidumut, ilhan/A-2772-2017
dc.contributor.authorUmut, Ilhan
dc.contributor.authorAkal, Dincer
dc.date.accessioned2024-06-12T10:52:34Z
dc.date.available2024-06-12T10:52:34Z
dc.date.issued2024
dc.departmentTrakya Üniversitesien_US
dc.description.abstractFigure A shows the components of the additional TEC unit designed in addition to the CPU cooling fan. In order to realize the heat transfer by conduction between the TEC unit and the CPU, the aluminum plate (TEC Module Interface Connection), seen in (Figure A), is designed. On the plate used in this TEC unit, there are thermoelectric module (TEC-12706), heatsink and fan. Since the temperature of the thermoelectric cooler will always be lower than the CPU temperature, effective cooling will be ensured.Purpose: Temperature rise in computers is an undesirable situation that occurs depending on the processor load. Due to excessive temperature rise in the Central Processing Unit (CPU), computers shut down and system damage occurs over time. In this study, a new thermoelectric cooling system is designed to reduce the temperature in the CPU. In addition, 3 different artificial intelligence models were created for the dynamic control of the system and their successes were compared.Theory and Methods: The new cooling system is designed using a thermoelectric module. It is to remove the excess heat by conduction and convection by taking advantage of the temperature difference between the thermoelectric cooler and the CPU we add to the system. Since the temperature of the thermoelectric cooler will always be lower than the CPU temperature, effective cooling will be provided. A special electronic circuit and software have been developed for the control of the cooling unit. Three different artificial intelligence models (artificial neural network, random forest, and k-nearest neighbor) were created to dynamically control the additional cooling system and their successes were compared. Artificial intelligence determines the power and fan speed of the thermoelectric cooling system. It performs this control by evaluating all parameters (different values such as CPU frequency, voltage, number of processes) instead of a specific CPU load or a specific temperature value.Results: While the CPU temperature was 41 & DEG;C at maximum load, this temperature was reduced to 310C thanks to the designed thermoelectric cooling system. All methods provided a high classification success in training. However, the classification success of the artificial neural network method (97.973%) is higher than the random forest (97.297%) and the k-nearest neighbor (96.306%). Conclusion: In the standard CPU fan, the CPU temperature at maximum load was 41 & DEG;C and the maximum energy consumed by the fan for cooling was 8 Watts. Thanks to the developed thermoelectric cooler system, the CPU temperature was reduced to 31 & DEG;C and the energy difference for this process was maximum 12 Watts, at maximum load.en_US
dc.identifier.doi10.17341/gazimmfd.1150632
dc.identifier.endpage124en_US
dc.identifier.issn1300-1884
dc.identifier.issn1304-4915
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85174163984en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage113en_US
dc.identifier.urihttps://doi.org/10.17341/gazimmfd.1150632
dc.identifier.urihttps://hdl.handle.net/20.500.14551/18761
dc.identifier.volume39en_US
dc.identifier.wosWOS:001058089000010en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherGazi Univ, Fac Engineering Architectureen_US
dc.relation.ispartofJournal Of The Faculty Of Engineering And Architecture Of Gazi Universityen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectCoolingen_US
dc.subjectCentral Processing Uniten_US
dc.subjectEnergyen_US
dc.subjectThermoelectricityen_US
dc.titleA novel thermoelectric CPU cooling system controlled by artificial intelligenceen_US
dc.typeArticleen_US

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