The　interface　state　of　SiC/SiO2　is　one　of　the　key　factors　limiting　the　reliability　and　performance　of　SiC　MOSFETs.　In　this　paper,　we　built　a　dedicated　detrap　measurement　platform　to　improve　the　accuracy　of　trap　measurement.　Based　on　the　excellent　voltage　switching　time　of　this　platform,　the　entire　voltage　switching　process　can　be　controlled　within　1　μs,　and　the　time　resolution　is　also　improved.　The　original　millisecond-level　acquisition　accuracy　is　improved　to　a　microsecond　level,　and　the　identification　range　of　traps　is　expanded.　The　traps　were　extracted　by　using　the　transient　current　method　based　on　the　Bayesian　deconvolution　algorithm.　With　this　approach,　we　investigated　the　trapping　mechanism　of　SiC　MOSFETs　and　mainly　characterized　the　trap　locations,　energy　levels,　and　trapping　time　constants.　The　findings　revealed　the　existence　of　three　different　types　of　traps/defects,　Dp1,　Dp2,　and　Dp3,　with　activation　energies　of　0.28　eV,　0.035　eV,　and　0.084　eV,　respectively.　The　non-destructive　characterization　of　SiC　MOSFET　defects　can　be　realized　through　the　test　platform　and　Bayesian　deconvolution　algorithm　in　this　paper,　which　brings　great　convenience　for　trap　characterization.　　©　Published　under　licence　by　IOP　Publishing　Ltd.