An equipment for estimating a motor parameter , the equipment comprising an input interface configured to receive an operating parameter ( u d,q , i d,q , ω e ) of an electric motor, a first device configured to perform a first parameter estimation algorithm estimating an estimated first motor parameter ( Ψ PM,1 ) based on the operating parameter ( u d,q , i d,q , ω e ) and on an initially determined second motor parameter ( R s,0 ) , and a second device configured to perform a second parameter estimation algorithm estimating an estimated second motor parameter ( R s,1 ) based on the operating parameter ( u d,q , i d,q , ω e ) and on an initially determined first motor parameter ( Ψ PM,0 ), wherein the equipment further comprises a third device configured to perform a third parameter estimation algorithm estimating a revised estimated second motor parameter ( R s , 2 ) based on the estimated first motor parameter ( Ψ PM,1 ) and on the operating parameter ( u d,q , i d,q , ω e ) , and a fourth device configured to perform a fourth parameter estimation algorithm estimating a revised estimated first motor parameter ( Ψ PM,2 ) based on the estimated second motor parameter ( R s,1 ) and on the operating parameter ( u d,q , i d,q , ω e ), wherein the operating parameter ( u d,q , i d,q , ω e ) comprises at least one of a detected voltage ( u d,q ), a detected current ( i d,q ), and a detected electrical speed (ω e ) , a first motor parameter ( Ψ PM ) comprises a permanent magnet flux linkage, and a second motor parameter (R s ) comprises a phase resistance, characterized in that the first device and the fourth device comprise an artificial neuronal network (ANN) model performing the first and fourth parameter estimation algorithm , and the second device and the third device comprise a model reference adaptive control (MRAC) model performing the second and third parameter estimation algorithm . an input interface configured to receive an operating parameter ( u d,q , i d,q , ω e ) of an electric motor, a first device configured to perform a first parameter estimation algorithm estimating an estimated first motor parameter ( Ψ PM,1 ) based on the operating parameter ( u d,q , i d,q , ω e ) and on an initially determined second motor parameter ( R s,0 ) , and a second device configured to perform a second parameter estimation algorithm estimating an estimated second motor parameter ( R s,1 ) based on the operating parameter ( u d,q , i d,q , ω e ) and on an initially determined first motor parameter ( Ψ PM,0 ), wherein the equipment further comprises a third device configured to perform a third parameter estimation algorithm estimating a revised estimated second motor parameter ( R s , 2 ) based on the estimated first motor parameter ( Ψ PM,1 ) and on the operating parameter ( u d,q , i d,q , ω e ) , and a fourth device configured to perform a fourth parameter estimation algorithm estimating a revised estimated first motor parameter ( Ψ PM,2 ) based on the estimated second motor parameter ( R s,1 ) and on the operating parameter ( u d,q , i d,q , ω e ), wherein the operating parameter ( u d,q , i d,q , ω e ) comprises at least one of a detected voltage ( u d,q ), a detected current ( i d,q ), and a detected electrical speed (ω e ) , a first motor parameter ( Ψ PM ) comprises a permanent magnet flux linkage, and a second motor parameter (R s ) comprises a phase resistance, characterized in that the first device and the fourth device comprise an artificial neuronal network (ANN) model performing the first and fourth parameter estimation algorithm , and the second device and the third device comprise a model reference adaptive control (MRAC) model performing the second and third parameter estimation algorithm . <EOS>