A novel rotor position estimation approach for an 8/6 solid rotor switched reluctance motor

Switched reluctance motor (SRM) is becoming popular due to its simple construction, low manufacturing cost, ruggedness and fault-tolerant capability. In conventional switched reluctance motor (SRM), rotor is laminated. But in solid rotor switched reluctance motor (SRM), rotor is not laminated, and it is suitable for applications where rotors are immersed in water environment. A stationary can arrangement is introduced between stator and rotor. In this research, an 8/6 solid rotor switched reluctance motor which is used in reactivity control mechanisms of nuclear reactors is considered as test motor. As solid rotor switched reluctance motor is suitable for working in water environments in nuclear reactors, rotor position estimation is the topic of interest. A new approach which adopts two-phase excitation method is presented for rotor position estimation. Four different artificial neural networks (ANNs) with 2-5-5-1 structure are trained to estimate rotor position. The main advantage of this approach is to minimize the required number of voltage and current sensors. The validity of the new approach is verified through online comparison of estimated and actual rotor position.