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Promoting new energy vehicles (NEVs) is considered to be one of the most effective ways to solve the increasingly serious problems of energy security and environmental pollution. With the growing energy shortage and the worsening of environmental pollution, electric vehicle (EV), as a new energy vehicle driven by electric energy, has attracted more and more attention. Because of its small size, high efficiency, large overload capacity and fast response, the brushless electric motor has occupied an important position in the servo field and is an ideal choice for electric drive systems of electric vehicles. The control precision of PMSM depends on the precision of rotor position detection to a great extent. The traditional method of obtaining rotor position is realized by high resolution position sensors, such as resolver, photoelectric encoder. It can obtain the rotor flux position with high resolution accurately and in real time, but this method has high cost. In order to reduce the cost of rotor position detection, the sensorless control technology has been developed. The rotor position is estimated by detecting the variables such as current, voltage and motor parameters. However, the Control Algorithm is complex and requires high parameters, and it doesn't work at full speed. Computationally efficient design of interior permanent magnet (IPM) motor rotor features is investigated utilizing analytical methods. The rotating transformer and the high-frequency signal method independently detect the rotor position, the high-frequency signal method verifies the detection precision of the rotating transformer at low speed, and the high-frequency signal method rotor position detection system at high speed stops working, in the case of a rotating transformer fault, the high frequency signal method system supports the motor to drive at low speed in fault mode.
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