A method for optimal speed and torque output of asynchronous motors for electric buses based on random forest regression algorithm
An asynchronous motor and random forest technology, which is applied in the direction of motor generator control, control of electromechanical brakes, control of electromechanical transmission devices, etc. The measured data is discontinuous, the current is adjusted accurately, and the effect of real-time response is realized.
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[0033] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.
[0034] To solve the above problems, such as figure 1 As shown, from the perspective of machine learning, the present invention models the VC control system based on the current ratio output model of the random forest regression algorithm, so that the excitation current and torque current for controlling the output speed and torque of the asynchronous motor are online predicted , to output the optimal current vector in real time to realize the optimal speed and torque output of the asynchronous motor. The main advantages are as follows: (1) The current ratio model based on the random forest regression algorithm can basically realize the synchronization of each system parameter input into the model with the output of the excitation current and torque current, and the current vector output response basically has no lag. (2) Avoid the formula oper...
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