Torque optimization method for electric vehicles based on data-driven predictive control
An electric vehicle, data-driven technology, applied in electric vehicles, control drive, power management, etc., can solve the problems of complex mechanism model of torque optimization control system, inability to optimize torque distribution design, modeling difficulties, etc., to avoid mechanism modeling , the effect of reducing the amount of calculation and avoiding the problem of model error
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[0061] The research method of the present invention is based on data-driven model predictive control, comprising the following steps:
[0062] Firstly, appropriate excitation data is designed for the dynamic characteristics of the system to ensure sufficient excitation of the system; secondly, the input and output data obtained by the excitation are used to construct the predictive output equation of the system; then, the actuators of the motor, battery pack and brake are considered With hard constraints, the model predictive control algorithm is used to construct the cost function of torque optimization control; finally, by solving the optimal problem corresponding to the cost function, the control input is obtained and acts on the system, so as to realize the control of the system.
[0063] In order to solve the problems of the technologies described above, the present invention is achieved by adopting the following technical solutions:
[0064] The electric vehicle torque o...
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