Control method of vehicle-mounted flywheel battery radial suspension support system based on working condition

Abstract

The invention discloses a control method of a vehicle-mounted flywheel battery radial suspension support system based on working conditions. The method includes: 1, taking a magnetic bearing system asa controlled object, and establishing a rotor dynamic model and a system state equation of the magnetic bearing system under different working conditions of the flywheel battery by using a dynamic test and a dynamic simulation; 2, subtracting the output x of the magnetic bear system from the target air gap x* to obtain the air gap error ex, and designing a sliding mode switch surface and a sliding mode controller including an equivalent control and a switching control based on the air gap error ex, a dynamic model and a state equation, and obtaining the sliding mode control law; 3, forming afuzzy RBF neural network by combining fuzzy control and an RBF neural network, and adjusting the constant velocity gain [epsilon] and exponential gain k of switching control by using the fuzzy RBF neural network; 4, adding a current controller, converting the output of the fuzzy sliding mode controller into the given current value of the current inner loop, and controlling the chopper to adjust the magnitude of the control current of the maglev bearing system. The control method improves the transient response rate of the current, and outputs the control current [delta] i of the maglev bearingsystem by the chopper.

Description

technical field [0001] The invention belongs to the technical field of electric drive control equipment, and in particular relates to a fuzzy neural network dynamic sliding mode control method for a vehicle-mounted flywheel battery radial suspension support system based on working conditions. Background technique [0002] The flywheel battery system is an energy storage device for electromechanical energy conversion, which has the advantages of high energy storage density, strong adaptability, wide application range, high efficiency, and no pollution. A new way is provided. Since the rotor in the flywheel system needs to rotate at a high speed to store energy, the requirements for the support system are very strict. In addition to bearing the weight of the flywheel rotor, other factors such as the gyroscopic force and centrifugal force of the flywheel must also be considered. Because of the high rigidity of the mechanical bearing support and the fixed position of the bearin...

AI Technical Summary

Problems solved by technology

[0004] The invention proposes a fuzzy neural network dynamic sliding mode control method based on working conditions for the radial suspension support system of the vehicle-mounted flywheel battery, which solves the problem of the system runaway caused by the disturbance caused by the rotor rotation of the flywheel battery and the sudden change of load under different working conditions problem, and ensure the robustness and anti-interference performance of the vehicle flywheel battery radial suspension support system, overcome the chattering problem of the actuator, and effectively improve the various control objectives of the vehicle flywheel battery radial suspension support system

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