A multi-dimensional integrated vehicle-mounted magnetic levitation flywheel battery control system

Abstract

The invention provides a multi-dimensional integrated vehicle-mounted magnetic levitation flywheel battery control system, which belongs to the technical field of vehicle-mounted flywheel battery control. In the present invention, the current signal processed by the current regularization module is used as the input signal of the support vector machine displacement prediction module, the output signal of the support vector machine displacement prediction module, the output signal of the fuzzy PID cross feedback control module and the neural network inverse decoupling control module are accumulated and summed The signal processed by the coordinate system conversion module is used as the input signal of the improved zero-power control module, the displacement signal output by the support vector machine displacement prediction module, and the output signal of the improved zero-power control module are used as the input signal of the linear closed-loop controller, and the linear closed-loop controller The output is used as the input signal of the fuzzy PID cross feedback control module and the neural network inverse decoupling control module. The invention simplifies the complexity of the whole system, greatly improves the real-time response characteristics, can not only suppress the gyro effect, improve the stability, but also reduce energy consumption and cost.

Description

technical field [0001] The invention relates to the technical field of control of a vehicle-mounted magnetic levitation flywheel battery (also called a flywheel energy storage device) used for an electric vehicle, in particular to a vehicle-mounted magnetic levitation flywheel battery control system integrating low energy consumption, low cost, and high stability control. Background technique [0002] Vehicle-mounted magnetic levitation flywheel battery is a new mechatronic device based on magnetic levitation bearing technology. It breaks through the limitations of traditional chemical batteries and has the advantages of high energy storage density, high energy conversion rate, long service life, and no pollution. The stability control, energy consumption and cost of the flywheel rotor are the key factors affecting the popularization of the vehicle-mounted maglev flywheel battery. [0003] In terms of stability control: the driving state of the car itself and complex road co...

AI Technical Summary

Problems solved by technology

The parameter estimation method relies on the precise mathematical model of the system, which has high requirements for the design of the controller; the high-frequency signal injection method requires special signal processing technology to realize the displacement estimation; the sensorless control method based on the neural network uses the neural network The strong nonlinear mapping ability of the network realizes the self-detection of rotor displacement. Although this control method makes up for the shortcomings of the above two methods, the neural network currently has defects such as overfitting, easy to fall into local extremum, and structural design relying on experience.

The above three methods only consider low cost issues, and do not involve low energy consumption and stability issues

[0006] In addition, if the methods to solve the above problems are piled up in a control system in the form of decentralized modules, it will inevitably lead to a complex control system and affect the real-time response of the system. Still maintain high stability, low energy consumption and low cost running state control

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