| Control Strategy for Automobile Inertia Brake Tester Based on AC drive mainly includes electric inertia system and Pneumatic Force Servo system. Electric inertia control technology and Pneumatic Force Servo control technology are the key technologies of the Automobile Inertia Brake Tester; they are also used in the simulation of inertia loads and dynamic loading system with a wide range of applications.Currently, Automobile Inertia Brake Tester, at home and abroad, commonly used mechanical inertia, with a large inertia of the rotating disk of inertia to simulate vehicle straight-line movement of inertia, but there are many drawbacks. Some experts use "electric inertia" to simulate Mechanical Inertia. Although there are many scholars study the electrical inertia technology, but they have a common drawback: System only control speed or torque single variable. But the electric inertia control system is a nonlinear, multivariable system. Variables may affect system performance. This paper considers multiple variable impact, and control the Automobile Inertia Brake Tester based on BP neural networks multivariable control in order to achieve the purpose of simulating mechanical inertia system by using motor.In Automobile Inertia Brake tester, Pneumatic Force Servo system provides braking force. Although pneumatic technology has advantages like low-energy-consuming, high-efficient, non-polluted, due to the factors of gas compressibility, nonlinear valve port flows, friction cause system instability, especially friction causes "low-speed stick-slip", affect system control performance. This paper probes to the low speed stick-slip nonlinear characteristics caused by the friction, proposes a new friction compensation way based LuGre model, identifying the parameters of LuGre model with Particle swarm optimization, and design the single neuron PID algorithm control to control the Pneumatic Force Servo system.This paper analyzed the electrical inertia and pneumatic force servo system, corresponding mathematical model, introduces AC motor vector control and SVPWM control algorithm, designs the control algorithm for electric inertia control based on BP neural network, simulates the electric inertia control system, to verification control algorithm, and shows the comparison curve of single variable and multi-variable control; designed single neuron PID controller for pneumatic force servo system, builds simulation models to verify the validity of control, and shows the simulation results based on friction compensation; designs a real system to verify the Control Algorithms of electronic inertia control system and Pneumatic Force Servo, TMS320F2812DSP is the core control unit, analyses the requirements for the system, designed the hardware and software, and shows the test curve. |
