Research on control of damped adjustable semi-active suspension system based on LSTM neural network
Based on a high-speed solenoid valve type three-stage damping adjustable shock absorber,its external characteristic curve was measured by the test bench.Compared with CDC shock absorber,it had similar adjustment range and lower manufacturing cost,and had the potential to be popularized on a large scale.Then the non-parametric model was established by BP neural network,which could be used for suspension dynamics inverse analysis well compared with the test.A seven-degree-of-freedom simulation model of the vehicle equipped with the shock absorber was built using MATLAB/Simulink.The vehicle unsprung mass acceleration response was obtained by random four-wheel excitation input on the road surface,and the LSTM neural network was trained.The verification set verified that the neural network could effectively identify the road surface grade.Finally,LSTM neural network and adjustable damping damper were used to carry out random road surface and rapid acceleration and deceleration experiments of real cars.It was proved that compared with traditional passive suspension,the LSTM neural network controlled adjustable damping damper suspension system could effectively improve the operating stability and ride comfort of vehicles.
NETL
NSTL
万方数据
维普
