Based on Embedded Technology to Real-Time Control for Analogous Active Suspension System

Conventional vehicle suspension system is mainly composed of coil springs and hydraulic dampers, and the elasticity coefficient K ad damping coefficient C are fixed values, so the traditional suspension system cannot adjust the suspension system according to different road conditions. Due to the varying road quality, many potholes, patches and manhole covers, and rainy climate, the comfort and maneuverability of driving are reduced. Therefore, this study proposes the application of embedded technology combined with road image to determine and control the class of Analogous Active Suspension System. In this study, the Analogous Active Suspension System is composed of air springs, proportional valve hydraulic dampers instead of traditional suspension system, and various sensors. For different types of uneven road surfaces such as potholes, speed bump, manhole covers, etc., the Controller Area Network (CAN bus) communication is used to transmit the road surface information to the vehicle embedded system, and then the control decision is calculated to adjust the corresponding air spring coefficients according to the corresponding conditions. At the same time, the optimal damping coefficients are calculated by using neural-like algorithms, so that the system can adjust the suspension parameters immediately according to the current road conditions to achieve better driving comfort and handling. Finally, the dynamic characteristics of the suspension system and the vehicle are investigated in a real vehicle dynamic test to optimize the control decision parameters to achieve the best driving comfort and to give the best driving safety.