A performance analysis of automotive semi-active suspension control algorithms was realized. Three on/off control strategies were tested in a quarter of vehicle model: hybrid Sky Hook-Ground Hook, hybrid Mix-1-Sensor and Frequency Estimation-Based controller. A commercial Magneto-Rheological damper was modeled by using an Artificial Neural Network approach. The automotive semi-active suspension was implemented in a commercial Controller Area Network system; and the control algorithms were implemented in a micro-controller system with comfort and road holding as main goals. Early results show the feasibility of this application.