Semi-active and active suspensions improves the maneuverability, comfort and stability of intelligent vehicles. Closed loop controllers for the active/semi-active suspension systems improve their performance as the uncertainty level decrease. In this article we present a methodology to estimate the main components of the suspension system with a single and integrated observer (virtual sensor). The proposed observer (an embedded algorithm) provides the system state, the road profile, the normal tire-ground forces and the load transfer without requiring expensive sensors. The sensors required are standard in commercial vehicles with actuated or semi-actuated suspension. The observer structure is based on Kalman filter technique due to its simplicity and robustness. The vehicle dynamics is fully integrated with the quarter-car suspension model in order to boost the system observability, its response and constraining the estimation error. The proposal is validated at different operation points using a high fidelity automotive simulator, OKTAL-SCANeR™studio-Callas® and experimental data.