Model Free Control (MFC) is a novel strategy to handle nonlinear and unknown dynamices in the control of vehicle systems. The method is based on an ultra-local model, which approximates the dynamical behavior of the system for a short time period. Although this algorithm has already been successfully applied to several control problems, there are some open questions, related to its implementation and tuning issues. This paper proposes a new control parameter tuning method on the ultra-local model for achieving improved trajectory tracking performances with MFC. A novel formulation of the MFC structure, i.e., an error-based ultra-local model, for tuning purposes is presented. Moreover, the control parameter tuning method based on data-driven tools for achieving optimal control parameter selection is proposed. The effectiveness of the proposed control strategy through a trajectory tracking problem using high-fidelity vehicle dynamics simulation software is illustrated.