As a typical parameter of the road-vehicle interface, the road friction potential acts an important factor that governs the vehicle motion states under certain maneuvering input, which makes the prior knowledge of maximum road friction capacity crucial to the vehicle stability control systems. Since the direct measure of the road friction potential is expensive for vehicle active safety system, the evaluation of this variable by cost effective method is becoming a hot issue all these years. A ‘wheel slip based’ maximum road friction coefficient estimation method based on a modified Dugoff tire model for distributed drive electric vehicles is proposed in this paper. It aims to evaluate the road friction potential with vehicle and wheel dynamics analyzing by using standard sensors equipped on production vehicle, and fully take the advantage of distributed EV that the wheel drive torque and rolling speed can be obtained accurately. A modified Dugoff tire model is built and analyzed, which acts as the fundamental of the road friction potential estimation algorithm. Newton-Raphson method and LMS method is introduced to estimate the maximum friction coefficient through the tire model. The simulation and a vehicle test show that this method has short convergence time and higher estimation accuracy. Numerical results verify that the estimator designed is capable of estimating tire-road friction coefficient with reasonable accuracy, and the algorithm proposed has good robustness and wide applicability under various driving conditions.