Railway traction vehicles transfer forces between wheels and rails through an adhesion coefficient. The adhesion coefficient value can decrease abruptly during the train run. Therefore, the wheels can simply gain high value of the wheels slip velocity. Thus, the vehicles are equipped with slip controllers for this case. During the past decades, many types of slip control strategies were developed, and the new methods are also developed today. Some perspective methods are based on an estimation of the adhesion coefficient or an adhesion force. However, correct operation of these methods is not guaranteed in all cases. Moreover, these methods have some weakness that can decrease their efficiency. Therefore, a novel method based on the adhesion condition estimation is presented in this paper. The adhesion condition is estimated by an unscented Kalman filter. When the method is connected to a controller, it is possible to eliminate the rising wheel slip velocity at its beginning and limit it to the appropriate value. The output of the method is directly used as an input of the controller without any additional calculation as it is used in traditional methods. The input signal does not need any additional filtration, and the method does not require information about the actual train velocity for its proper work. The verification of the method is done with the measured data that were measured on a freight train hauled by an electric locomotive. This paper also presents simulation results of the method with a controller based on the locomotive mathematical model.