Page - 128 - in Maximum Tire-Road Friction Coefficient Estimation

7 Summary sensors of a vehicle equipped with electronic stability control (ESC), also require some information about vehicle and tire parameters. Thefirstchapter (Introduction)of this thesisdiscussedthesignificanceof the friction potential to enhance traffic safety. The influence of the road conditions on the number of accidents was shown, and possible traffic safety measures were discussed. Thereafter, the importance of the friction potential for ADAS and vehicle dynamic controls (VDC) were shown, with an emphasis on the requirements for an estimate of the friction poten- tial for selected applications. Finally, the AEB was selected as an exemplary application case to adapt the intervention strategy based on an estimate of the friction potential. Thesecondchapter (Estimation of the friction potential)presentedthemain factors that influence the friction potential, as well as the state of the art for existing estimation methods. After a brief definition of the friction potential, the basics of rubber physics and the relevant effects on the rotating wheel were discussed. An overview was given of the factors that influence the friction potential. Main effects (e.g. road surface, inter- mediary layers, tire’s vertical load and vehicle’s longitudinal velocity) were discussed in more detail. Next, there was a brief discussion of the wide variety of methods published in the research area of tire/road friction estimation, with a focus on vehicle-dynamics- basedmethods. Within theseapproaches, methodsusingaBayesianobserver framework such as the Kalman filter or the particle filter were emphasized. The third chapter (Vehicle model) comprisedadescriptionof thevehiclemodel that was used throughout this thesis for both the sensitivity analysis in Chapter 4 and (par- tially) for the observer model presented in Chapter 5. In a first step, the required model complexity was investigated in order to be able to model the tire/road contact as accu- rately as possible but keeping in mind the computational effort. Thus, the influence of the model complexity of certain sub-systems on the model accuracy was evaluated using a validated vehicle model with 14 degrees of freedom and certain driving manoeuvres. Based on the results of this investigation, a vehicle model with 7 degrees of freedom was then chosen, which was presented along with the tire model used. Pitch and roll motion are neglected within the chosen vehicle model, but tire load distribution during braking, accelerating and cornering is included by considering the horizontal accelerations in the vehicle’s COG. In the fourth chapter (Sensitivity analysis), a mathematical solution to the problem 128