Heavy Vehicle Braking using Friction Estimation for Controller Optimization

Abstract

In this thesis project, brake performance of heavy vehicles is improved by the development of new wheel-based functions for a longitudinal slip control braking system using novel Fast Acting Braking Valves (FABVs). To achieve this goal, Volvo Trucks' vehicle dynamics model has been extended to incorporate the FABV system. After validating the updated model with experimental data, a slip-slope based recursive least squares friction estimation algorithm has been implemented. Using information about the tire-road friction coefficient, the sliding mode slip controller has been made adaptive to different road surfaces by implementing a frictiondependent reference slip signal and switching gain for the sliding mode controller. This switching gain is further optimized by means of a novel on-line optimization algorithm. Simulations show that the on-line friction estimation converges close to the reference friction level within one second for hard braking. Furthermore, using this information for the optimized controller has resulted in reduction of braking distance on most road surfaces of up to 20 percent, as well as in most cases a reduction in air usage.