Research on the real-time identification approach of longitudinal road slope and maximum road friction coefficient

Real-time knowledge of maximum road friction coefficient and road slope is crucial for active vehicle control systems. Most recent researches mainly assume that the road slope is constant and the influence on the identification of the maximum road friction coefficient is not considered. In this paper, the IMM Kalman filter method for the identification of road longitudinal slope is developed. Considering the axle load transfer caused by the road slope, the current road type is recognised by comparing the samples of the estimated instantaneous road friction coefficient with each standard road, then the maximum road friction coefficient can be easily determined by an online lookup table. Finally, experimental tests on the braking system hardware-in-the-loop test rig driven by the driving simulator are conducted. The results demonstrate that the identification approach can identify the current road slope and maximum road friction coefficient with good adaptability to various vehicle conditions.