Variable transmission ratio strategy for improving brake feeling based on driver’s target braking strength

Abstract

Due to the absence of vacuum sources for electric vehicle, the vacuum booster is replaced by electronic brake boosting (EBB) system. In order to improve the driver’s brake feeling based on EBB, this work fully exploits the flexible and variable power-assisted characteristics, and designs different transmission ratios according to the driver’s target braking strength. To identify the driver’s braking strength, an improved radial basis function (IRBF) neural network, combining self-organization method and supervised learning method, is proposed to establish the relationship between the driver’s braking strength and the characteristic parameters. Based on this, the variable transmission ratio strategy is designed, and its main optimized parameters are optimized by means of multi-objective optimization algorithm to provide the driver with a satisfactory brake feeling. The strategies under fixed and variable transmission ratios are simulated and analyzed in low-speed with gentle-brake and high-speed with emergency-brake. The simulation results show that, compared with the fixed transmission ratio, the proposed variable transmission ratio shows excellent performances in both brake feeling and brake safety.