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To improve traditional heavy commercial vehicles performance, this paper introduces a novel hydraulic hub-motor auxiliary system, which could achieve auxiliary driving and auxiliary braking function. Firstly, the system configuration and operation modes are described. In order to achieve coordinating control and distribution of the engine power between mechanical and hydraulic paths, the paper proposes an optimal algorithm based on enhance of vehicle slip efficiency and the results show that displacement of hydraulic variable pump relates with the transmission gear ratio. And then the hydraulic pump displacement controller is designed, in which the feedforward and feedback strategy is adopted. Considering the characteristics of hydraulic hub-motor auxiliary system, a layered auxiliary drive control strategy is proposed in the paper, which includes signal layers, core control layers and executive layers.

With the aim of addressing the problem of inconsistency of the traditional proportion integration (PI) driver model with the actual driving behavior, a longitudinal driver model based on the elastic net regression (ENR) and adaptive network fuzzy inference system (ANFIS) method is proposed. First, longitudinal driving behavior data are collected through bench tests to extract the characteristic parameters that affect driving behavior. A quadratic regression model is established after considering the nonlinear characteristics of the driver behavior. The multi-collinear problem of high-dimensional variables in the regression model is solved by the ENR method, and the parameters with significant influence on driving behavior selected. A longitudinal driver model of ANFIS was established with the selected characteristic parameters as input. Finally, the validity of the model is verified by comparing it with the PI and ENR driver models.