This paper presents the design and validation of a differential braking controller for sport utility vehicles (SUVs) using driver-in-the-loop real-time simulations. SUVs are constructed with high ground clearance, which is the main reason for their high rollover rate. A nonlinear 3 degrees-of-freedom (DOF) SUV model with the Dugoff’s tire model is generated to design a differential braking controller. The desired states will be decided using a 2-DOF bicycle model and the automated lane-keeping control results derived from the vehicle velocity and the curvature of the road to negotiate. Actual vehicle states, observed from the nonlinear model, may deviate from the desired ones. A nonlinear robust controller, namely sliding model controller (SMC), is designed to minimize the state error so as to improve the performance measures, e.g., yaw stability. The proposed controller constructed in Labview software is integrated with a virtual SUV developed in CarSim package for co-simulations. The effectiveness of the controller is first investigated using the emulated sine-with-dwell maneuver specified in FMVSS 126. The overall SUV performance depends not only on the control scheme, but on its interaction with the human driver. To investigate the interaction of the driver and the controller, the dynamics of the overall system is simulated using driver-software-in-the-loop real-time simulations (DSIL) under a double-line-change (DLC) maneuver emulated on the DSIL platform in the Multidisciplinary Vehicle Systems Design Laboratory (MVSDL) at the University of Ontario Institute of Technology (UOIT). The simulations show that, even equipped with the electronic stability control (ESC) system, the driver still plays an important role in the vehicle dynamics. The simulations demonstrate the effectiveness of the proposed differential braking controller for enhancing the lateral stability of the SUV. Furthermore, the research discloses important interactions of the driver and the ESC system, and a driver’s training program is highly recommended.

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