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Stability of motion, turnability, mobility and fuel consumption of all-wheel drive terrain vehicles strongly depends on engine power distribution among the front and rear driving axles and then between the left and right wheels of each axle. This paper considers kinematic discrepancy, which characterizes the difference of the theoretical velocities of the front and rear wheels, as the main factor that influences power distribution among the driving axles/wheels of vehicles with positively locked front and rear axles. The paper presents a new algorithm which enables minimization of the kinematic discrepancy factor for the improvement of AWD terrain vehicle dynamics while keeping up with minimal power losses for tire slip. Three control modes associated with gear ratio control of the front and rear driving axles are derived to provide the required change in kinematic discrepancy. Computer simulation results are presented for different scenarios of terrain and road conditions.

This paper presents an innovative combined control using Model Predictive Control (MPC) to enhance the stability of automated vehicles. It integrates path tracking and vehicle stability control into a single controller to satisfy both objectives. The stability enhancement is achieved by computing two expected yaw rates based on the steering wheel angle and on lateral acceleration into the MPC model. The vehicle's stability is determined by comparing the two reference yaw rates to the actual one. Thus, the MPC controller prioritises path tracking or vehicle stability by actively varying the cost function weights depending on the vehicle states. Using two industrial standard manoeuvres, i.e. moose test and double lane change, we demonstrate a significant improvement in path tracking and vehicle stability of the proposed MPC over eight benchmark controllers in the high-fidelity simulation environment.