Adaptive model predictive control for co-ordination of compression and friction brakes in heavy duty vehicles

Abstract

In this paper, an adaptive model predictive control scheme is designed for speed control of heavy vehicles. The controller co-ordinates use of compression brakes and friction brakes on downhill slopes. Moreover, the model predictive controller takes the actuator constraints into account. A recursive least square scheme with forgetting is used in parallel with the controller to update the estimates of vehicle mass and road grade. The adaptation improved the model predictive controller. Also online estimation of the road grade enhanced the closed-loop performance further by contributing through feedforward control. Simulations of realistic driving scenarios with a validated longitudinal vehicle model are used throughout this paper to illustrate the benefits of co-ordinating the two braking mechanisms and influence of unknown vehicle mass and road grade.

Model Predictive Braking Control for Heavy-Duty Commercial Vehicles Considering Response Delay of Air-Brake

“…MPC takes constraints explicitly into optimization problems, and there are research treating the braking torque limit (4) or the road width (5) as constraints. Besides, the following characteristics of HDCVs have been considered in MPC: the time delay due to actuators, sensors, and communication networks in HDCVs platoons (6) , roll-over prevention by the high center of gravity (7) ~ (10) , and vehicle model uncertainty (11) (12) .…”