Predictive Powertrain Control for Heavy Duty Trucks

Abstract A truck driver controls his vehicle with the objective of maintaining a desired velocity while keeping the fuel consumption as low as possible. In order to achieve these goals he continuously estimates oncoming operation points of thepowertrain and chooses the inputs (driving torque, brake level, gear) in an optimal manner based on this estimation. A navigation system combined with a 3D digital road map is able to provide information about the roadway not only for the current position but also for a coming distance if the route is known. By imitating the driver, the Model Predictive Control method is used to apply this information for the implementation of a predictive gearshift program and a predictive cruise controller. Thereby in both systems the input variables are determined by the successive solution of discrete/continuous optimal control problems. The present paper first points out the idea of a predictive powertrain control for a heavy duty truck, followed by the description of its algorithmic realization.