Abstract
AbstractThe fuel economy is critical in the operation of commercial vehicles. An MPC-based predictive cruise control (PCC) scheme with multiple objectives is used to control the longitudinal behavior of the vehicle, which can effectively utilize recorded road slope to solve the optimal control to achieve better performance than PID-Based cruise control. The fuel economy of different driving tasks with different target speeds, loads, and roads are simulated on TruckSim. In addition, the effects of the prediction horizon length on fuel-saving potential are analyzed. The simulation results showed that the proposed PCC algorithm can effectively improve the fuel economy and meet the desired travel time for different cruising tasks irrespective of the vehicle load. The fuel-saving potential increases with a longer prediction horizon, reaching an average of 3.43%.KeywordsAutonomous vehicleFuel economyPredictive cruise controlModel predictive control
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