Minimum Fuel Consumption Strategy in Autonomous Adaptive Cruise Control Scenarios

Fuel consumption is a crucial challenge for ACC (Adaptive Cruise Control) scenarios. This paper focuses on a synthesized controller of ACC based on a PnG (Pulse-and-Gliding) strategy to reduce fuel consumption in a car-following situation. A switching logic module is proposed for real-time control. A gear shifting algorithm and braking logic are added to the controller concerning the real following situation and structure of powertrain. Simulations are implemented in Matlab/Simulink and the results demonstrate that, compared with a MPC (Model Predictive Control) based benchmark controller, the synthesized controller could save fuel up to 14.5%. The significant fuel saving attributes to keeping the working point at or around at the best fuel economy point of engine. The algorithm could be implemented to some heavy commercial vehicles.