Double Optimization of Fuel Consumption and Speed Tracking

This paper presents automatic fuel consumption optimization with simultaneous keeping the recommended vehicle's speed. These tasks are closely related since a simple minimization of fuel consumption leads to stopping a vehicle. The proposed “double” optimization is performed online using combination of two controllers. The first of them is based on fully probabilistic design (FPD) under Bayesian methodology. It optimizes the “driver-vehicle” closed loop with the aim to save fuel and keep the recommended speed, using externally given setpoints. Optimized values serve as setpoints for PID controller, which provides necessary setpoint tracking. Research is performed in collaboration with Škoda auto (www.skoda-auto.com).