Servo Problem within Fuel Consumption Optimization

Abstract

The presented paper deals with a problem of fuel consumption optimization. Today's automotive industry solves this problem mainly via various conceptual approaches (hybrid and electric vehicles). However, it leads to high initial cost of a vehicle. This paper focuses on fuel economy for conventional vehicles. For this aim, recursive algorithms of adaptive optimal quadratic control under Bayesian methodology are used. A stochastic servo problem, including setpoint tracking, is a part of the considered adaptive control design. In this paper, fuel consumption and speed of a driven vehicle are the controlled variables, where the first one is to be optimized and the second one is pushed to track its set-point. This set-point is a recommended roaddependent speed. Experiments with real data measured on a driven vehicle are provided.

Optimization of driving based on currently measured data

“…However, it should be noted that even very slight changes in penalizations can bring results in the form of reducing fuel consumption or better preserving the recommended speed. The presented results also confirm the summary obtained using other control approaches within this project [11], [12]. …”

“…Using the setpoint pre-programming, we decided to apply it to the specific task of optimization of fuel consumption. Within the current project the control algorithms based on the fully probabilistic design [10] have been already exploited [11] as well its combination with a PID controller [12]. Here we focus on application of dynamic programming with preprogrammed setpoints.…”