A stochastic approach for the optimization of open-loop engine control systems. (English) Zbl 0726.90094
Summary: The operation of sensors and actuators in engine control systems is always affected by errors, which are stochastic in nature. In this paper it is shown that, because of the nonlinear interactions between engine performance and control laws in an open-loop engine control systems, these errors can give rise to unexpected deviations of control variables, fuel consumption and emissions from the optimal values, which are not predictable in an elementary way.
A model for vehicle performance evaluation on a driving cycle is presented, which provides the expected values of fuel consumption and emissions in the case of stochastic errors in sensors and actuators, utilizing only steady-state engine data.
The stochastic model is utilized to obtain the optimal control laws; the resultant nonlinear constrained minimization problem is solved by an augmented Lagrangian approach, using a quasi-Newton technique. The results of the stochastic optimization always indicate that significant reductions in performance degradation may be achieved with respect to the solutions provided by the classical deterministic approach.
A model for vehicle performance evaluation on a driving cycle is presented, which provides the expected values of fuel consumption and emissions in the case of stochastic errors in sensors and actuators, utilizing only steady-state engine data.
The stochastic model is utilized to obtain the optimal control laws; the resultant nonlinear constrained minimization problem is solved by an augmented Lagrangian approach, using a quasi-Newton technique. The results of the stochastic optimization always indicate that significant reductions in performance degradation may be achieved with respect to the solutions provided by the classical deterministic approach.
MSC:
| 90C90 | Applications of mathematical programming |
| 90C15 | Stochastic programming |
| 90B90 | Case-oriented studies in operations research |
| 49N99 | Miscellaneous topics in calculus of variations and optimal control |
Keywords:
probabilistic constraints; engine control systems; vehicle performance evaluation; fuel consumption; stochastic errors in sensors and actuatorsReferences:
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