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This paper proposes a novel optimization method that allows a reduction in the pollutant emission of diesel engines during transient operation. The key idea is to synthesize optimal actuator commands using reliable models of the engine system and powerful numerical optimization methods. The engine model includes a mean-value engine model for the dynamics of the gas paths, including the turbocharger of the fuel injection, and of the torque generation. The pollutant formation is modeled using an e.xtended quasi-static modeling approach. The optimization substantially changes the input signals, such that the engine model is enabled to extrapolate all relevant outputs beyond the regular operating area. A feedforward controller for the injected fuel mass is used to eliminate the nonlinear path constraints during the optimization. The model is validated using e.xperimental data obtained on a transient engine test bench, A direct single shooting method is found to be most effective for the numerical optimization. The results show a significatit potential for reducing the pollutant emissions during transient operation of the engine. The optimized input ttajectories derived assist the design of sophisticated engine control .•systems.

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This paper presents a novel control-oriented model of the raw emissions of diesel engines. An extended quasistationary approach is developed where some engine process variables, such as combustion or cylinder charge characteristics, are used as inputs. These inputs are chosen by a selection algorithm that is based on genetic-programming techniques. Based on the selected inputs, a hybrid symbolic regression algorithm generates the adequate nonlinear structure of the emission model. With this approach, the model identification efforts can be reduced significantly. Although this symbolic regression model requires fewer than eight parameters to be identified, it provides results comparable to those obtained with artificial neural networks. The symbolic regression model is capable of predicting the behavior of the engine in operating points not used for the model parametrization, and it can be adapted easily to other engine classes. Results from experiments under steady-state and transient operating conditions are used to show the accuracy of the presented model. Possible applications of this model are the optimization of the engine system operation strategy and the derivation of virtual sensor designs.