Abstract

In this paper a mean value model of a turbocharged diesel engine air path with an electric wastegate (WG) and an exhaust throttle valve (ETV) is presented. The model is designed with regard to system analysis, controller design, and real-time feasibility. That means, care is taken to ensure that the model contains the relevant dynamics on the one hand and that the requirements for computing power and memory (RAM) are kept as low as possible on the other hand. New approaches for modeling the ETV and the exhaust gas temperature are presented. The latter is formulated via an artificial neural network (ANN) computed outside the model. The ANN is integrated into the model in such a way that the differentiation of the model still provides meaningful results for controller design. Thus, this model may also be used for online computation of nonlinear model predictive controllers (MPC) or nonlinear state observers. The parameters of the model are determined using GT-Power simulation data covering the entire working range of the engine. Only measured variables that are also accessible on the engine test bench are used. All optimization problems to be solved within the parameter determination are presented. It is analyzed which sensors are suitable to support the model in an implementation on an electronic control unit (ECU), and the effect without and with sensor correction is shown in a dynamic test bench measurement. Furthermore, the properties of the generated C code are presented, which are the number of mathematical operations, the runtimes, and the stack size. An evaluation of the real time capability is given based on eigenvalue analyses and the properties of the C code .

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