Dynamic Mapping of Diesel Engine through System Identification

Henningsson, Maria; Ekholm, Kent; Strandh, Petter; Tunestål, Per; Johansson, Rolf

doi:10.1007/978-1-4471-2221-0_13

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…Hence, it is essential to convert the detailed air path model into a simplified mathematical model that is able to accurately capture the relationship between the manipulated variables and manipulated objects. 37 The internal prediction model is a state-space model, which is a kind of data-driven linear model. The governing equations for the state-space model are listed in equations (30) and (31).…”

Section: Tmpc Controller Design Frameworkmentioning

confidence: 99%

Tuneable model predictive control of a turbocharged diesel engine with dual loop exhaust gas recirculation

Zhang

2017

Proceedings of the Institution of Mechanical Engineers, Part D:

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The air path of a turbocharged diesel engine is a multi-input multi-output (MIMO) system with strong nonlinearity, coupling effect, delay and actuator constraints. This makes the design and tuning of the controller complex. In this paper, a tuneable model predictive control (TMPC) controller for a diesel engine's air path with dual loop exhaust gas recirculation (DLEGR) is presented. The objective is to regulate the intake manifold pressure and exhaust gas recirculation (EGR) mass flow in each loop to meet the time-varying setpoints through coordinated control of the variable geometry turbocharger (VGT) and EGR valves. The TMPC controller adopts the design framework of an MPC controller. This controller is also able to provide a map-based switching scheme for the local controller and the controller's weightings. A comparison between the TMPC controller and a conventional PID controller is conducted on a validated real-time engine model. The simulation results show that the TMPC controller achieves lower overshoot, faster response and a shorter settling time on the manipulated objects. These improvements are beneficial for obtaining lower fuel consumption. In order to test the capability of the TMPC controller, it is validated on a hardware in the loop (HIL) platform. The results show that the agreement between the simulation and the actual ECU's response is good.

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Section: Tmpc Controller Design Frameworkmentioning

confidence: 99%

Tuneable model predictive control of a turbocharged diesel engine with dual loop exhaust gas recirculation

Zhang

2017

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…Henningsson et al [13] presented a linear state-space model for the dynamics of a six-cylinder heavy-duty engine over a range of operating points. Fuel injection duration, fuel injection timing, exhaust gas recirculation (EGR) and variable geometry turbo (VGT) are considered as inputs, indicated mean effective pressure, combustion phasing, peak pressure derivative, NOx and soot emissions are modeled as outputs.…”

Section: Introductionmentioning

confidence: 99%

Predicting NOx emissions in diesel engines via sigmoid NARX models using a new experiment design for combustion identification

et al. 2019

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Diesel engines are still widely used in heavy-duty engine industry because of their high energy conversion efficiency. In recent decades, governmental institutions limit the maximum acceptable hazardous emissions of diesel engines by stringent international regulations, which enforces engine manufacturers to find a solution for reducing the emissions while keeping the power requirements.A reliable model of the diesel engine combustion process can be quite useful to search for the best engine operating conditions. In this study, nonlinear modeling of a heavy-duty diesel engine NOx emission formation is presented. As a new experiment design, air-path and fuel-path input channels were excited by chirp signals where the frequency profile of each channel is different in terms of the number and the direction of the sweeps. This method is proposed as an alternative to the steadystate experiment design based modeling approach to substantially reduce testing time and improve modeling accuracy in transient operating conditions. Sigmoid based nonlinear autoregressive with exogenous input (NARX) model is employed to predict NOx emissions with given input set under both steady-state and transient cycles. Models for different values of parameters are generated to analyze the sensitivity to parameter changes and a parameter selection method using an easy-tointerpret map is proposed to find the best modeling parameters. Experimental results show that the steady-state and the transient validation accuracies for the majority of the obtained models are higher than 80% and 70%, respectively.

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