Steady-State and Transient Operations of a Euro VI 3.0L HD Diesel Engine with Innovative Model-Based and Pressure-Based Combustion Control Techniques

2017 ◽  
Vol 10 (3) ◽  
pp. 1080-1092 ◽  
Author(s):  
Ezio Spessa ◽  
Stefano D'Ambrosio ◽  
Daniele Iemmolo ◽  
Alessandro Mancarella ◽  
Roberto Vitolo ◽  
...  
Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3423 ◽  
Author(s):  
Hu ◽  
d’Ambrosio ◽  
Finesso ◽  
Manelli ◽  
Marzano ◽  
...  

A comparison of four different control-oriented models has been carried out in this paper for the simulation of the main combustion metrics in diesel engines, i.e., combustion phasing, peak firing pressure, and brake mean effective pressure. The aim of the investigation has been to understand the potential of each approach in view of their implementation in the engine control unit (ECU) for onboard combustion control applications. The four developed control-oriented models, namely the baseline physics-based model, the artificial neural network (ANN) physics-based model, the semi-empirical model, and direct ANN model, have been assessed and compared under steady-state conditions and over the Worldwide Harmonized Heavy-duty Transient Cycle (WHTC) for a Euro VI FPT F1C 3.0 L diesel engine. Moreover, a new procedure has been introduced for the selection of the input parameters. The direct ANN model has shown the best accuracy in the estimation of the combustion metrics under both steady-state/transient operating conditions, since the root mean square errors are of the order of 0.25/1.1 deg, 0.85/9.6 bar, and 0.071/0.7 bar for combustion phasing, peak firing pressure, and brake mean effective pressure, respectively. Moreover, it requires the least computational time, that is, less than 50 s when the model is run on a rapid prototyping device. Therefore, it can be considered the best candidate for model-based combustion control applications.


2013 ◽  
Vol 46 (21) ◽  
pp. 95-100 ◽  
Author(s):  
Hiroya Sahara ◽  
Yoshie Kakuda ◽  
Sang-kyu Kim ◽  
Daisuke Shimo ◽  
Keiji Maruyama ◽  
...  

Author(s):  
Ahmed Al-Durra ◽  
Marcello Canova ◽  
Stephen Yurkovich

Cylinder pressure is one of the most important parameters characterizing the combustion process in an internal combustion engine. The recent developments in engine control technologies suggest the use of cylinder pressure as a feedback signal for closed-loop combustion control. However, the sensors measuring in-cylinder pressure are typically subject to noise and offset issues, requiring signal processing methods to be applied to obtain a sufficiently accurate pressure trace. The signal conditioning implies a considerable computational burden, which ultimately limits the use of cylinder pressure sensing to laboratory testing, where the signal can be processed off-line. In order to enable closed-loop combustion control through cylinder pressure feedback, a real-time algorithm that extracts the pressure signal from the in-cylinder sensor is proposed in this study. The algorithm is based on a crank-angle based engine combustion of that predicts the in-cylinder pressure from the definition of a burn rate function. The model is then adapted to model-based estimation by applying an extended Kalman filter in conjunction with a recursive least-squares estimation scheme. The estimator is tested on a high-fidelity diesel engine simulator as well as on experimental data obtained at various operating conditions. The results obtained show the effectiveness of the estimator in reconstructing the cylinder pressure on a crank-angle basis and in rejecting measurement noise and modeling errors. Furthermore, a comparative study with a conventional signal processing method shows the advantage of using the derived estimator, especially in the presence of high signal noise (as frequently happens with low-cost sensors).


Author(s):  
A A Stotsky

The time and cost associated with running long-term tests to acquire data on the soot percentage in the oil of a diesel engine necessitate the development of a new method for a model-based prediction of the soot accumulation performance. A new method for a model-based prediction of the soot percentage for a vehicle that sequentially executes a number of taxi cycles is proposed. The method is based on the steady-state soot accumulation rate measurements that are made in the engine test cell, and is used for a relative soot percentage judgement and selection of the most suitable data set among several candidates. The method provides significant savings with respect to the direct long-term soot percentage measurements on a vehicle.


Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 460 ◽  
Author(s):  
Roberto Finesso ◽  
Gilles Hardy ◽  
Alessandro Mancarella ◽  
Omar Marello ◽  
Antonio Mittica ◽  
...  

A real-time combustion model was assessed and applied to simulate BMEP (Brake Mean Effective Pressure) and NOx (Nitrogen Oxide) emissions in an 11.0 L FPT Cursor 11 diesel engine for heavy-duty applications. The activity was carried out in the frame of the IMPERIUM H2020 EU Project. The developed model was used as a starting base to derive a model-based combustion controller, which is able to control indicated mean effective pressure and NOx emissions by acting on the injected fuel quantity and main injection timing. The combustion model was tested and assessed at steady-state conditions and in transient operation over several load ramps. The average root mean square error of the model is of the order of 110 ppm for the NOx simulation and of 0.3 bar for the BMEP simulation Moreover, a statistical robustness analysis was performed on the basis of the expected input parameter deviations, and a calibration sensitivity analysis was carried out, which showed that the accuracy is almost unaffected when reducing the calibration dataset by about 80%. The model was also tested on a rapid prototyping device and it was verified that it features real-time capability, since the computational time is of the order of 300–400 µs. Finally, the basic functionality of the model-based combustion controller was tested offline at steady-state conditions.


2020 ◽  
Vol 140 (4) ◽  
pp. 272-280
Author(s):  
Wataru Ohnishi ◽  
Hiroshi Fujimoto ◽  
Koichi Sakata

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1107
Author(s):  
Stefano d’Ambrosio ◽  
Roberto Finesso ◽  
Gilles Hardy ◽  
Andrea Manelli ◽  
Alessandro Mancarella ◽  
...  

In the present paper, a model-based controller of engine torque and engine-out Nitrogen oxide (NOx) emissions, which was previously developed and tested by means of offline simulations, has been validated on a FPT F1C 3.0 L diesel engine by means of rapid prototyping. With reference to the previous version, a new NOx model has been implemented to improve robustness in terms of NOx prediction. The experimental tests have confirmed the basic functionality of the controller in transient conditions, over different load ramps at fixed engine speeds, over which the average RMSE (Root Mean Square Error) values for the control of NOx emissions were of the order of 55–90 ppm, while the average RMSE values for the control of brake mean effective pressure (BMEP) were of the order of 0.25–0.39 bar. However, the test results also highlighted the need for further improvements, especially concerning the effect of the engine thermal state on the NOx emissions in transient operation. Moreover, several aspects, such as the check of the computational time, the impact of the controller on other pollutant emissions, or on the long-term engine operations, will have to be evaluated in future studies in view of the controller implementation on the engine control unit.


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