Nonlinear Model Predictive Control of Integrated Diesel Engine and Selective Catalytic Reduction System for Simultaneous Fuel Economy Improvement and Emissions Reduction

Author(s):  
Pingen Chen ◽  
Junmin Wang

The applications of diesel engines in ground vehicles have attracted much attention over the past decade for the reasons of outstanding fuel economy, power capability, and reliability. With the increasing demand of less greenhouse gas emissions, the current diesel engine fuel efficiency remains unsatisfactory partially due to the conflict between the engine fuel efficiency and engine-out NOx emissions. While advanced aftertreatment systems, such as selective catalytic reduction (SCR) systems or lean NOx trap, have been integrated to diesel engines for reducing the tailpipe NOx emissions, the integrated controls for coordinating diesel engine and SCR system to achieve high engine efficiency and low tailpipe emissions are still limited. The purpose of this study is to develop such an integrated diesel engine and SCR system control method using nonlinear model predictive control (NMPC) approach with both start of injection (SOI) timing and urea solution injection rate as the control inputs. Control-oriented engine models were developed to quantify the influences of SOI timing on engine efficiency and engine-out NOx emissions. Simulation results under US06 driving cycle demonstrate that, given the same catalyst size in total, the proposed controllers are capable of reducing total engine fuel consumption over the driving cycle by 9.36% and 9.50%, respectively, for lumped SCR system and two-cell SCR system, while maintaining high NOx conversion efficiencies and low tailpipe ammonia slip.

Author(s):  
Kenneth Meierjurgen ◽  
Brian Harries ◽  
Marc Compere ◽  
Yan Tang

The transportation industry is a major contributor to the increase of greenhouse gasses present in the atmosphere. With the number of automobiles increasing every year, the U.S. government has implemented several regulations to reduce the environmental impact of the transportation industry. The most recent regulations increase the Corporate Average Fuel Economy (CAFÉ) to over 50mpg by 2025. These increased fuel economy standards will save consumers money, reduce dependence on foreign oil and cut GHG emissions in half (1). In order to comply with these regulations and reduce GHG emissions, automakers are improving powertrain efficiency and diversifying their fuel sources. One way automakers are improving fleet fuel economy is by offering more efficient Compression Iginition (CI) engines. Compression ignition engines can have a 10% improvement in peak efficiency over a Spark Ignition (SI) Engine. Although CI engines have higher efficiencies, they also have higher Nitrous Oxide (NOx) emissions. One of the most effective methods for reducing NOx emissions is a Selective Catalytic Reduction (SCR) system. Current methods for reducing NOx emissions using SCR rely on two NOx sensors for close loop control. These sensors add substantial costs to the production exhaust after treatment systems. This paper presents an intelligent control technique to achieve accurate prediction of NOx emissions and closed loop control without the use of expensive on board sensors. Simulation models were created to validate two artificial neural networks that aim to replace the upstream and downstream NOx sensors. The upstream neural network was trained using dynamometer data from a General Motors 1.3l turbo diesel engine. This neural network represented NOx emissions as a function of engine speed and throttle position. The downstream ANN was created using a nonlinear statespace plant model that simulates the catalyst NOx and nh3 reaction. To control the nh3 injection into the catalyst, a Fuzzy Logic Controller (FLC) was implemented. The FLC controller had two inputs: the error function calculated from the output NOx and a predetermined NOx target as well as the predicted surface coverage from the nh3 reaction. The results from steady state and drive cycle simulations are shown. The work presented in this paper serves as a proof of concept for the sensorless SCR system that was developed as part of ERAU’s entry in EcoCAR2: Plugging Into the Future. The simulations were conducted as part of year 1 of the EcoCAR2 competition and will be further developed during years 2 and 3 on ERAU’s Series Plug-in Hybrid Electric Vehicle.


2017 ◽  
Author(s):  
Apostolos Karvountzis-Kontakiotis ◽  
Apostolos Pesiridis ◽  
Hua Zhao ◽  
Fuhaid Alshammari ◽  
Benjamin Franchetti ◽  
...  

Author(s):  
B. B. Sahoo ◽  
U. K. Saha ◽  
N. Sahoo ◽  
P. Prusty

The fuel efficiency of a modern diesel engine has decreased due to the recent revisions to emission standards. For an engine fuel economy, the engine speed is to be optimum for an exact throttle opening (TO) position. This work presents an analysis of throttle opening variation impact on a multi-cylinder, direct injection diesel engine with the aid of Second Law of thermodynamics. For this purpose, the engine is run for different throttle openings with several load and speed variations. At a steady engine loading condition, variation in the throttle openings has resulted in different engine speeds. The Second Law analysis, also called ‘Exergy’ analysis, is performed for these different engine speeds at their throttle positions. The Second Law analysis includes brake work, coolant heat transfer, exhaust losses, exergy efficiency, and airfuel ratio. The availability analysis is performed for 70%, 80%, and 90% loads of engine maximum power condition with 50%, 75%, and 100% TO variations. The data are recorded using a computerized engine test unit. Results indicate that the optimum engine operating conditions for 70%, 80% and 90% engine loads are 2000 rpm at 50% TO, 2300 rpm at 75% TO and 3250 rpm at 100% TO respectively.


Catalysts ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1269
Author(s):  
Muhammad Khristamto Aditya Wardana ◽  
Kwangchul Oh ◽  
Ocktaeck Lim

Heavy-duty diesel engines in highway use account for more than 40% of total particulate and nitrogen oxide (NOx) emissions around the world. Selective catalytic reduction (SCR) is a method with effective results to reduce this problem. This research deals with problems in the urea evaporation process and ammonia gas distribution in an SCR system. The studied system used two types of urea injectors to elucidate the quality of ammonia uniformity in the SCR system, and a 12,000-cc heavy-duty diesel engine was used for experimentation to reduce NOx in the system. The uniformity of the generated quantities of ammonia was sampled at the catalyst inlet using a gas sensor. The ammonia samples from the two types of urea injectors were compared in experimental and simulation results, where the simulation conditions were based on experimental parameters and were performed using the commercial CFD (computational fluid dynamics) code of STAR-CCM+. This study produces temperatures of 371 to 374 °C to assist the vaporization phenomena of two injectors, the gas pattern informs the distributions of ammonia in the system, and the high ammonia quantity from the I-type urea injector and high quality of ammonia uniformity from the L-type urea injector can produce different results for NOx reduction efficiency quality after the catalyst process. The investigations showed the performance of two types of injectors and catalysts in the SCR system in a heavy-duty diesel engine.


2001 ◽  
Author(s):  
J. A. Mc Geehan ◽  
W. Alexander ◽  
M. C. Couch ◽  
J. A. Rutherford ◽  
S. H. Roby

Author(s):  
Kuo Yang ◽  
Pingen Chen

Abstract Engine efficiency improvement is very critical for medium to heavy-duty vehicles to reduce Diesel fuel consumption and enhance U.S. energy security. The tradeoff between engine efficiency and NOx emissions is an intrinsic property that prevents modern Diesel engines, which are generally equipped with exhaust gas recirculation (EGR) and variable geometry turbocharger (VGT), from achieving the optimal engine efficiency while meeting the stringent NOx emission standards. The addition of urea-based selective catalytic reduction (SCR) systems to modern Diesel engine aftertreatment systems alleviate the burden of NOx emission control on Diesel engines, which in return creates extra freedom for optimizing Diesel engine efficiency. This paper proposes two model-based approaches to locate the optimal operating point of EGR and VGT in the air-path loop to maximize the indicated efficiency of turbocharged diesel engine. Simulation results demonstrated that the engine brake specific fuel consumption (BSFC) can be reduced by up to 1.6% through optimization of EGR and VGT, compared to a baseline EGR-VGT control which considers both NOx emissions and engine efficiency on engine side. The overall equivalent BSFCs are 1.8% higher with optimized EGR and VGT control than with the baseline control. In addition, the influence of reducing EGR valve opening on the non-minimum phase behavior of the air path loop is also analyzed. Simulation results showed slightly stronger non-minimum phase behaviors when EGR is fully closed.


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