Investigating the relative contribution of operational parameters on performance and emissions of a common-rail diesel engine using neural network

Engine performance and emissions depend on a variety of parameters affecting the engine. Thanks to utilization of modern diesel engine with mechatronic systems, the number engine actuators increase significantly. The actuators can affect the internal states (operational parameters) of diesel engine such as inlet manifold pressure, EGR rate, quantity and timing of pilot and main injection which in turn will influence the engine emissions and performance. These internal states can be considered as boundary conditions of in-cylinder combustion process. Due to large number of effective parameters, study of relative contribution of these states on engine outputs will be helpful in better controlling and calibration of diesel engines. In this paper, comparative effects of internal states on both performance and emissions are investigated using statistical method and ranked based on their importance. Ten engine operational parameters including: injected fuel mass, pilot and main injection mass, main and pilot injection timing, inlet air pressure and temperature, exhaust pressure, fuel rail pressure and exhaust gas recirculation rate (EGR) are considered and their influence on brake torque, Soot, NOx and brake specific fuel consumption (BSFC) is investigated. A thermodynamic model of engine cycle is developed in AVL Boost®; the model is tuned and validated using experimental data. In order to better and faster study the effects of operational parameters on engine performance, a neural network is employed. The required data to train the neural networks is provided by using AVL Boost Design Explorer. Due to large number of inputs and outputs, a low-discrepancy and low-dispersion sequences generator called Sobol method is used to generate quasi random sequences of input data. More than 4000 engine operation points are generated and simulated in AVL Boost. The provided data is then used to train a feed forward neural network using Bayesian training method. Comparison between experimental data and simulated results shows about 6% error in prediction of the outputs. The engine performance and emission is then analyzed using both graphical and statistical methods to study how different input parameters can influence the engine emissions and performance. Finally, the relative importance of each parameter on different engine performance and emission characteristics are investigated using perturbation method and most influential parameters on different outputs are obtained

Numerical/Experimental Studies on Performance at Low Engine Speeds:A Case study Downsized Iranian National Engine (EF7)

Engine downsizing is a trusted method to reduce fuel consumption and pollution emitted from internal combustion engines. In this method, engine displacement volume is reduced while maintaining the same power/torque characteristics. However, there still exist several limitations to utilize this technology. In this paper, the naturally aspirated type of Iran national engine (EF7-NA) is investigated for a possible downsized version. A one-dimensional engine model equipped with a zero-dimensional two-zone combustion sub-model was developed and validated via experimental results for both natural aspirated and turbocharged engine types. Then experimental and numerical studies were carried out for the primary concept, deactivation of one cylinder besides using a turbocharger. To overcome the concept shortages, especially in lower ranges of engine speed, numerical studies were extended. Deployment of several turbochargers with different performance maps and different valve timing via a dual CVVT system were investigated. The results showed that there is a feasible method for EF7 engine downsizing via a 3-cylinder type equipped with a modified turbocharger and valve timing. The maximum difference between base-engine and downsized version torque is about 7% in low engine speeds

Engine Downsizing; Global Approach to Reduce Emissions: A World-Wide Review:A World-Wide Review

Engine downsizing is a promising method to reduce emissions and fuel consumption of internal combustion engines. The main concept is to reduce engine displacement volume while keeping the needed output characteristics unchanged. The issue has become one of the most current fields of interest in recent years after the International Energy Agency set a target of a 50% reduction in global average emissions by the year 2030. In this review paper, different aspects of researchers’ efforts on engine downsizing are configured and, due to overlaps, categorized into five main areas. Each category is discussed thoroughly, and recent works are highlighted. The global attention in these categories, the countries involved and the trend change in the last four years are presented in detail. Doi: 10.28991/HIJ-2021-02-04-010 Full Text: PD

A Model-Based Investigation of Electrically Split Turbocharger Systems Capabilities to Overcome the Drawbacks of High-Boost Downsized Engines

Engine downsizing is one the most common methods of coping with strict emission regulations. However, it must be coupled with complementary systems so that the engine performance would meet the standards. That is why new efficient solutions can pave the way toward this goal. The electric forced-induction system (EFIS) is the emerging replacement for conventional forced-induction systems (FIS), namely, turbochargers and superchargers. The reason behind this replacement is the drawbacks associated with FIS, among them are turbo lag and inefficiency in exhaust gas energy recycling. Electrically split turbocharger (EST) is a form of EFIS which offers a great potential for engine downsizing. In this paper, a new approach to EST utilization for lowering the fuel consumption (FC) without compromising performance has been introduced, through which the augmented degree of freedom enabled by an EST is used to optimize the air-charge boosting. To show the effectiveness of the proposed method, a model-based approach is used to compare two engines with and without EST technology; the performance of an already existing 1.6-l 4-cylinder turbocharged engine has been modeled based on the experimental data, and its performance indices are used as a benchmark for a downsized 1l 3-cylinder engine equipped with an EST. A comparison of these two engines in the dynamic drive cycles of the EPA Federal Test Procedure (FTP75) and Worldwide harmonized Light vehicles Test Cycles (WLTC) has shown a 28.87% and 25.35% reduction in FC, respectively, independent of the external electrical source. Furthermore, the downsized engine has shown superior performance through full-throttle acceleration in terms of torque transient response. Finally, the concept of coherence among gas-path components and its importance is presented, and knock precautions associated with air charging in this method are addressed

Development of a Driver-in-the-Loop Simulation to Evaluate the Performance to Energy Trade-Off of Active Dynamics Systems on an Electric Race Car

Automotive industry interest in renewable propulsion technology has led to a surge of investment in electric-only motorsport categories as a technological test bed. Electrification has enabled easier implementation of active vehicle dynamics control systems to improve performance and drivability, but limitations in battery technology create significant constraints which force a compromise between efficiency and performance. In this paper, four different control systems—Automatic Rear Steering (ARS), Drag Reduction System (DRS), Semi-Active Suspension (SAS), and Torque Vectoring (TV)—are tested in various configurations and combinations with the aim of characterizing their performance to energy consumption trade-offs in an electric Formula Student vehicle. A Driver-in-the-Loop (DiL) simulator was developed using Cruden Panthera along with a multibody Simulink vehicle model to capture the effects of drivability on vehicle performance. Vehicle configurations were tested using a combination of open-loop and closed-loop driving maneuvers, measuring performance indicators to capture absolute performance, power consumption, and driver workload. TV was the most effective at improving vehicle performance but also incurred the largest energy cost. ARS was also found to improve performance by a lesser degree but brought the greatest improvement to drivability. DRS improved straight-line performance and energy consumption at the expense of cornering performance and driver workload. SAS improved steady-state cornering performance but had minimal effect on transient maneuvers to justify its energy cost and complexity. Using TV, DRS, and ARS in conjunction was found to be the optimal configuration by quantifiably improving driver workload, lap time performance, and power consumption over the baseline vehicle

Investigating a new model-based calibration procedure for optimizing the emissions and performance of a turbocharged diesel engine

Today, diesel engines are no longer mentioned for generating huge amount of soot and high level of noise. These achievements are owing to the employment of numerous mechatronic systems implemented in the engine. Altogether, with the increase of the number of controllable parameters, the complexity of control and calibration tasks has been increased. In the conventional calibration processes, numerous tests are required for calibration of engine controllers, making it a time consuming and expensive procedure. However, in this paper a model-based calibration procedure based on evolutionary algorithms is investigated to fulfill the feed-forward controller look-up tables. The look-up tables obtain the fuel injection and air induction system parameters based on engine speed and relative load and guarantee the optimal operation of engine. The developed procedure guarantees the maximum attainable torque in full load. The proposed method decreased the time, cost and complexity of whole calibration procedure to high extent. Artificial neural network is employed for modeling the combustion process while steady-state mass and energy balance equations are used for inlet and exhaust models. The models have been validated using experimental data. The optimization is done in two phases: full load curve shaping and part load optimization. The aim of former is attaining maximum possible torque with the minimum emissions and fuel consumption in every engine speed while the aim of latter is delivering the required torque with the lowest possible emissions and fuel consumption. The results of tests show that the proposed model-based calibration method can effectively reduce the fuel consumption and emissions in whole engine operation regime and decrease the time and cost of calibration

Model Based Development of Torque Control Drive for Induction Motors for Micro Electric Vehicles

Electric vehicles are attaining significant attention recently and the current legislation is forcing the automotive industry to electrify the productions. Regardless of electric energy accumulation technology, drive technology is one of the vital components of EVs. The motor drive technology has been mainly developed based on the application which required position/velocity control. In automotive application, however, torque control is an important aspect since the drivers have already used to drive the vehicle based on torque control approach in traditional powertrain system. In this article, a model-based approach is employed to develop a controller which can guarantee the precise control of the induction motors torque for a micro electric vehicle (EV) application regardless of operating conditions. The implementation of the control drive was conducted in MATLAB/Simulink environment, followed by Model In the Loop simulation and testing at various test conditions to confirm the robustness of the developed drive. Direct Torque Control (DTC) with optimum voltage vector selection method is employed to control the motor torque that requires fewer power electronics to process its operation and hence lowers the cost of implementation. The result shows the practicality of the designed control system and its ability to track reference torque commands. Vitally, the controlled approach shows fair abilities to control IMs to produce torque at both the motoring and regenerative modes which is a highly important requirement in electrical propulsion powertrains. Furthermore, the controller’s response time was within the industrial standard range which confirms its suitability for industrial implementation at low cost