Model-Based Actuator Trajectories Optimization for a Diesel Engine Using a Direct Method

2010 ◽  
Vol 133 (3) ◽  
Author(s):  
Michael Benz ◽  
Markus Hehn ◽  
Christopher H. Onder ◽  
Lino Guzzella
Keyword(s):  
Numerical Optimization ◽  
Fuel Injection ◽  
Direct Method ◽  
Optimization Methods ◽  
Optimization Method ◽  
Mean Value ◽  
Pollutant Emissions ◽  
Pollutant Emission ◽  
Transient Operation ◽  
Engine Model

This paper proposes a novel optimization method that allows a reduction in the pollutant emission of diesel engines during transient operation. The key idea is to synthesize optimal actuator commands using reliable models of the engine system and powerful numerical optimization methods. The engine model includes a mean-value engine model for the dynamics of the gas paths, including the turbocharger of the fuel injection, and of the torque generation. The pollutant formation is modeled using an extended quasi-static modeling approach. The optimization substantially changes the input signals, such that the engine model is enabled to extrapolate all relevant outputs beyond the regular operating area. A feedforward controller for the injected fuel mass is used to eliminate the nonlinear path constraints during the optimization. The model is validated using experimental data obtained on a transient engine test bench. A direct single shooting method is found to be most effective for the numerical optimization. The results show a significant potential for reducing the pollutant emissions during transient operation of the engine. The optimized input trajectories derived assist the design of sophisticated engine control systems.

Nonsmooth Optimization Method for Image Restoration

1995 ◽  
Author(s):  
Kazufumi Ito ◽  
Karl Kunisch
Keyword(s):  
Image Restoration ◽  
Nonsmooth Optimization ◽  
Numerical Optimization ◽  
Augmented Lagrangian ◽  
Energy Criterion ◽  
Optimization Methods ◽  
Optimization Method ◽  
Augmented Lagrangian Methods ◽  
Active Set ◽  
First Order

Abstract In this paper we discuss applications of the numerical optimization methods for nonsmooth optimization, developed in [IK1] for the variational formulation of image restoration problems involving bounded variation type energy criterion. The Uzawa’s algorithm, first order augmented Lagrangian methods and Newton-like update using the active set strategy are described.

scholarly journals Development of a Variable Valve Actuation Control to Improve Diesel Oxidation Catalyst Efficiency and Emissions in a Light Duty Diesel Engine

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4561 ◽  
Author(s):  
José R. Serrano ◽  
Francisco J. Arnau ◽  
Jaime Martín ◽  
Ángel Auñón
Keyword(s):  
Diesel Oxidation Catalyst ◽  
Operating Conditions ◽  
Pollutant Emissions ◽  
Oxidation Catalyst ◽  
Pollutant Emission ◽  
Engine Model ◽  
Light Duty ◽  
Diesel Oxidation ◽  
Variable Valve ◽  
Catalyst Efficiency

Growing interest has arisen to adopt Variable Valve Timing (VVT) technology for automotive engines due to the need to fulfill the pollutant emission regulations. Several VVT strategies, such as the exhaust re-opening and the late exhaust closing, can be used to achieve an increment in the after-treatment upstream temperature by increasing the residual gas amount. In this study, a one-dimensional gas dynamics engine model has been used to simulate several VVT strategies and develop a control system to actuate over the valves timing in order to increase diesel oxidation catalyst efficiency and reduce the exhaust pollutant emissions. A transient operating conditions comparison, taking the Worldwide Harmonized Light-Duty Vehicles Test Cycle (WLTC) as a reference, has been done by analyzing fuel economy, HC and CO pollutant emissions levels. The results conclude that the combination of an early exhaust and a late intake valve events leads to a 20% reduction in CO emissions with a fuel penalty of 6% over the low speed stage of the WLTC, during the warm-up of the oxidation catalyst. The same set-up is able to reduce HC emissions down to 16% and NOx emission by 13%.

scholarly journals An Empirical Study on Low Emission Taxiing Path Optimization of Aircrafts on Airport Surfaces from the Perspective of Reducing Carbon Emissions

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1649 ◽  
Author(s):  
Nan Li ◽  
Yu Sun ◽  
Jian Yu ◽  
Jian-Cheng Li ◽  
Hong-fei Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Emission Reduction ◽  
Trajectory Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
Path Optimization ◽  
Pollutant Emissions ◽  
Future Research ◽  
Aircraft Emissions ◽  
Fuel Consumption And Emissions

Aircraft emissions are the main cause of airport air pollution. One of the keys to achieving airport energy conservation and emission reduction is to optimize aircraft taxiing paths. The traditional optimization method based on the shortest taxi time is to model the aircraft under the assumption of uniform speed taxiing. Although it is easy to solve, it does not take into account the change of the velocity profile when the aircraft turns. In view of this, this paper comprehensively considered the aircraft’s taxiing distance, the number of large steering times and collision avoidance in the taxi, and established a path optimization model for aircraft taxiing at airport surface with the shortest total taxi time as the target. The genetic algorithm was used to solve the model. The experimental results show that the total fuel consumption and emissions of the aircraft are reduced by 35% and 46%, respectively, before optimization, and the taxi time is greatly reduced, which effectively avoids the taxiing conflict and reduces the pollutant emissions during the taxiing phase. Compared with traditional optimization methods that do not consider turning factors, energy saving and emission reduction effects are more significant. The proposed method is faster than other complex algorithms considering multiple factors, and has higher practical application value. It is expected to be applied in the more accurate airport surface real-time running trajectory optimization in the future. Future research will increase the actual interference factors of the airport, comprehensively analyze the actual situation of the airport’s inbound and outbound flights, dynamically adjust the taxiing path of the aircraft and maintain the real-time performance of the system, and further optimize the algorithm to improve the performance of the algorithm.

Sliding Mode Control of Both Air-to-Fuel and Fuel Ratios for a Dual-Fuel Internal Combustion Engine

2012 ◽  
Vol 134 (3) ◽  
Author(s):  
Stephen Pace ◽  
Guoming G. Zhu
Keyword(s):  
Sliding Mode Control ◽  
Fuel Injection ◽  
Sliding Mode ◽  
Combustion Engine ◽  
Direct Injection ◽  
Mean Value ◽  
Automotive Engine ◽  
Engine Model ◽  
Mode Control ◽  
Flow Disturbances

A multi-input-multi-output (MIMO) sliding mode control scheme was developed with guaranteed stability to simultaneously control air-to-fuel ratio (AFR) and fuel ratios to desired levels under various air flow disturbances by regulating the mass flow rates of engine port-fuel-injection (PFI) and direct injection (DI) systems. The sliding mode control performance was compared with a baseline multiloop proportional integral differential (PID) controller through simulations and showed improvements. A four cylinder mean value engine model and the proposed sliding mode controller were implemented into a hardware-in-the-loop (HIL) simulator and a target engine control module, and HIL simulations were conducted to validate the developed controller for potential implementation in an automotive engine.

Advance of Optimization Methods for Identifing Groundwater Pollution Source Porperties

2012 ◽  
Vol 178-181 ◽  
pp. 603-608 ◽  
Author(s):  
Yu Qiao Long ◽  
Wei Li ◽  
Ju Huang
Keyword(s):  
Heuristic Algorithm ◽  
Groundwater Pollution ◽  
Direct Method ◽  
Groundwater Resources ◽  
Field Tests ◽  
Simulation Method ◽  
Optimization Methods ◽  
Optimization Method ◽  
Pollution Source ◽  
Groundwater Environment

China has to confront the groundwater resources crisis and the deterioration of groundwater environment. Reinforcing the studies on groundwater pollution source identification (GPSI) could be an important support to contamination removing, groundwater protecting, drinking water security, and development of society and economy. Exploring the new theory and method on GPSI could push the studies on ill-posed problems, and improve the techniques of contamination remediation. GPSI has been studied for thirty years, and a brief review is given to conclude the characteristics of GPSI problems. The mathematical simulation method can be classified into four types: optimization method, analytical and regression method, direct method, and stochastic method. A specific review of optimization approaches is given in this paper. The configuration, simulation procedures, common optimization algorithms used by the optimization methods are discussed in detail. Both non-heuristic and heuristic algorithm can be used to solve the PSI problem. The heuristic algorithm is more suitable for complex numerical and field cases, but it is time-consuming. The non-heuristic algorithm, especially the algorithm combined with analytical method, is time-economical, but is not suitable for complicated numerical and field tests. Further researches may focus on more complex GPSI problems, expressing physical chemistry and biological process, improving efficiency and model uncertainty of GPSI modeling.

scholarly journals Advanced Interior Optimization Methods with Electronics Applications

2021 ◽  
pp. 97-110
Author(s):  
Francisco Casesnoves
Keyword(s):  
Nonlinear Systems ◽  
Numerical Optimization ◽  
Global Minimum ◽  
Optimization Methods ◽  
Optimization Method ◽  
Systems Of Nonlinear Equations ◽  
Systems Of Equations ◽  
Nonlinear Systems Of Equations ◽  
Further Development

<p>In a previous contribution, the mathematical-computational base of Interior Optimization Method was demonstrated. Electronics applications were performed with numerical optimization data and graphical proofs. In this evoluted-improved paper a series of electronics applications of Interior Optimization in superconductors BCS algorithms/theory are shown. In addition, mathematical developments of Interior Optimization Methods related to systems of Nonlinear Equations are proven. The nonlinear multiobjective optimization problem constitutes a difficult task to find/determine a global minimum, approximated-global minimum, or a convenient local minimum whith/without constraints. Nonlinear systems of equations principles set the base in the previous article for further development of Interior Optimization and Interior-Graphical Optimization [Casesnoves, 2016-7]. From Graphical Optimization 3D optimization stages [Casesnoves, 2016-7], the demonstration that solution of nonlinear systems of equations is not unique in general emerges. Software-engineering and computational simulations are shown with electronics superconductors [several elements, Type 1 superconductors] and electronics physics applications. Extensions to similar applications for materials-tribology models and Biomedical Tribology are explained.</p>

A New Structural Optimization Method Based on Group Hunting of Animals: Hunting Search (HuS)

2010 ◽  
Author(s):  
R. Oftadeh ◽  
M. J. Mahjoob
Keyword(s):  
Structural Optimization ◽  
Numerical Optimization ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Harmony Search ◽  
Optimization Methods ◽  
Optimization Method ◽  
Global Optimization Methods ◽  
Multi Level ◽  
Group Hunting

This paper presents a novel structural optimization algorithm based on group hunting of animals such as lions, wolves, and dolphins. Although these hunters have differences in the way of hunting but they are common in that all of them look for a prey in a group. The hunters encircle the prey and gradually tighten the ring of siege until they catch the prey. In addition, each member of the group corrects its position based on its own position and the position of other members. If the prey escapes from the ring, the hunters reorganize the group to siege the prey again. A benchmark numerical optimization problems is presented to show how the algorithm works. Three benchmark structural optimization problems are also presented to demonstrate the effectiveness and robustness of the proposed Hunting Search (HuS) algorithm for structural optimization. The objective in these problems is to minimize the weight of bar trusses. Both sizing and layout optimization variables are included, too. The proposed algorithm is compared with other global optimization methods such as CMLPSA (Corrected Multi-Level & Multi-Point Simulated Annealing) and HS (Harmony Search). The results indicate that the proposed method is a powerful search and optimization technique. It yields comparable and in some cases, better solutions compared to those obtained using current algorithms when applied to structural optimization problems.

A Multi-Stage Krill Herd Algorithm for Global Numerical Optimization

2016 ◽  
Vol 25 (02) ◽  
pp. 1550030 ◽  
Author(s):  
Gai-Ge Wang ◽  
Amir H. Gandomi ◽  
Amir H. Alavi ◽  
Suash Deb
Keyword(s):  
Numerical Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimization Method ◽  
Fine Tuning ◽  
Benchmark Problems ◽  
Global Numerical Optimization ◽  
Candidate Solution ◽  
Multi Stage ◽  
Krill Herd

A multi-stage krill herd (MSKH) algorithm is presented to fully exploit the global and local search abilities of the standard krill herd (KH) optimization method. The proposed method involves exploration and exploitation stages. The exploration stage uses the basic KH algorithm to select a good candidate solution set. This phase is followed by fine-tuning a good candidate solution in the exploitation stage with a focused local mutation and crossover (LMC) operator in order to enhance the reliability of the method for solving global numerical optimization problems. Moreover, the elitism scheme is introduced into the MSKH method to guarantee the best solution. The performance of MSKH is verified using twenty-five standard and rotated and shifted benchmark problems. The results show the superiority of the proposed algorithm to the standard KH and other well-known optimization methods.

Optimal Mission Analysis Accounting for Engine Aging and Emissions

2008 ◽  
Author(s):  
M. Kelaidis ◽  
N. Aretakis ◽  
A. Tsalavoutas ◽  
K. Mathioudakis
Keyword(s):  
Optimization Method ◽  
Flight Simulation ◽  
Pollutant Emissions ◽  
Mission Analysis ◽  
Engine Model ◽  
Board Performance ◽  
Overall Performance ◽  
Profile Characteristics ◽  
Semi Empirical ◽  
Engine Condition

This paper describes an aircraft mission analysis procedure, comprising a flight simulation module, an engine model and an optimization method. The incorporation of engine deterioration modeling extends this procedure’s ability to estimate the on board performance of a given engine as it ages through time and use. Additionally, in order to investigate the environmental impact, pollutant emissions semi-empirical correlations have been introduced, after being adapted to available emissions data. The proposed procedure allows the optimization of a flight scenario for a variety of aircrafts, missions, and engine condition combinations, using an optimization method. The values of mission profile characteristics (e.g. cruise, altitude, and speed) that provide the optimum overall performance, regarding fuel conservation, time related costs, or pollutants production, are studied.

scholarly journals Improving Bees Algorithm Using Gradual Search Space Reduction

2021 ◽  
Author(s):  
Turki Binbakir
Keyword(s):  
Numerical Optimization ◽  
Optimization Methods ◽  
Search Space ◽  
Optimization Method ◽  
New Technique ◽  
Bees Algorithm ◽  
Elimination Method ◽  
Space Reduction ◽  
Engineering Problems ◽  
A New Technique

Abstract The aim of this research is to propose a new technique to improve Bees Algorithm. Bees Algorithm is one of the well-known metaheuristic optimization method which have been subject to several attempts to improve it by overcoming some of the weaknesses. The suggested method is derived from the numerical optimization methods, namely bracketing and region elimination methods. It employs an adaption of the regional elimination method to achieve abandonment and reduction of search space within the Bees Algorithm. The utilization of the exhaustive search involves exploring the whole search space to find the optimum at equally located intervals. To assess performance, the proposed method was evaluated on twenty-four benchmark functions and two engineering problems. The acquired result indicated a statistically significant improvement.

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