Multi-Objective Optimization of Transient Air-Fuel Ratio Limitation of a Diesel Engine Using DoE Based Pareto-Optimal Approach

Gurel, Cetin; Ozmen, Elif; Yılmaz, Metin; Aydin, Didem; Köprübasi, Kerem

doi:10.4271/2017-01-0587

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…Excessive fuel injection mass will shorten the service life of the diesel engine and even cause serious damage. Besides, the fuel injection mass is usually limited to ensure appropriate excess air coefficient in order to achieve economical efficiency and satisfy strict emission requirements [41].…”

Section: Remarkmentioning

confidence: 99%

Disturbance Observer-Based Finite-Time Speed Control for Marine Diesel Engine With Input Constraints

Liu

Zhang

et al. 2020

IEEE Access

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In this article, a finite-time observer-based speed control strategy for the marine diesel engine is proposed with consideration of system parameter uncertainties, external disturbances and input constraints. Initially, a finite-time disturbance observer is designed, by which the synchronized uncertainties are accurately estimated in the sense of finite-time stability. Based on the observed information, a speed control strategy is proposed, and practical finite-time stability of the closed-loop system is demonstrated by rigorous theoretical analysis. Besides, for solving the input constraints inherent with the speed control system, an auxiliary variable is introduced to compensate the extra part of control output signals. Finally, numerical simulation and comparison are presented. The common operation situations of the marine diesel engines are taken into account, including starting, acceleration and deceleration between speed set points, sudden load changing, varied propulsion system parameters and different slope limits, etc. Comparing with the related existing method, the effectiveness and advantages of the proposed finite-time observer-based control law are illustrated. INDEX TERMS Finite-time control, disturbance observer, input constraints, marine diesel engine.

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Section: Remarkmentioning

confidence: 99%

Disturbance Observer-Based Finite-Time Speed Control for Marine Diesel Engine With Input Constraints

Liu

Zhang

et al. 2020

IEEE Access

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“…of combustion optimization [20]. Therefore, accurate modeling of transient NOx emissions is a key enabler for offline optimization, online control and onboard diagnostic of diesel engine combustion considering future diesel engine technologies [21].…”

Section: Wltp Rde and Pems Test Cycles Increases The Emphasis Of Trmentioning

confidence: 99%

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

et al. 2019

Self Cite

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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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“…Adding any technology to a powertrain exponentially increases the calibration effort needed to obtain the reductions in fuel economy each technology promises [1]. Beyond a specific complexity level, rule-based techniques driven by calibrated tables [2,3] break down. The exponential increase in computing requirements from the growth of the design space is called the curse of dimensionality [4].…”

Section: Introductionmentioning

confidence: 99%

A Review of Reinforcement Learning-Based Powertrain Controllers: Effects of Agent Selection for Mixed-Continuity Control and Reward Formulation

2023

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One major cost of improving the automotive fuel economy while simultaneously reducing tailpipe emissions is increased powertrain complexity. This complexity has consequently increased the resources (both time and money) needed to develop such powertrains. Powertrain performance is heavily influenced by the quality of the controller/calibration. Since traditional control development processes are becoming resource-intensive, better alternate methods are worth pursuing. Recently, reinforcement learning (RL), a machine learning technique, has proven capable of creating optimal controllers for complex systems. The model-free nature of RL has the potential to streamline the control development process, possibly reducing the time and money required. This article reviews the impact of choices in two areas on the performance of RL-based powertrain controllers to provide a better awareness of their benefits and consequences. First, we examine how RL algorithm action continuities and control–actuator continuities are matched, via native operation or conversion. Secondly, we discuss the formulation of the reward function. RL is able to optimize control policies defined by a wide spectrum of reward functions, including some functions that are difficult to implement with other techniques. RL action and control–actuator continuity matching affects the ability of the RL-based controller to understand and operate the powertrain while the reward function defines optimal behavior. Finally, opportunities for future RL-based powertrain control development are identified and discussed.

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Multi-Objective Optimization of Transient Air-Fuel Ratio Limitation of a Diesel Engine Using DoE Based Pareto-Optimal Approach

Cited by 4 publications

References 16 publications

Disturbance Observer-Based Finite-Time Speed Control for Marine Diesel Engine With Input Constraints

Disturbance Observer-Based Finite-Time Speed Control for Marine Diesel Engine With Input Constraints

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

A Review of Reinforcement Learning-Based Powertrain Controllers: Effects of Agent Selection for Mixed-Continuity Control and Reward Formulation

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