scholarly journals Cold-Start Modeling and On-Line Optimal Control of the Three-Way Catalyst

2021 ◽  
Author(s):  
Jonathan Lock ◽  
Kristoffer Clasén ◽  
Jonas Sjöblom ◽  
Tomas McKelvey
Keyword(s):  
Optimal Control ◽  
Combustion Engine ◽  
Cold Start ◽  
Reaction Rates ◽  
Hydrogen Gas ◽  
Optimal Controller ◽  
Individual Species ◽  
Model Parameters ◽  
Heat Of Reaction ◽  
Three Way Catalyst

AbstractWe present a three-way catalyst (TWC) cold-start model, calibrate the model based on experimental data from multiple operating points, and use the model to generate a Pareto-optimalcold-start controller suitable for implementation in standard engine control unit hardware. The TWC model is an extension of a previously presented physics-based model that predicts carbon monoxide, hydrocarbon, and nitrogen oxides tailpipe emissions. The model axially and radially resolves the temperatures in the monolith using very few state variables, thus allowing for use with control-policy based optimal control methods. In this paper, we extend the model to allow for variable axial discretization lengths, include the heat of reaction from hydrogen gas generated from the combustion engine, and reformulate the model parameters to be expressed in conventional units. We experimentally measured the temperature and emission evolution for cold-starts with ten different engine load points, which was subsequently used to tune the model parameters (e.g. chemical reaction rates, specific heats, and thermal resistances). The simulated cumulative tailpipe emission modeling error was found to be typically − 20% to + 80% of the measured emissions. We have constructed and simulated the performance of a Pareto-optimal controller using this model that balances fuel efficiency and the cumulative emissions of each individual species. A benchmark of the optimal controller with a conventional cold-start strategy shows the potential for reducing the cold-start emissions.

scholarly journals Modelling and Fuzzy-Threshold Control of SI Engine for Emission Reduction during Cold Start Phase

2019 ◽  
Vol 16 (4) ◽  
pp. 7225-7242
Author(s):  
O. Khalilikhah ◽  
M. Shalchian
Keyword(s):  
Combustion Engine ◽  
Cold Start ◽  
Model Parameters ◽  
Si Engine ◽  
Threshold Control ◽  
Operating Condition ◽  
Warm Up ◽  
Engine Efficiency ◽  
Start Up ◽  
Harmful Emissions

We present a controllable model of an internal combustion engine that captures the overlapping of the cylinder valves as a controllable parameter and its effect on engine efficiency and EGR rates. The model parameters have been calibrated for the EF7 engine and validated with experimental data. This model successfully estimates the performance and HC and NOx emissions concentration of the engine under cold start operating condition. A model-based fuzzy-threshold control strategy has been proposed in cold start operating condition. This strategy uses the overlapping angle of the cylinder inlet and outlet valves as an extra degree of freedom in comparison to the regular PID strategy in order to accelerate the warm-up duration the catalyst converter while reduces the exhaust harmful emissions during the warm-up phase. The proposed controller model has been verified in MATLAB Simulink environment and simulation results indicates 8.6% reduction of the start-up time of the catalyst converter and reduction of 3.5%, 8.5% and 7% of HC, NO and fuel consumption respectively during the catalyst warm-up phase.

scholarly journals Optimal Control for a Hydraulic Recuperation System Using Endoreversible Thermodynamics

2021 ◽  
Vol 11 (11) ◽  
pp. 5001
Author(s):  
Robin Masser ◽  
Karl Heinz Hoffmann
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Energy Savings ◽  
Combustion Engine ◽  
Mechanical Energy ◽  
Hydraulic Systems ◽  
Commercial Vehicles ◽  
Hybrid Drive ◽  
Environmental Considerations ◽  
Onboard System

Energy savings in the traffic sector are of considerable importance for economic and environmental considerations. Recuperation of mechanical energy in commercial vehicles can contribute to this goal. One promising technology rests on hydraulic systems, in particular for trucks which use such system also for other purposes such as lifting cargo or operating a crane. In this work the potential for energy savings is analyzed for commercial vehicles with tipper bodies, as these already have a hydraulic onboard system. The recuperation system is modeled based on endoreversible thermodynamics, thus providing a framework in which realistic driving data can be incorporated. We further used dissipative engine setups for modeling both the hydraulic and combustion engine of the hybrid drive train in order to include realistic efficiency maps. As a result, reduction in fuel consumption of up to 26% as compared to a simple baseline recuperation strategy can be achieved with an optimized recuperation control.

The Effect of Adding Oxygenated Compounds to Gasoline on Automotive Exhaust Emissions

2002 ◽  
Vol 125 (1) ◽  
pp. 344-350 ◽  
Author(s):  
S. G. Poulopoulos ◽  
C. J. Philippopoulos
Keyword(s):  
Octane Number ◽  
Combustion Engine ◽  
Methyl Tertiary Butyl Ether ◽  
Butyl Ether ◽  
Tertiary Butyl ◽  
Research Octane Number ◽  
Oxygenated Compounds ◽  
Reid Vapor Pressure ◽  
Three Way Catalyst ◽  
Unregulated Emissions

In the present work, the effect of adding ethanol or methyl tertiary butyl ether (MTBE) to gasoline on the regulated and unregulated emissions from an internal combustion engine with a typical three-way catalyst was studied. The addition of ethanol to fuel (10% w/w) increased both the research octane number and the Reid vapor pressure of the fuel, whereas adding 11% w/w MTBE caused an increase only in the research octane number of the fuel. When the fuel contained MTBE, less hydrocarbons, carbon monoxide, and acetaldehyde were emitted in the tailpipe. The increased emissions of acetaldehyde and ethanol were the main disadvantages of using ethanol.

Optimal Control of Arrays of Microcantilevers

1999 ◽  
Vol 121 (4) ◽  
pp. 686-690 ◽  
Author(s):  
Mariateresa Napoli ◽  
Bassam Bamieh ◽  
Mohammed Dahleh
Keyword(s):  
Optimal Control ◽  
Atomic Force Microscopy ◽  
Optimal Controller ◽  
Invariant System ◽  
Sensors And Actuators ◽  
Force Microscopy ◽  
Atomic Force ◽  
Distributed Array ◽  
Spatial Invariance ◽  
Analytic Expression

In this paper we will present a model for an array of microcantilevers that are used in Atomic Force Microscopy and nano-scale manufacturing. The microcantilevers are connected to each other through a common base, and are individually actuated. The sensors are also integrated on each microcantilever. We consider the problem of controlling a tightly packed array of identical microcantilevers that are dynamically coupled. This system is an example of a spatially-invariant system with a distributed array of sensors and actuators. We exploit the spatial invariance of the problem to design optimal ℋ2 controllers for this array. An analytic expression for the optimal controller is derived in the transformed domain, and estimates of the coupling range of the controller is obtained.

scholarly journals Estimation and optimal control of the multi-scale dynamics of the Covid-19

2021 ◽  
Author(s):  
David Jaurès Fotsa-Mbogne ◽  
Stéphane Yanick Tchoumi ◽  
Yannick Kouakep-Tchaptchie ◽  
Vivient Corneille Kamla ◽  
Jean-Claude Kamgang ◽  
...  
Keyword(s):  
Optimal Control ◽  
Human Population ◽  
Virus Transmission ◽  
Scale Model ◽  
Model Parameters ◽  
Optimal Control Strategy ◽  
Or Efficiency ◽  
Human Virus ◽  
Multi Scale ◽  
Human Density

AbstractThis work aims at a better understanding and the optimal control of the spread of the new severe acute respiratory corona virus 2 (SARS-CoV-2). We first propose a multi-scale model giving insights on the virus population dynamics, the transmission process and the infection mechanism. We consider 10 compartments in the human population in order to take into accounts the effects of different specific mitigation policies: susceptible, infected, infectious, quarantined, hospitalized, treated, recovered, non-infectious dead, infectious dead, buried. The population of viruses is also partitioned into 10 compartments corresponding respectively to each of the first nine human population compartments and the free viruses available in the environment. Indeed, we have human to human virus transmission, human to environment virus transmission, environment to human virus transmission and self infection by susceptible individuals. We show the global stability of the disease free equilibrium if a given threshold 𝒯0 is less or equal to 1 and we provide how to compute the basic reproduction number ℛ0. A convergence index 𝒯1 is also defined in order to estimate the speed at which the disease extincts and an upper bound to the time of extinction is given. The existence of the endemic equilibrium is conditional and its description is provided. We evaluate the sensitivity of ℛ0, 𝒯0 and 𝒯1 to control parameters such as the maximal human density allowed per unit of surface, the rate of disinfection both for people and environment, the mobility probability, the wearing mask probability or efficiency, and the human to human contact rate which results from the previous one. Except the maximal human density allowed per unit of surface, all those parameters have significant effects on the qualitative dynamics of the disease. The most significant is the probability of wearing mask followed by the probability of mobility and the disinfection rate. According to a functional cost taking into consideration economic impacts of SARS-CoV-2, we determine and discuss optimal fighting strategies. The study is applied to real available data from Cameroon and an estimation of model parameters is done. After several simulations, social distancing and the disinfection frequency appear as the main elements of the optimal control strategy.

scholarly journals Design and optimal control of a tiltrotor micro-aerial vehicle for efficient omnidirectional flight

2020 ◽  
Vol 39 (10-11) ◽  
pp. 1305-1325
Author(s):  
Mike Allenspach ◽  
Karen Bodie ◽  
Maximilian Brunner ◽  
Luca Rinsoz ◽  
Zachary Taylor ◽  
...  
Keyword(s):  
Optimal Control ◽  
Design Optimization ◽  
System Design ◽  
Optimal Controller ◽  
Micro Aerial Vehicle ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Robust System ◽  
Six Degree Of Freedom ◽  
Allocation Approach

Omnidirectional micro-aerial vehicles (MAVs) are a growing field of research, with demonstrated advantages for aerial interaction and uninhibited observation. While systems with complete pose omnidirectionality and high hover efficiency have been developed independently, a robust system that combines the two has not been demonstrated to date. This paper presents the design and optimal control of a novel omnidirectional vehicle that can exert a wrench in any orientation while maintaining efficient flight configurations. The system design is motivated by the result of a morphology design optimization. A six-degree-of-freedom optimal controller is derived, with an actuator allocation approach that implements task prioritization, and is robust to singularities. Flight experiments demonstrate and verify the system’s capabilities.

Turing and Benjamin–Feir instability mechanisms in non-autonomous systems

2020 ◽  
Vol 476 (2238) ◽  
pp. 20200003 ◽  
Author(s):  
Robert A. Van Gorder
Keyword(s):  
Autonomous Systems ◽  
Reaction Diffusion ◽  
Reaction Rates ◽  
Time Dependent ◽  
Model Parameters ◽  
Time Varying ◽  
Reaction Diffusion Systems ◽  
Diffusion Systems ◽  
Dependent Model ◽  
Spatio Temporal

The Turing and Benjamin–Feir instabilities are two of the primary instability mechanisms useful for studying the transition from homogeneous states to heterogeneous spatial or spatio-temporal states in reaction–diffusion systems. We consider the case when the underlying reaction–diffusion system is non-autonomous or has a base state which varies in time, as in this case standard approaches, which rely on temporal eigenvalues, break down. We are able to establish respective criteria for the onset of each instability using comparison principles, obtaining inequalities which involve the in general time-dependent model parameters and their time derivatives. In the autonomous limit where the base state is constant in time, our results exactly recover the respective Turing and Benjamin–Feir conditions known in the literature. Our results make the Turing and Benjamin–Feir analysis amenable for a wide collection of applications, and allow one to better understand instabilities emergent due to a variety of non-autonomous mechanisms, including time-varying diffusion coefficients, time-varying reaction rates, time-dependent transitions between reaction kinetics and base states which change in time (such as heteroclinic connections between unique steady states, or limit cycles), to name a few examples.

scholarly journals Bayesian inference of distributed time delay in transcriptional and translational regulation

2019 ◽  
Vol 36 (2) ◽  
pp. 586-593
Author(s):  
Boseung Choi ◽  
Yu-Yu Cheng ◽  
Selahattin Cinar ◽  
William Ott ◽  
Matthew R Bennett ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Stochastic Systems ◽  
Imaging Techniques ◽  
Reaction Rates ◽  
Biochemical Networks ◽  
Supplementary Information ◽  
Mcmc Methods ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Cell Functions

Abstract Motivation Advances in experimental and imaging techniques have allowed for unprecedented insights into the dynamical processes within individual cells. However, many facets of intracellular dynamics remain hidden, or can be measured only indirectly. This makes it challenging to reconstruct the regulatory networks that govern the biochemical processes underlying various cell functions. Current estimation techniques for inferring reaction rates frequently rely on marginalization over unobserved processes and states. Even in simple systems this approach can be computationally challenging, and can lead to large uncertainties and lack of robustness in parameter estimates. Therefore we will require alternative approaches to efficiently uncover the interactions in complex biochemical networks. Results We propose a Bayesian inference framework based on replacing uninteresting or unobserved reactions with time delays. Although the resulting models are non-Markovian, recent results on stochastic systems with random delays allow us to rigorously obtain expressions for the likelihoods of model parameters. In turn, this allows us to extend MCMC methods to efficiently estimate reaction rates, and delay distribution parameters, from single-cell assays. We illustrate the advantages, and potential pitfalls, of the approach using a birth–death model with both synthetic and experimental data, and show that we can robustly infer model parameters using a relatively small number of measurements. We demonstrate how to do so even when only the relative molecule count within the cell is measured, as in the case of fluorescence microscopy. Availability and implementation Accompanying code in R is available at https://github.com/cbskust/DDE_BD. Supplementary information Supplementary data are available at Bioinformatics online.

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