Development of a digital twin for real-time simulation of a combustion engine-based power plant with battery storage and grid coupling

Coordinated control of combustion engine-based power plants with battery storage is the next big thing for optimising renewable energy. Digital twins can enable such sophisticated control but currently are too simplistic for the required insight. This study explores the feasibility of a fully physics-based combustion engine model in real-time co-simulation with an electrical power plant model, including battery storage. A detailed, crank-angle resolved, one-dimensional model of a large-bore stationary engine is reduced to a fast-running model (FRM). This engine digital twin is coupled with a complete power plant control model, developed in Simulink. Real-time functions are tested on a dedicated rapid-prototyping system using a target computer. Measurement data from the corresponding power plant infrastructure provide validation for the digital twin. The model-in-the-loop simulations show real-time results from both the standalone combustion and electric submodels mostly within 5% of measured values. The model coupling for fully predictive simulation was tested on a desktop computer, showing expected functionality and validity within 4% and 8% of the respective measured generator and converter outputs. However, execution time of the FRM needs reducing when moving to final hardware-in-the-loop implementation of a complete power plant model.© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Toward a digital twin of a mid-speed marine engine : From detailed 1D engine model to real-time implementation on a target platform

System complexity is challenging for development of marine mid-speed engines when striving to meet increasingly stringent emission targets. Control-oriented modeling offers a solution, cutting calibration time and enabling robust control strategies. Simultaneously, real-time, physics-based engine models (digital twins) are emerging as they offer better predictive capability and scalability than typical mean-value, data-driven approaches. This study explored development of a control-oriented digital twin of a Wärtsilä 4L20 marine engine. Starting from a detailed one-dimensional model (GT-Suite), it explored reduction strategies toward a fast-running engine model (FRM), balancing the calculation speed and accuracy trade-off. Finally, the FRM was tested for real-time implementation on a target machine. Comprehensive experimental data from the 4L20 platform in the VEBIC Engine Laboratory provided the baseline for model calibration. Model calibration and validation covered four representative operating points and involved correlation of crank-angle, resolved in-cylinder pressures, thermal state at several locations of the engine air-path and relevant performance indicators. The results shed new light on the feasibility of digital twins in the marine engine domain. The obtained FRM was three times faster than real-time, while the accuracy loss was comfortably within the 5% tolerance levels for the governing outputs, including crank angle resolved in-cylinder pressure. The grid-resolved simulation was obtained with four times fewer flow components and internal discretization length of 100% and 150% of the cylinder bore for intake and exhaust components respectively. The balance between predictivity, accuracy and real-time surplus, was ultimately more favorable than in state of the art automotive applications and enables exploring further coupling with semi-predictive emission sub-models. The real-time capable FRM is considered applicable in hardware-in-the-loop simulation, and this application is scheduled in a follow-up project.©2023 IMechE. Published by Sage Publications. The article is protected by copyright and reuse is restricted to non-commercial and no derivative uses. Users may also download and save a local copy of an article accessed in an institutional repository for the user's personal reference. Article reuse guidelines: sagepub.com/journals-permissions, DOI: 10.1177/14680874221106168 journals.sagepub.com/home/jerfi=vertaisarvioitu|en=peerReviewed

Thermo-kinetic multi-zone modelling of low temperature combustion engines

Many researchers believe multi-zone (MZ), chemical kinetics–based models are proven, essential toolchains for development of low-temperature combustion (LTC) engines. However, such models are specific to the research groups that developed them and are not widely available on a commercial nor open-source basis. Consequently, their governing assumptions vary, resulting in differences in autonomy, accuracy and simulation speed, all of which affect their applicability. Knowledge of the models´ individual characteristics is scattered over the research groups´ publications, making it extremely difficult to see the bigger picture. This combination of disparities and dispersed information hinders the engine research community that wants to harness the capability of multi-zone modelling. This work aims to overcome these hurdles. It is a comprehensive review of over 120 works directly related to MZ modelling of LTC extended with an insight to primary sources covering individual submodels. It covers 16 distinctive modelling approaches, three different combustion concepts and over 60 different fuel/kinetic mechanism combination. Over 38 identified applications ranging from fundamental-level studies to control development. The work aims to provide sufficient detail of individual model design choices to facilitate creation of improved, more open multi-zone toolchains and inspire new applications. It also provides a high-level vision of how multi-zone models can evolve. The review identifies a state-of-the-art multi-zone model as an onion-skin model with 10–15 zones; phenomenological heat and mass transfer submodels with predictive in-cylinder turbulence; and semi-detailed reaction kinetics encapsulating 53-199 species. Together with submodels for heat loss, fuel injection and gas exchange, this modelling approach predicts in-cylinder pressure within cycle-to-cycle variation for a handful of combustion concepts, from homogeneous/premixed charge to reactivity-controlled compression ignition (HCCI, PCCI, RCCI). Single-core simulation time is around 30 minutes for implementations focused on accuracy: there are direct time-reduction strategies for control applications. Major tasks include a fast and predictive means to determine in-cylinder fuel stratification, and extending applicability and predictivity by coupling with commercial one-dimensional engine-modelling toolchains. There is also significant room for simulation speed-up by incorporating techniques such as tabulated chemistry and employing new solving algorithms that reduce cost of jacobian construction.© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Real-time predictive model for reactivity controlled compression ignition marine engines

Model-based design is proven to be essential for the development of control systems. This paper presents a real-time predictive control-orientated model (COM) for low-temperature combustion (LTC), dual-fuel, reactivity-controlled compression ignition (RCCI) engines. A comprehensive model-based design methodology must be capable of constructing an RCCI control-orientated model with high accuracy, high noise immunity, good response, predictivity in governing mechanisms, and low computation time. This work attains all of these for the first time for a cutting-edge RCCI marine engine. The real-time model (RTM) captures the key sensitivities of RCCI by controlling the total fuel energy and the blend ratio (BR) of two fuels, while also considering uncertainties arising from variations of inlet temperature and the gas exchange process. It provides not only the cycle-wise combustion indicators but also the crank-angle-based cylinder pressure trend. The RTM is derived by direct linearisation of a physics-based model and is successfully validated against experimental results from a large-bore, RCCI engine and the previously acknowledged UVATZ (University of Vaasa Advanced Thermo-kinetic Multi-zone) model. Validation covers both steady-state and transient modes. With high accuracy in several case studies representing typical load transients and air-path disturbance rejection tests, the model predicts maximum cylinder pressure (Pmax), crank-angle of 5 % burnt (CA5), crank-angle of 50 % burnt (CA50) and indicated mean effective pressure (IMEP) with root means square (RMS) errors of 8.6 %, 0.3 %, 0.6 %, and 0.6 % respectively. The average simulation time without any code optimisation is around 5 ms/cycle, offering sufficient real-time surplus to incorporate a semi-predictive emission submodel within the current approach.© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Operational Profile Based Optimization Method for Maritime Diesel Engines

This paper presents an approach to a new engine calibration method that takes the engine’s operational profile into account. This method has two main steps: modeling and optimization. The Design of Experiments method is first conducted to model the engine’s responses such as Brake Specific Fuel Consumption (BSFC) and Nitrogen Oxide ( NOx ) emissions as the functions of fuel injection timing, common rail pressure and charged air pressure. These response surface models are then used to minimize the fuel consumption during a year, according to a typical load profile of a ferry, and to fulfill the NOx limits set by International Maritime Organization (IMO) regulations, Tier II, test cycle E2. The Sequential Quadratic Programming algorithm is used to solve this minimization problem. The results showed that the fuel consumption can be effectively reduced with the flexibility to trade it off with the NOx emissions while still fulfilling the IMO regulations. In general, this method can decrease the manual calibrationeffort and improve the engine’s performance with a tailored setting for individual operational profiles.Peer reviewe

Simulation Environment for Analysis and Controller Design of Diesel Engines

Novel combustion concepts and multi injection cylinder-wise control methods are needed in large marine diesel engines for increased performance and to reduce the green house gas emissions. Even though diesel technology in cars might be reducing there is no replacement of dual fuel diesel technology in large marine engines to be seen in the near future. The paper discusses a rapid grey-box modelling technique, which can be used to predict cylinder pressure and heat release in engine cylinders. The model can be used to design effective cylinder-wise control algorithms which increase the engine performance and save fuel under constraint of emissions.Peer reviewe

Model-based on-board post-injection control development for marine diesel engine

Funding Information: Funding information: This work is part of the INTENS (Integrated Energy Solutions to Smart and Green Shipping) project. The authors would like to express their gratitude to Business Finland for funding support. Publisher Copyright: © 2021 Xiaoguo Storm et al., published by De Gruyter.The increasing demands for reducing fuel consumption and emissions in contemporary technology solutions lead to the use of more sensors, actuators, and control applications. With this increasing engine complexity, the feedback design is complex due to the coupling between inputs and combustion parameters. To be able to design the controller systematically, model predictive control (MPC) comes to the scope because of its advantages in the design of multi-input multi-output (MIMO) systems, especially with its constraints handling ability and performance in simultaneously optimizing the engine fuel efficiency and emission reduction. Multi-injection is one of the promising techniques for achieving better engine performance. In this work, post-injection control is implemented utilizing MPC MIMO strategy with the target of exploring the possibility of reducing emissions and improving engine efficiency by controlling post-injection duration and injection timing. The workflow of the MPC controller design from control-oriented model (COM) establishing to MPC problem formation and solution methodology is discussed in this work. Moreover, one contribution from this work is the different implementation angle when compared with the state-of-the-art approaches, where the MPC controller is implemented purely by Matlab Simulink to enable the rapid control prototyping design. The simulation result demonstrated the ability of the controller's tracking performance and showed a preliminary step towards the nonlinear combustion model-based multi-injection MPC design. The systematic model-based controller framework developed in this work can be applied to other control applications and enables a fast path from design to test.Peer reviewe

Model predictive control for a multiple injection combustion model

In this work, a model predictive controller is developed for a multiple injection combustion model. A 1D engine model with three distinct injections is used to generate data for identifying the state-space representation of the engine model. This state-space model is then used to design a controller for controlling the start of injection and injected fuel mass of the post injection. These parameters are used as inputs for the engine model to control the maximum cylinder pressure and indicated mean effective pressure.Peer reviewe

Low Temperature Combustion Modeling and Predictive Control of Marine Engines

The increase of popularity of reactivity-controlled compression ignition (RCCI) is attributed to its capability of achieving ultra-low nitrogen oxides (NOx) and soot emissions with high brake thermal efficiency (BTE). The complex and nonlinear nature of the RCCI combustion makes it challenging for model-based control design. In this work, a model-based control system is developed to control the combustion phasing and the indicated mean effective pressure (IMEP) of RCCI combustion through the adjustments of total fuel energy and blend ratio (BR) in fuel injection. A physics-based nonlinear control-oriented model (COM) is developed to predict the main combustion performance indicators of an RCCI marine engine. The model is validated against a detailed thermo-kinetic multizone model. A novel linear parameter-varying (LPV) model coupled with a model predictive controller (MPC) is utilized to control the aforementioned parameters of the developed COM. The developed system is able to control combustion phasing and IMEP with a tracking error that is within a 5% error margin for nominal and transient engine operating conditions. The developed control system promotes the adoption of RCCI combustion in commercial marine engines