Transactions of the Institute of Measurement and Control

Liu, Xinghua; Li, Xiang; Tian, Jiaqiang; Cao, Hui

doi: 10.1177/01423312211060572pmid: N/A

The carbon capture device can catch CO2 produced by conventional units and coupled with power-to-gas (P2G) operation provides an effective way to reduce the carbon emissions of the integrated energy system (IES). In this paper, a low-carbon economic dispatch is proposed for an integrated electricity-gas system (IEGS) considering carbon capture devices, and the carbon trading mechanism is introduced. Based on the traditional thermal power units, carbon capture devices are installed to form carbon capture power plants (CCPP). Carbon emissions are reduced from the energy supply side via capturing CO2 generated by conventional units. Detailed modeling of IEGS, CCPP, and P2G are performed, respectively. The electricity and natural gas networks security constraints are incorporated into the low-carbon economic dispatch model to minimize carbon transaction costs and system operation costs. Finally, a 4-bus power system/4-node natural gas system is used, for example, analysis. The arithmetic simulation is performed by the YALMIP toolbox of MATLAB. The total costs and CO2 emissions of the three scenarios are compared. The feasibility and validity of the proposed model are verified by the simulated results.

Huin, Xavier; Di Loreto, Michaël; Bideaux, Eric; Benzaoui, Hellal

doi: 10.1177/01423312211029692pmid: N/A

In the context of heavy-duty application, this paper introduces a novel methodology for better defining the specifications of the internal combustion engine (ICE) in plug-in hybrid electric vehicles (pHEVs) with energy management-based evaluation. From mathematical modelling of reference engine static efficiency and maximum torque, parametric transformations are performed to explore alternative engine designs. A coupled optimization problem is formulated as a bi-level form with powertrain optimal energy management based on a combinatorial problem formulation solved by Branch&Bound algorithm in the inner loop and exhaustive evaluation of ICE designs in the outer loop. A detailed transmission losses model and limitations on engine torque response dynamics are included in the optimization problem. The number of engine ignition and shutdown phases are also considered in order to better simulate the powertrain. The results show potential fuel reduction of 2.4% on a regional delivery cycle with zero-emission zones, and are intended to be used as specifications to guide further detailed engine development dedicated to hybrid powertrains.

Chrouta, Jaouher; Farhani, Fethi; Zaafouri, Abderrahmen

doi: 10.1177/01423312211029509pmid: N/A

In the present study, we suggest a modified version of heterogeneous multi-swarm particle swarm optimization (MSPSO) algorithm, that allows the amelioration of its performance by introducing an adaptive inertia weight approach. In order to bring about a balance between the exploration and exploitation characteristics of MSPSO allowing to promote information exchange amongst the subswarms. However, the classical MSPSO algorithm search behavior has not always been optimal in finding the optimal solution to certain problems, which results in falling into local optimum leading to premature convergence. The most advantages of the MSPSO there are easy to implement and there are few parameters to adjust. The inertia weight (w) is one of the most Particle Swarm Optimization’s (PSO) parameters. Controlling this parameter could facilitate the convergence and prevent an explosion of the swarm. To overcome the above limitations, this paper proposes a heterogeneous multi swarm PSO algorithm based on PSO number selection approach centred on the idea of particle swarm referred to as Multi-Swarm Particle Swarm Optimization algorithm with Factor selection strategy (FMSPSO). In the various process implementations of the particle swarm search, different parameter selection strategies are adopted to ameliorate the global search ability. The proposed FMSPSO is able to improve the population’s diversity and better explore the entire feature space. The statistical test and indicators that are reported in the specialized literature demonstrate that the suggested approach is superior in terms of efficiency to nine other popular PSO algorithms in solving the optimization problem of complex problems. The approach suggests that FMSPSO reaches a very promising performance for solving different types of optimization problems, leading eventually to higher solution accuracy.

Wu, Xiaogang; Xia, Yinlong; Du, Jiuyu; Zhang, Kun; Sun, Jinlei

doi: 10.1177/01423312211058563pmid: N/A

High-power-charging (HPC) behavior and extreme ambient temperature not only pose security risks on the operation of lithium-ion batteries but also lead to capacity degradation. Exploring the degradation mechanism under these two conditions is very important for safe and rational use of lithium-ion batteries. To investigate the influence of various charging-current rates on the battery-capacity degradation in a wide temperature range, a cycle-aging test is carried out. Then, the effects of HPC on the capacity degradation at various temperatures are analyzed and discussed using incremental capacity analysis and electrochemical impedance spectroscopy. The analysis results show that a large number of lithium ions accelerate the deintercalation when the HPC cycle rate exceeds 3 C, making the solid electrolyte interphase at the negative surface unstable and vulnerable to destruction, which results in irreversible consumption of active lithium. In addition, the decomposition of electrolyte is significantly promoted when the HPC temperature is more than 30°C, resulting in accelerated consumption of electrode materials and active lithium, which are the main reasons for the capacity degradation of lithium-ion batteries during HPC under various temperatures.

Rodriguez-Torres, Andres; Morales-Valdez, Jesús; Yu, Wen

doi: 10.1177/01423312211021052pmid: N/A

The article deals with the development of active vibration control of seismically-excited building structures. The control scheme is based on an alternative proportional-derived (PD) controller designed based only on the bandwidth of the system, which is an attractive technique for structural vibration suppression purposes and practical motion control solutions. The tuning method is analyzed employing Kharitonov’s theorem and Routh-Hurwitz criteria, which give necessary and sufficient conditions for choosing the two PD range of gains. Based on modal analysis, the system is transformed into a set of decoupled ordinary differential equations to simplify the PD design. An important advantage concerning a classical PD controller is the proposed PD design only uses the natural frequencies, which are relatively easy to estimates around an experimental test. Moreover, the proposed approach does not need frequently tune the gains parameters, so the design procedure is greatly simplified and, the proposed scheme does not need the system parameters, which generally are unknown. This method allows generalizing the controller design for multi-story buildings without modifying the controller structure, by choosing a scalar parameter. The effectiveness of the proposed PD schemes is demonstrated through simulation and experimental results of a reduced scale two-story building prototype.

Chen, Tao; Gao, Ciwei; Hui, Hongxun; Cui, Qiushi; Long, Huan

doi: 10.1177/01423312211057981pmid: N/A

Lithium-ion battery-based energy storage systems have been widely utilized in many applications such as transportation electrification and smart grids. As a key health status indicator, battery performance would highly rely on its capacity, which is easily influenced by various electrode formulation parameters within a battery. Due to the strongly coupled electrical, chemical, thermal dynamics, predicting battery capacity, and analysing the local effects of interested parameters within battery is significantly important but challenging. This article proposes an effective data-driven method to achieve effective battery capacity prediction, as well as local effects analysis. The solution is derived by using generalized additive models (GAM) with different interaction terms. Comparison study illustrate that the proposed GAM-based solution is capable of not only performing satisfactory battery capacity predictions but also quantifying the local effects of five important battery electrode formulation parameters as well as their interaction terms. Due to data-driven nature and explainability, the proposed method could benefit battery capacity prediction in an efficient manner and facilitate battery control for many other energy storage system applications.

Yacef, Fouad; Rizoug, Nassim; Degaa, Laid; Bouhali, Omar; Hamerlain, Mustapha

doi: 10.1177/01423312211058560pmid: N/A

Unmanned aerial vehicles are used today in many real-world applications. In all these applications, the vehicle endurance (flight time) is an important constraint that affects mission success. This study investigates the limitations of embedded energy for a quadrotor aerial vehicle. We consider a quadrotor simple tasked to travel from an initial hover configuration to a final hover configuration. In order to have a precise approximation of the consumed energy, we propose a power consumption model with battery dynamic, motor dynamic, and rotor efficiency function. We then introduce an optimization algorithm to minimize the energy consumption during quadrotor aerial vehicle mission. The proposed algorithm is based on an optimal control problem formulated for the quadrotor model and solved using nonlinear programming. In the optimal control problem, we seek to find control inputs (rotor velocity) and vehicle trajectory between initial and final configurations that minimize the consumed energy during a point-to-point mission. We extensively test in simulation experiments the proposed algorithm under normal and windy weather conditions. We compare the proposed optimization method with a nonlinear adaptive control approach to highlight the saved amount of energy.

Dachraoui, Chaima; Mouelhi, Aymen; Drissi, Cyrine; Labidi, Salam

doi: 10.1177/01423312211040309pmid: N/A

Multiple sclerosis is a chronic neuro-inflammatory disease. Its diagnosis and evaluation require a visual assessment in brain magnetic resonance images. This neurological disease is characterized by its unpredictable evolution. The most common form is relapsing–remitting multiple sclerosis, consisting of episodes of neurological dysfunction remitting with a variable degree of recovery. The underlying mechanisms are still unknown and have no mathematical models to explain this spatial and temporal dissemination. The main objective of this paper is to propose an approach based on chaos theory to define the clinical characteristics for lesion progression, principally its evolution. Previous authors have explored the nervous system by accurately modeling their attractors in the phase space and reproducing a non-linear result. This remains to be compared with chaotic attributes. In this work, multiple sclerosis lesions are treated through modeling and calculating of their degree of evolution. This is a retrospective study of cases collected from the National Institute of Neurology Mongi Ben Hmida. It included 74 patients with an age group ranging from 20 to 72 years. Four clinical trials are properly discussed: unstable cases with active lesions may be described by dynamic and non-linear systems presenting higher chaos value compared to ill patients with inactive lesions. On the other hand, the accuracy of chaos demonstration can be favorably affected by the reduced resolution of magnetic resonance images. Therefore, the interest is in preprocessing to improve the eventual results. High accuracy was achieved for the models discussed in this paper (91.97–85.1%). Accordingly, the suitability and practical usefulness of the ‘simple’ pretreatment to achieve multiple sclerosis classification are demonstrated.

Feliks, Tomasz; Hunek, Wojciech P; Krok, Marek

doi: 10.1177/01423312211050545pmid: N/A

The innovative analytical approach to the minimum-energy design problem of the inverse model control (IMC) state-space structures is presented in this work. Following the recent papers, it should be concluded that the optimal behavior of the IMC strategy cannot longer be associated with the application of the well-known Moore–Penrose minimum-norm inverse. However, the minimum-energy IMC-oriented scheme has only be obtained through heuristic methods. Nevertheless, in the recent authors’ work, it has been proven for the first time that such an issue can be considered in an analytical manner. Yet, the obtained results have only been valid for the second-order state-space systems. Therefore, the motivation instance proposed in the manuscript, confirming the possibility of extending such paradigm to higher-order plants, will certainly contribute to the introduction of the new unified minimum-energy IMC theory canon. Since the nonunique σ and H inverses can successfully be employed in the robustification of the discussed control strategy, they can also be helpful in the case of our essential considerations. Thus, from now on the yet unexplored research area can now be investigated in the analytical manner, what has never been seen before in the modern IMC-originated control theory and practice. The predefined methodology clearly fills the gap in the analytical control design procedures and opens a new chapter in the knowledge related to the well-known and broadly accepted multivariable control canons.

Flores-Flores, Juan Pablo; Martínez-Guerra, Rafael

doi: 10.1177/01423312211032061pmid: N/A

In this work we present a methodology to design dynamical distributed controllers for the synchronization problem of systems governed by partial differential equations of integer and fractional order. We consider fractional systems whose space derivatives are of integer order and time derivatives are of fractional commensurate order. The methodology is based on finding canonical forms by means of a change of variable, such that a distributed controller can be designed in a natural way in the form of a chain of integrators. To study the stability of the integer order closed loop system, we propose to use the spectral and semi-group theory for infinite dimensional Hilbert spaces. On the other hand, the stability criterion previously established by Matignon is used for the stability analysis of the fractional order case. Additionally, we tackle the synchronization problem of multiple systems, which is reduced to a problem of generalized multi-synchronization. To illustrate the effectiveness of the proposed methodology, examples and numerical results are given.