Nonlinear Dynamic Model for Parameter Estimation of Li-Ion Batteries Using Supply–Demand Algorithm

El‐Sehiemy, Ragab A.; Hamida, Mohamed Assaad; Elattar, Ehab E.; Shaheen, Abdullah M.; Ginidi, Ahmed

doi:10.3390/en15134556

Cited by 19 publications

(8 citation statements)

References 48 publications

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“…Unlike other models, emission factors are calculated as a result of the kinematics of vehicle movement in the modelled area. This approach to calculating emissions is contained in three steps [78,79]:…”

Section: Macroscopic Emission Modelsmentioning

confidence: 99%

Vehicle Emission Models and Traffic Simulators: A Review

Mądziel¹

2023

Preprint

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Accurate estimation of vehicle emissions is essential and can be helpful in the decision-making process. Thanks to calculation methods, it is possible to accurately estimate the emissions that result from driving a car and to determine their impact on, for example, the health of pedestrians who are on the pavement near an arterial road. Recent years have seen an increase in the use and importance of emission models, as well as vehicle traffic simulation models. Increasingly, emission models are being combined with traffic simulation models, as it is not practical to actually measure the on-road emissions of an entire fleet of vehicles over a given stretch of road. This paper provides an overview of the selected work on the topic of emission modelling and vehicle traffic simulation models. The models are distinguished according to their respective scales of accuracy, i.e., micro, meso, and macro. Selected work combining emission and traffic simulation models is also presented, as well as development trends in the field. In particular, the paper also highlights the fact of proper calibration of vehicle traffic simulation models in order to obtain the most reliable vehicle emissions results from computational models. The review of the works carried out may be helpful for future projects concerning the use of simulation tools for transport and environmental decision-makers in the area of arterial roads.

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Section: Macroscopic Emission Modelsmentioning

confidence: 99%

Vehicle Emission Models and Traffic Simulators: A Review

Mądziel¹

2023

Preprint

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“…Following the determination of all individuals' grades, a roulette wheel selection process [36] is used to choose an alternative by including a high probability of getting a high grade (YA FDBM ). As a result, the decomposition step stated in Equation ( 19) is improved by combining the FDBM:…”

Section: Proposed Maea With Fdbmmentioning

confidence: 99%

An Improved Artificial Ecosystem Algorithm for Economic Dispatch with Combined Heat and Power Units

et al. 2022

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The most effective use of numerous Combined Heat and Power Units (CHPUs) is a challenging issue that requires strong approaches to handle the Economic Dispatch (ED) with CHPUs. It aims at minimizing the fuel costs by managing the Power-Only Units (POUs), CHPUs, and Heat-Only Units (HOUs). The transmission losses are also integrated, which increases the non-convexity of the ED problem. This paper proposes a Modified Artificial Ecosystem Algorithm (MAEA) motivated by three energy transfer processes in an ecosystem: production, consumption, and decomposition. The MAEA incorporates a Fitness Distance Balance Model (FDBM) with the basic AEA to improve the quality of the solution in non-linear and multivariate optimization environments. The FDBM is a selection approach meant to find individuals which will provide the most to the searching pathways within a population as part of a reliable and productive approach. Consequently, the diversity and intensification processes are carried out in a balanced manner. The basic AEA and the proposed MAEA are performed, in a comparative manner considering the 7-unit and 48-unit test systems. According to numerical data, the proposed MAEA shows a robustness improvement of 97.31% and 96.63% for the 7-unit system and 46.03% and 60.57% for the 48-unit system, with and without the power losses, respectively. On the side of convergence, based on the average statistics, the proposed MAEA shows a considerable improvement of 47% and 43% of the total number of iterations for the 7-unit system and 13% and 20% of the total number of iterations for the 48-unit system, with and without the power losses, respectively. Thus, the suggested MAEA provides significant improvements in the robustness and convergence properties. The proposed MAEA also provides superior performance compared with different reported results, which indicates a promising solution methodology based on the proposed MAEA.

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“…Fuel cells were mathematically represented where SDBT [5], LST [6] and GTT [7] were adopted to adequately estimate the PEMFC parameters including the maximum current density, membrane thickness, membrane preparation parameter, parametric coefficient, cell connection resistance and empirical coefficient, respectively. Batteries were mathematically represented [8] where the generic equivalent circuitry modeling is built with a series of RC component parts designated by RC-model [9]. This comparable RC group is regarded as a relaxation portion to alleviate the difficulty of extracting the battery characteristics, whereas the state space model for battery dynamics was represented [10].…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification of Solar Photovoltaic Systems Using an Augmented Subtraction-Average-Based Optimizer

Moustafa

2023

Eng

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Solar photovoltaic system parameter identification is crucial for effective performance management, design, and modeling of solar panel systems. This work presents the Subtraction-Average-Based Algorithm (SABA), a unique, enhanced evolutionary approach for solving optimization problems. The conventional SABA works by subtracting the mean of searching solutions from the position of those in the population in the area of search. In order to increase the search capabilities, this work proposes an Augmented SABA (ASABA) that incorporates a method of collaborative learning based on the best solution. In accordance with manufacturing, the suggested ASABA is used to effectively estimate Photovoltaic (PV) characteristics for two distinct solar PV modules, RTC France and Kyocera KC200GT PV modules. Through the adoption of the ASABA approach, the simulation findings improve the electrical characteristics of PV systems. The suggested ASABA outperforms the regular SABA in terms of efficiency and effectiveness. For the R.T.C France PV system, the suggested ASABA approach outperforms the traditional SABA technique by 90.1% and 87.8 for the single- and double-diode models, respectively. Also, for the Kyocera KC200GT PV systems, the suggested ASABA approach outperforms the traditional SABA technique by 99.1% and 99.6 for the single- and double-diode models, respectively. Furthermore, the suggested ASABA method is quantitatively superior to different current optimization algorithms.

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Nonlinear Dynamic Model for Parameter Estimation of Li-Ion Batteries Using Supply–Demand Algorithm

Cited by 19 publications

References 48 publications

Vehicle Emission Models and Traffic Simulators: A Review

Vehicle Emission Models and Traffic Simulators: A Review

An Improved Artificial Ecosystem Algorithm for Economic Dispatch with Combined Heat and Power Units

Parameter Identification of Solar Photovoltaic Systems Using an Augmented Subtraction-Average-Based Optimizer

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