Alejo-Reyes, Avelina

Main Affiliation

Preferred name

ORCID

0000-0001-9903-7476

Researcher ID

EKT-0166-2022

Scopus Author ID

57202425879

Now showing 1 - 10 of 36

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Data-driven modeling of proton-exchange membrane fuel cell stacks
(Elsevier BV, 2025-01)
Edgar Silva-Vera
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Jesus E. Valdez-Resendiz
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Jesse Y. Rumbo-Morales
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Optimized energy conversion in fuel cells using the 2P6O converter with small inductors and capacitors
(Elsevier BV, 2025-03)
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Jesus E. Valdez-Resendiz
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Victor M. Sanchez
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Alma Rodriguez
Renewable energy sources are critical to addressing global energy challenges, offering sustainable alternatives to fossil fuels. Among these, fuel cells are gaining attention with applications spanning transportation, stationary power, and portable devices. Power electronics play a vital role in enabling the integration of fuel cells into practical systems. Specifically, DC-DC converters are indispensable for transforming energy, regulating voltage levels, and optimizing the performance of the systems. This paper presents the design and evaluation of an energy conversion system for a Fuel Cell Stack based on a recently introduced DC-DC converter. The two-phase six-order (2P6O) has shown to be a feasible converter with a good performance. In this article, the 2P6O converter was designed to convert the electrical energy from a fuel cell stack. The main objective of this study is to explore the performance of the 2P6O converter in the discussed application. Using a comparative analysis approach, the 2P6O converter was integrated into a standard fuel cell system, and its operation and storage demands were meticulously analyzed. The findings indicate that the system that incorporates the 2P6O converter requires less energy storage; specifically in the study, the 2P6O converter required 74% of the energy stored in inductors compared to the multiphase boost converter, a very competitive topology and 57% of the energy stored in capacitors. Reducing 26% of the stored energy in inductors and 43% of the energy stored in capacitors compared to the multiphase boost converter. Compared to the traditional boost and the multiphase boost, experimental results are provided.
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Algorithms for Supplier Selection and Order Quantity Allocation
(2020)
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Mendoza Andrade, Abraham
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Olivares Benitez, Elías
Supply chain management is particularly important because of its influence on a compan\¶s profitabilit\ and competitiYeness. Among the different actiYities inYolYed in supply chain management, purchasing decisions, supplier selection, and order quantity allocation have a direct impact on the cost of the produced items. The cost function usually deals with non-linear equation systems with an infinite number of possible solutions. The result is an optimal inventory policy with a minimum cost per time unit. This research addresses the supplier selection and order quantity allocation problem. The objective is to allocate the corresponding order quantities over time to the selected suppliers, while minimizing inventory and transportation costs, simultaneously. In selecting suppliers, two feasibility constraints are considered: capacity and quality (perfect rate). Typically, in the literature, the acceptable perfect quality rate of raw materials is ensured with a mathematical inequality in the model constraints. Therefore, this research first addresses the desired perfect rate by including it as part of the order cycle parameters calculation and not as an individual constraint. The main advantages of doing so are: (i) it leads to lower-cost solutions compared to previously proposed literature, (ii) it effectively faces the so-called low perfect rate situations, by providing feasible solutions when the perfect rate of suppliers is smaller than the minimum perfect-rate required by the customer. A sensitivity analysis was carried out on the proposed model to analyze the effect of some parameters on the total cost per time unit. Results showed that transportation costs have an important effect on the order quantity and that the price levels do not necessarily affect the number of purchased units. Hence the importance of considering transportation costs when making order quantity allocation decisions. Another challenge of the problem under study is that the model is non-linear and has an infinite number of possible solutions because of the continuous nature of the variables. Therefore, there is a need from the scientific and industry communities to find solutions in an efficient and timely manner. Former studies introduced limits to the length of the order cycle or to the number of orders in the order cycle in order to obtain a solution using commercial software. However, computers still take many hours or days to provide optimal solutions, if at all. Therefore, second, this research applies different metaheuristic algorithms to solve the problem, namely: particle swarm optimization (PSO), genetic algorithm (GA), and differential evolution (DE). With these algorithms, a larger solution space can be explored while getting a solution in the order of seconds; this allows cheaper solutions to be found. PSO, GA, and DE are well known metaheuristic algorithms in the optimization field and have been used to solve lot-sizing, and supplier selection problems. New metaheuristic methods are commonly proposed for particular circumstances, for example, converging to an optimal solution faster than other strategies. A recently proposed metaheuristic algorithm, the Grey Wolf Optimizer (GWO), was explored in this research. The algorithm was modified and adapted to the supplier selection and order quantity allocation problem when the amount of decision variables is too large. The improved GWO method, called iGWO, includes weighted factors and a displacement vector to promote the exploration of the search strategy avoiding the use of unfeasible solutions. The iGWO was tested and results showed that, in addition to obtain optimal solutions, it performed a better search strategy, finding feasible solutions in all instances of the tested problem. Finally, based on the knowledge acquired through the previous contributions, a heuristic algorithm to solve the problem under study is proposed. This heuristic algorithm allows to extend the explored solution space to an exceptionally large limit. The solutions obtained with the proposed heuristic algorithm were compared against the solutions obtained with PSO and DE. Two numerical examples are solved. In the first one, it is shown that the proposed heuristic performed best compared to other solutions previously published in the literature, both in terms of computational time and total cost. In the second numerical example, larger instances were studied. Our findings show that the proposed heuristic was able to find a feasible solution, while PSO and DE were unable to find a solution. Therefore, the proposed heuristic does not just lead to lower total cost solutions, but it also performs a more exhaustive search in shorter computational times for larger instances of the problem.
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Inventory replenishment decisions for the supplier selection problem considering transportation freight rates and quality
(2018)
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4 2
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Quadratic Boost Converter with Optimized Switching Ripple Based on the Selection of Passive Components
(2024)
Edgar D. Silva-Vera
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Jesus E. Valdez-Resendiz
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This work introduces a boost converter with quadratic gain. Its main advantage compared to well-known similar quadratic boost converters is that it requires capacitors with a relatively small capacitance and inductors with small inductance, leading to a reduction in the size or stored energy while performing a power conversion of similar power rating and the same switching ripples in both the input current and the output voltage. It is inspired by the recently introduced ISB converter and uses a specific PWM method. This results in achieving switching ripple constraints while using smaller energy storage elements (capacitors and inductors). The updated converter offers the same voltage gain compared to the conventional quadratic boost topology with the benefit of compact component sizes. While it has more passive elements, they are of reduced size. An analysis of energy storage revealed that this new converter uses only half the energy in inductors and 14% in capacitors when compared to specific design parameters.
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Inventory replenishment decision model for the supplier selection problem using metaheuristic algorithms
(2020)
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Scopus© Citations 17 9 1
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A Mathematical Model for an Inventory Management and Order Quantity Allocation Problem with Nonlinear Quantity Discounts and Nonlinear Price-Dependent Demand
(2023)
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Erik Cuevas
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<jats:p>This article focuses on solving the order quantity allocation problem for retailers. It considers factors such as quality constraints, nonlinear quantity discounts, and price-dependent demand. By formulating it as a nonlinear maximization problem, the article aims to find the best combination of suppliers and order quantity out of infinite solutions to maximize the retailer’s profit. The main contribution of this research is a new mathematical model that can solve the problem of quality constraint and demand in a single step. This problem is complex due to the number of equations, their nonlinear nature, and the various trade-offs given by the market. Additionally, this research considers demand as output and includes price-dependent demand, which is more realistic for retailers. The proposed model was tested using an example from the recent literature and showed better results than the previously published best solution regarding profit maximization.</jats:p>
47 1
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Statistical Analysis of Lean Construction Barriers to Optimize Its Implementation Using PLS-SEM and PCA
(2024)
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<jats:p>The construction industry performs many tasks scheduled and related to other activities. Companies must optimize their operations, increase efficiency, eliminate waste, and deliver better products to their customers. As a result, this study aims to identify the main challenges associated with the implementation of the Lean Construction model in small and medium-sized construction companies and optimize the implementation of this process using statistically-focused mathematical models. This study was conducted using the partial least squares (PLS-SEM) method and also carried out the principal component analysis to optimize Lean barriers so that they can be properly implemented in the construction industry. The most important obstacles are displayed, as well as the relationships with other factors. Significant relationships have been discovered between the barriers to Lean construction adoption, especially with regard to corporate culture, communication, training, leadership, and the influence of mentality on business and employee adaptability. Construction executives and managers can make well-informed policy and strategic decisions by having a thorough understanding of the main barriers to Lean implementation. This information enables them to focus on the implementation of Lean technologies in projects, to increase market competitiveness, reduce waste and enhance overall work efficiency.</jats:p>
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An Evolutionary Algorithm-Based PWM Strategy for a Hybrid Power Converter
(2020)
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Erik Cuevas
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Francisco Beltran-Carbajal
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<jats:p>In the past years, the interest in direct current to direct current converters has increased because of their application in renewable energy systems. Consequently, the research community is working on improving its efficiency in providing the required voltage to electronic devices with the lowest input current ripple. Recently, a hybrid converter which combines the boost and the Cuk converter in an interleaved manner has been introduced. The converter has the advantage of providing a relatively low input current ripple by a former strategy. However, it has been proposed to operate with dependent duty cycles, limiting its capacity to further decrease the input current ripple. Independent duty cycles can significantly reduce the input current ripple if the same voltage gain is achieved by an appropriate duty cycle combination. Nevertheless, finding the optimal duty cycle combination is not an easy task. Therefore, this article proposes a new pulse-width-modulation strategy for the hybrid interleaved boost-Cuk converter. The strategy includes the development of a novel mathematical model to describe the relationship between independent duty cycles and the input current ripple. The model is introduced to minimize the input current ripple by finding the optimal duty cycle combination using the differential evolution algorithm. It is shown that the proposed method further reduces the input current ripple for an operating range. Compared to the former strategy, the proposed method provides a more balanced power-sharing among converters.</jats:p>
Scopus© Citations 3 4 1
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Power quality improvement by interleaving unequal switching converters
(2016)
Arias-Angulo Juan Pedro
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Beltran-Carbajal Francisco
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Haro-Sandoval, Eduardo
Scopus© Citations 7 41 1

Alejo-Reyes, Avelina

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