مقاله انگلیسی رایگان در مورد به کارگیری از WASPAS فازی برای گزینش جایگاه ریکاوری باتری‌ لیتیوم یونی – الزویر 2022

Abstract

     With the emergence of battery-based electric vehicles, transportation systems gradually leave using fossil fuel-based combustion engines. Due to their reasonable performance, Lithium-ion batteries have become one of the major batteries used for electric vehicles. Although these batteries are being used in most companies, their high production cost, rare raw material, and short life cycle have raised important incentives for their recovery process. However, locating a recovery center for end-of-life Lithium-ion batteries is a multi-aspect decision making problem influenced by many criteria. For this purpose, a novel integrated decision-making model is developed based on Measuring Attractiveness by a Categorical Based Evaluation TecHnique (MACBETH) for calculating the criteria weights and Weight Aggregated Sum Product ASsessment (WASPAS) methods under the fuzzy environment with Dombi norms for evaluating the alternatives to address recovery center location selection problem considering technical as well as environmental, economic, and social aspects. To show the reliability and applicability of the developed method, a real-world case study in Istanbul is investigated. The developed method is used to evaluate six potential locations for the possible establishment of a recovery center. Results showed that Tuzla district is the most suitable location for opening a recovery center for end-of-life Lithium-ion batteries. Tuzla is in a very good position in terms of proximity to suppliers, transportation and location. To illustrate the robustness of the obtained results, extensive sensitivity analysis tests are performed.

Introduction

     Electric vehicles (EVs) are an appealing solution for the decarburization of the transportation sector (Romero-Ocaño et al., 2022, Zhang et al., 2020). It is estimated that more than 125 million EVs will be on the road worldwide by 2030 (Hua et al., 2020). Lithium-ion batteries (LiBs) have exponential growth and a key portion of industry investments (Chen et al., 2019, Cui et al., 2022). An automobile Lithium-ion battery (ALiB) is a major component of an EV (Pelletier et al., 2017, Ramoni and Zhang, 2013). ALiBs provide the required energy storage for EVs due to the superiority of high energy density, high output voltage, low self-discharge rate, and long cycling life (Tang et al., 2019, Wang et al., 2022). They are composed of a cathode, an anode, an electrolyte, and a separator (Olivetti, Ceder, Gaustad, & Fu, 2017). The useful lifetime of ALiBs is 120,000–240,000 km (Onat, Kucukvar, Tatari, & Zheng, 2016).

     Approximately 11 million ALiBs are expected to be sold worldwide by 2020 (Li et al., 2018; Alamerew & Brissaud, 2020). Due to the degradation in capacity and quality, the service life of these complex multiple material products, which belong to class 9 of dangerous goods, is 5–10 years (Li et al., 2018; Chen et al., 2019, Tang et al., 2019, Alamerew and Brissaud, 2020, Li et al., 2020). ALiB is replaced when the capacity has reached 70–80 % of its initial capacity (Alamerew and Brissaud, 2020, Hua et al., 2020, Ramoni and Zhang, 2013).

Conclusions

     The emergence of EVs has been a noticeable point for transportation systems to transform from fossil fuel-based vehicles to cleaner vehicles which require lower energy costs and also produce lower negative environmental, economic, and social impacts. The utilization of ALiBs is of great importance for EVs, but more and more valuable resources are being depleted without appropriate recovery. Therefore, countries should consider establishing recovery centers for ALiBs as soon as possible. However, locating a recovery center is a complex and multi-aspect decision-making problem. For this purpose, we developed a novel decision-making approach based on the MACBETH-D-WASPAS model under the fuzzy environment. The proposed integrated fuzzy decision-making approach empowers experts in the field of LiB management to enhance their decision-making capabilities and select the most suitable location for an EoL ALiB recovery center. Besides, the real-life case study of Istanbul is provided to show the feasibility and applicability of the developed methodology for solving the recovery center location selection problem. Results showed that Sariyer and Büyükçekmece are top first and second locations that a recovery center for an EoL ALiB recovery center. On the other hand, results pointed out that Ümraniye is the least preferred location for establishment of an EoL ALiB recovery center.