Abstract
In 2018-2019, the recall scale of electric vehicles (EVs) in China reached 168,700 units; recalls account for approximately 6.9% of sales volume. There are imperative reasons for electric vehicle batteries (EVBs) recalls, such as mandatory laws or policies, safety and environmental pollution risks, and the high value of EVB echelon use, and thus, it has become increasingly important to reasonably design a reverse logistics (RL) network for an EVB recall. In this study, a multiobjective and multiperiod recall RL network model is developed to minimize safety and environmental risks, maximize the social responsibility and economic benefits, and consider the characteristics of EVBs, including the configuration of key recall facilities and the control of recall flows. The results of this study will help EVB practitioners, relevant departmental policymakers, and others to comprehensively understand the recall of EVBs, strengthen the safety and environmental protection issues in the EVB recall process, and promote the establishment of a safe, green, and sustainable EVB recall RL network.
Highlights
According to the International Energy Agency [1], global EV ownership exceeded 7.2 million units by the end of 2019, and the annual sales of EVs are predicted to reach 80 million units by 2030 in the context of sustainable development
Case Study. is study takes the Shanghai EVB recall as an example and establishes an RL network based on the recall volume of EVBs during the three years. e locations of RL infrastructure such as service outlets, recall sites, recall processing centers, recall transfer centers, and echelon use centers were identified, and the flow directions were determined
Research is study aims to solve the problem of optimizing the configuration of RL network facilities for an EVB recall, which is a key issue of EVB safety risk management and an inevitable requirement in promoting the construction of an ecological and green society
Summary
According to the International Energy Agency [1], global EV ownership exceeded 7.2 million units by the end of 2019, and the annual sales of EVs are predicted to reach 80 million units by 2030 in the context of sustainable development. A report released by China’s General Administration of State Market Regulation [2] shows that 168,700 EVs were recalled in 2018-2019; recalls account for approximately 6.9% of sales volume. China’s Ministry of Industry and Information Technology released a report on the Big Data Safety and Supervision Achievements of the National Supervision Platform for EVs [3], which showed that, from May to August 2019, 58% of vehicles burned, where the cause of the fire was identified, were due to battery problems. Erefore, their safety, environmental protection, and whether they can be effectively recalled and disposed of are a wide concern. In the event of an emergency recall owing to safety or environmental concerns, it is even more important to establish a fast and safe RL network
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