Collection policy analysis for retired electric vehicle batteries through agent-based simulation. (1st January 2023) - Tang, Yanyan; Tao, Yuan; Li, Yaoming
Abstract: With the massive deployment of Electric Vehicles (EVs), a large number of lithium-ion batteries are reaching retirement age, attracting great concerns about the industrial sustainability. Currently, several incentive measures are being introduced and expected to address this waste management challenge, but the exact effects remain unclear. Therefore, an agent-based model of EV battery collection system is established in this study, which characterizes the heterogeneous interactive relationship, behavior rules and decision-making function of three main agents including residents, formal and informal collection enterprises. Eventually, the policy implementation effects are quantitatively evaluated. The results show that: (i) the publicity policy with the strongest implementation level leads to a 38.11% increase in the collection rate, which is defined as the ratio of the number of battery packs collected through formal channels to the total; (ii) the collection price subsidy policy of 80 RMB/kWh improves the collection rate by 109.87%; (iii) with the target level and intensity level set at 50 kWh and 80 RMB/kWh, the collection target policy enhances the market share of formal collection enterprises by 1.08%; (iv) with the combination of these three collection policies, the policy mix enhances the collection rate by 3.81 times, which is greater than the implementation effect of any single policy. In sum, this research will promote the sustainable supply chain management of EV batteries. With a further model extension, it can also provide decision support for the policy-making of more countries.