Environment-oriented disassembly planning for end-of-life vehicle batteries based on an improved northern goshawk optimisation algorithm

Due to environmental pollution and resource shortages, the electric vehicle industry has been developing swiftly, and the market demand for batteries, as an essential part of electric vehicles, has also surged. Proper disassembly of end-of-life vehicle batteries (ELV batteries) is necessary to achieve the integrity and closure of their life cycle, promote the development of green remanufacturing, effectively reduce the pollution of the environment caused by metal ion leakage, and reduce people's dependence on natural resources to a certain extent. To schedule the disassembly operations of ELV batteries more rationally and further promote their disassembly quality and efficiency, this paper proposes a dual-objective disassembly sequence planning (DSP) optimisation model, which aims to minimise the hazard index and energy cost during ELV battery disassembly operations. Since the proposed model is a complex NP-hard optimisation problem, this study develops an efficient metaheuristic algorithm for solving this model based on the northern goshawk optimisation algorithm. The main algorithm adds two types of discrete recombination operators and a local search operator. At the same time, the predatory behaviour of the goshawk is optimised by combining the characteristics of the disassembly sequence planning problem to improve its performance. Finally, the disassembly of the battery of a Tesla Model 1 is used as a case study to demonstrate the effectiveness and feasibility of the proposed method.