Disassembly Sequence Optimization of Lithium Battery Pack Based on Priority Constraint Graph

Abstract

Abstract With the rapid development of the new energy vehicle power industry, the power system of automobiles is about to usher in a wave of retirement. At present, most of power lithium battery packs are disassembled violently, which lack a reasonable disassembly order. This causes a waste of time and cost during the disassembly process. Some harmful parts will also pollute the environment. In order to improve the disassembly efficiency of retired lithium-ion battery packs, the disassembly sequence planning problem (DSP) based on priority constraint graph is studied in this paper. After analyzing disassembly characteristics, the priority constraint graph is constructed as the constraint matrix. Considering the disassembly efficiency, a mathematical model is established to optimize the direction and the number of tool changes. An improved Simulated Annealing Particle Swarm Optimization (SA-PSO) algorithm is designed, which is to update the disassembly sequence by the population update method. The particles are assisted to jump out of the local optimum by the Metropolis criterion of SA algorithm. An adaptive method is proposed for the PSO inertia weight ω. In order to verify the validity of the model and algorithm, an example is introduced to compare SA-PSO with PSO and SA algorithm. The results show that the improved algorithm performs well in the evaluation index of fitness. The convergence rate is fast and more stable.