Research On Disassembly Sequence Planning For Automotive Traction Batteries

Accelerating the transition to vehicle electrification is one of the important initiatives of governments to achieve "carbon neutrality" in road traffic.As one of the expensive components of electric vehicles,automotive traction batteries(ATBs)have a limited service life.A large number of retained ATBs contain huge mineral resources and can become a source of pollution if they are not recycled properly.The recycling of end-of-life(EOF)ATBs,first cascade utilizing the batteries to extend their service life and then extracting rare metal materials for the production of new batteries,can promote the development of a circular economy and is one of the ways to achieve carbon emission reduction.Disassembly is particularly important as a necessary part of battery cascade utilization and material utilization.Effective disassembly sequence planning(DSP)can improve disassembly efficiency,resource utilization and dismantling profitability.In recent decades,finding the optimal disassembly sequence for retired products has been a popular topic studied by many research scholars.In this paper,we take ATBs as the research object,focus on the disassembly information model,disassembly sequence generation method and sequence optimization,and propose a new disassembly information model and the corresponding DSP methods,mainly including the following research contents:(1)A disassembly ontology and semantic model is proposed to address the problem that the existing disassembly information model is difficult to semantically describe the constraint relationships of parts containing destructive connection methods in ATBs.Based on the characteristics of ATBs such as diverse specifications and complex structures,the disassembly operation model is determined and the common non-destructive and destructive connection methods between parts are revealed by systematically analyzing the composition structure and disassembly process of ATBs.The assembly characteristics of ATBs are analyzed and the parts of ATBs are redefined so that they apply to the description of part constraints with destructive connection methods.The mapping relationship between connection methods,assembly constraints and disassembly order is analyzed,and a set of disassembly constraint matrices based on the assembly constraint relationship and connection relationship of ATBs are constructed based on the fixing parts and functional parts.Through the class,object and data attributes of the ontology,this set of disassembly constraint matrices and disassembly instances are described semantically,and the disassembly ontology and semantic model are constructed to provide the theoretical and methodological basis for the generation and optimization of the disassembly sequence of ATBs.(2)A Case-based reasoning/Rule-based reasoning(CBR/RBR)disassembly sequence generation method is proposed for the problem of applying manual disassembly knowledge and experience to rapidly generate disassembly solutions.Based on the disassembly constraint matrices,the disassembly feasibility determination rules for functional parts and fixing parts are developed.By using the determination rules and introducing environmental and safety constraints,an asynchronous-parallel-local destructive-hybrid disassembly sequence generation method with priority normal direction disassembly is designed.The disassembly case library is constructed by the disassembly semantic model,the CBR-based disassembly sequence generation method is presented,and the disassembly scheme of matching cases can directly guide the ATB disassembly.The disassembly rule base is constructed by the designed local destructive disassembly rules and disassembly tool selection rules,and the RBR-based multi-person asynchronous and human-robot asynchronous disassembly sequence generation methods are proposed.For the problem of many influencing factors and complex hierarchical association of human-robot disassembly task assignment,a human-robot disassembly task assignment method based on part automation potential assessment is proposed to achieve reasonable human-robot disassembly task assignment.(3)The disassembly sequence optimization problem is studied for two disassembly modes: multi-person asynchronous and human-robot asynchronous.Based on the full analysis of the disassembly time composition of individual part,a waiting strategy is introduced,a mathematical optimization model based on the disassembly time of individual ATB is proposed,and an improved genetic algorithm is used to solve the near-optimal disassembly scheme.Taking batch disassembly of ATBs as the starting point,the mathematical optimization model based on the fatigue-recovery model is constructed considering the influence of personnel fatigue on the disassembly efficiency of human-robot and the total time of batch disassembly as the optimization objective.The approximate optimal disassembly solutions of the two optimization models are solved by a case,and the influence of the maximum fatigue level on the mathematical optimization model based on the fatigue-recovery model is analyzed using numerical experiments.(4)Around the above work,a prototype system of DSP cloud service is developed to realize the integrated application of the above models and methods.The requirements and functions of the system are analyzed,the architecture of the system is constructed,the main functional modules of the system are studied,and the application of the system is illustrated with case studies.