Research On Disassembly Sequence Planning Of Power Battery System Based On Human-Machine Cooperation

With the popularization of new energy vehicles,the power battery system,as the main component of the new energy vehicle,has the characteristics of short life cycle and the presence of harmful substances inside.The green treatment of the power battery system has become a research focus.Disassembly and recycling is an important means for the reuse of waste power battery systems.Due to the wide variety of power battery systems,there is no uniform design standard,and the flexibility of disassembly is relatively high,so the manual disassembly method is mainly used at present,but this method is used for disassembly Some harmful parts may cause health hazards to itself.The robot can solve this problem,and at the same time,it is more efficient to disassemble a single repeated part.Therefore,in view of the flexibility of the power battery during the disassembly process and the batch disassembly requirements,this paper proposes to combine the advantages of humans and robots to conduct an in-depth study on the disassembly sequence planning of the power battery system.First,take the new energy power battery system as the research object,summarize the existing power battery system structure,then analyze the characteristics of the selection and disassembly methods of disassembly tools,and summarize the dismantling process of the power battery system,and finally combine the waste power battery The status information of the system disassembly,and the framework of the disassembly process of the power battery system is proposed.Secondly,comprehensively integrate the basic characteristics of the power battery system,analyze the allocation method of the human-machine collaboration task difficulty level and the impact indicators of task allocation,and then establish a product disassembly hybrid diagram,and generate multiple sets of human-machine collaboration disassembly sequences on this basis.Establish a multi-objective optimization model of disassembly cost,difficulty and time.Third,in view of the complexity of the optimization process of human-machine collaborative disassembly sequence,the firefly algorithm is used to optimize it,and the characteristics and shortcomings of the firefly algorithm are analyzed,and then the foraging behavior and tail-catch behavior of artificial fish schools are introduced into the firefly algorithm In this paper,the problem of slow convergence speed of traditional fireflies and the tendency to fall into local optimal solutions is solved,and then combined with the idea of ? ? Pareto solution set to balance multiple sub-goals at the same time,a firefly algorithm based on Pareto fish school behavior is proposed.Finally,using Tesla Model1s as the research object,a human-machine collaborative disassembly sequence model is established,and the firefly algorithm of multi-target fish behavior is used to verify the effectiveness and feasibility of the above research method.