Design for Safe Handling Disposal of the Lithium Waste Power Batteries in a Disassembly Line using Control System Equipped with Machine learning

With the rapid development of electric vehicles, the problem of disposing of waste power batteries has become increasingly prominent. The optimization of the dismantling process route for waste power batteries is a key step before dismantling, which directly determines the economic benefits of dismantling. Taking a certain model of waste power battery as an example, based on the analysis of the uncertainty of the dismantling efficiency of waste power batteries, a machine learning method is proposed to solve the problem of the coupling of characteristic factors affecting it, and a machine learning based optimization framework for the dismantling process of waste power batteries is constructed. This article attempts various machine learning models, such as multi-layer perceptron models, and ultimately proposes a transformer based disassembly order prediction method. Based on the results of simulation training, a brand new lithium battery disassembly production line is designed. The effectiveness of the algorithm is verified through experimental verification and comparative analysis of the calculation results