大型电热辊道窑多温区多耦合温度场建模与控制方法研究

With the depletion of natural resources and the deterioration of the global environment, lithium-ion battery as a new type of highly efficient, pollution-free green energy has received great attention. Roller kiln is the first choice of produce cathode materials for lithium-ion batteries. Under the condition of the fixed raw material and formula, roller kiln temperature has become the key factor of product quality. This project focuses on the modeling and control problems in roller kiln's temperature field. In the actual background of roller kiln, firstly, the temperature field model of the system is established, which includes many kinds of heat exchange mechanism and air flow rate, careful handling of various uncertainties in production. Then, each temperature zone model is regarded as a subsystem, and a small gain theorem is established by combining the stochastic stability theorem. The influence of various uncertain parameters on the stability of the system is described. “Practical consistency” is proposed. The Lyapunov function with virtual parameter estimation error is constructed. Decentralized adaptive robust controller is designed to realize coordinated control. Finally, optimize the flow through the atmosphere, recovery the clean atmosphere, establish the health index to optimize the system, to achieve energy saving. The results not only can be used in the production of lithium battery materials, ceramic products and other processing industries for roller kiln, and other industrial furnace also has the reference value.

随着自然资源的消耗和全球环境的恶化，锂离子电池作为新型高效、无污染的绿色能源受到极大的关注。辊道窑是生产锂离子电池正极材料的首选窑炉。在原料及配方固定的情况下，辊道窑的温度成为产品质量的关键。本项目聚焦于辊道窑温度场的建模与控制问题。以实际辊道窑为背景，首先分温区建立包含多种热交换机理和气氛流量相关的温度场系统模型，细致处理生产中出现的多种不确定性；然后将各个温区模型当成子系统，结合随机稳定性定理建立融合多不确定性参数的小增益模型，刻画各种不确定性参数对系统稳定性能的影响，提出“实用一致”，构造包含虚拟参数估计误差的Lyapunov函数，设计分散自适应鲁棒控制器，实现协调控制；最后，优化通入气氛流量，回收高温干净气氛，建立健康指数对系统进行优化控制，实现节能降耗。研究成果不但能应用于锂电池材料的生产，对陶瓷用品等其他用辊道窑来加工的工业，以及对其他的工业窑炉同样具有借鉴的价值。

随着自然资源的消耗和全球环境的恶化，锂离子电池作为新型高效、无污染的绿色能源受到极大的关注。辊道窑是生产锂离子电池正极材料的首选窑炉。在原料及配方固定的情况下，辊道窑的温度成为产品质量的关键。本项目聚焦于辊道窑温度场的建模与控制问题。以实际辊道窑为背景，先基于传热机理和热平衡机理建立辊道窑内温度场数学模型，准确体现工业过程中辊道窑内的传热过程，针对工业过程复杂性和工业噪声影响存在着随机不确定性因素干扰，通过历史数据进行采样分析，结合数据驱动对机理模型进行补偿，考虑变量重要性的差异和相关样本与查询样本的相似层度，提出一种基于双层局部加权实时学习极限学习机(DLW-JIT-ELM)模型来进行误差补偿，综合提出一种结合机理和数据驱动的集成模型来提高温度预测性能。设计了一种基于热图处理的辊道窑温度控制系统，通过热辐射传感器来采集辊道窑的数据生成热力分布图，基于热力分布图得到热量流动数据，根据热量流动数据计算每个温区对应的加热单元的功率调整值，功率调整值实时依据热力分布图的变化而变化，使得最终辊道窑内温度分布与温度函数吻合。研究成果不但能应用于锂电池材料的生产，对陶瓷用品等其他用辊道窑来加工的工业，以及对其他的工业窑炉同样具有借鉴的价值。