Multi-Parameter Optimization of Servo Control System for Lithium Battery Electrode Rolling Mill Based on an Improved NGSA Algorithm

The uniformity of lithium battery electrodes is a key parameter affecting electrochemical activity, which highlights the importance of rolling process accuracy. Conventional electrode rolling mill servo control systems have major problems with nonlinearity, load disturbances, and finding optimal adjustable parameter values. This paper proposes a new multi-parameter optimization technique for servo control systems that utilizes an improved niche genetic simulated annealing algorithm. The algorithm combines a niche approach to ensure population diversity and utilizes simulated annealing to achieve global convergence. Experimental tests on a lithium battery rolling mill have shown that the technique exhibits higher control accuracy, speed, and energy efficiency than conventional genetic algorithms and PID methods. This suggests its suitability for intelligent manufacturing in the energy storage industry.