Optimization of continuous triboelectrification process for polymeric materials in dry contact

Abstract

Triboelectrification (i.e., generation of electric charge by friction between two materials) is a complex process. Besides the nature and condition of the surfaces in contact, several factors can have an influence on charge generation: pressure load and relative velocity between the two bodies, number of friction cycles, ambient temperature and humidity, condition and type of material surface. This paper aims at demonstrating that associating the experimental response surface methodology and genetic algorithms is an effective technique for the optimisation of triboelectrification process. The quadratic model derived from the experiments is used in a genetic algorithm program to find the optimal combination of factor values (10 sliding cycles; normal force: 10 N; sliding speed: 55 mm/s) that maximize the average potential at the surface of the tribocharged materials: -1633 V. A final experiment confirmed the prediction of the genetic algorithm. The conclusions of this experimental study can be applied to the optimisation of industrial triboelectrification processes, and contribute to the reduction of the related maintenance, energy and raw-material costs.