WOA算法在氢水分离效能预测上的应用

Application of WOA Algorithm in the Prediction of Hydrogen Water Separation Efficiency

提高氢水分离器的分离效能对优化氢燃料电池汽车的动力表现具有重要意义。因此,可以利用神经网络算法对分离效能表现进行预测。针对BP神经网络预测精度不高、收敛速度慢等,提出鲸鱼优化算法(WOA-BP)。通过训练预测,相比BP神经网络,WOA-BP算法能较好地对氢水分离器的分离效能表现进行预测,与实际值吻合度高,优化效果良好。

Improving the separation efficiency of hydrogen water separator is of great significance to optimize the power performance of hydrogen fuel cell vehicles.Therefore,neural network algorithm can be used to predict the performance of separation efficiency.Aiming at the low prediction accuracy and slow convergence speed of BP neural network,a whale optimization algorithm(WOA-BP)is proposed.Through training and prediction,compared with BP neural network,WOA-BP algorithm can better predict the performance of separation efficiency of hydrogen-water separator,with high coincidence with the actual value and good optimization effect.