The relationship between gas pressure drop and gas resistance coefficient versus operation condition and gas phase Reynolds number in three packing plate distance was theoretically analyzed and experimentally measured...The relationship between gas pressure drop and gas resistance coefficient versus operation condition and gas phase Reynolds number in three packing plate distance was theoretically analyzed and experimentally measured in the centrifugal field.The experimental results show that packing plate distance has a great influence on gas phase resistance and too small distance makes liquid clogging and causes great gas phase resistance.The fitness distance of the packing plate is large than 3.1 mm under the operation condition in this paper.展开更多
针对一辆小型燃料电池电动车的2 k W质子交换膜燃料电池(PEMFC)动力系统,利用遗传算法优化的BP神经网络建立其电压输出特性模型,将PEMFC部分实测数据作为遗传算法优化的BP神经网络的训练样本对其进行训练,利用训练好的神经网络对电堆电...针对一辆小型燃料电池电动车的2 k W质子交换膜燃料电池(PEMFC)动力系统,利用遗传算法优化的BP神经网络建立其电压输出特性模型,将PEMFC部分实测数据作为遗传算法优化的BP神经网络的训练样本对其进行训练,利用训练好的神经网络对电堆电压输出特性进行预测,并与实验数据进行对比,结果显示:网络预测的输出电压与实测输出电压之间的最大相对误差均保持在4%之内.展开更多
文摘The relationship between gas pressure drop and gas resistance coefficient versus operation condition and gas phase Reynolds number in three packing plate distance was theoretically analyzed and experimentally measured in the centrifugal field.The experimental results show that packing plate distance has a great influence on gas phase resistance and too small distance makes liquid clogging and causes great gas phase resistance.The fitness distance of the packing plate is large than 3.1 mm under the operation condition in this paper.
文摘针对一辆小型燃料电池电动车的2 k W质子交换膜燃料电池(PEMFC)动力系统,利用遗传算法优化的BP神经网络建立其电压输出特性模型,将PEMFC部分实测数据作为遗传算法优化的BP神经网络的训练样本对其进行训练,利用训练好的神经网络对电堆电压输出特性进行预测,并与实验数据进行对比,结果显示:网络预测的输出电压与实测输出电压之间的最大相对误差均保持在4%之内.