Fluidic soft actuators have drawn more and more research interest in recent years, but it is not clear on their behaviors of dynamical energy consumption, which is critical to power system design. To solve this problem, this work develops an analytical model of required energy including elastic potential energy and dissipated energy for fiber-reinforced fluidic soft actuators based on the theory of viscoelasticity. Since the parameters of soft material are difficult to obtain, the key parameters in the model are identified by experimental data and genetic algorithm. To verify the general performance of the developed model, a series of fiber-reinforced fluidic soft actuators with different dimensions are fabricated and tested. The average errors of the experimental value and the predicted value are equal to 0.045 J, 0.003 J, 0.001 J, and 0.011 J, which are less than 15% of the nominal values. The experimental results show that the model can capture the energy characteristics of the soft actuators under various operating conditions with expected accuracy. Finally, the energy consumption of a robotic arm composed of three soft actuators is also evaluated. This work can promote the understanding on the energy requirement of soft robots and provide further reference to the optimization design of power system.

近年来，流体软执行器引起了越来越多的研究兴趣，但对于动态能耗的行为尚不清楚，这对电力系统设计至关重要。为了解决这个问题，这项工作基于粘弹性理论建立了纤维增强流体软致动器所需能量的分析模型，包括弹性势能和耗散能量。由于难以获得软材料的参数，因此通过实验数据和遗传算法确定了模型中的关键参数。为了验证所开发模型的总体性能，制造并测试了一系列具有不同尺寸的纤维增强流体软执行器。实验值和预测值的平均误差等于0.045 J，0.003 J，0.001 J和0.011 J，小于标称值的15％。实验结果表明，该模型能够以期望的精度捕获各种操作条件下的软执行器的能量特性。最后，还评估了由三个软致动器组成的机械臂的能耗。这项工作可以增进对软机器人能量需求的理解，并为电力系统的优化设计提供进一步的参考。