Planning of Energy-Efficient Trajectories with Utilization of Energy Storage and Energy Interchange between Electrical Drives

在德国的生产工厂中，大约2/3的电能被电力驱动消耗。在此，能量损失主要是由于低效率的工作点和通过转换成热能的制动能量耗散。现代伺服逆变器的内部DC总线可以电耦合（例如在多轴系统中）。因此，电动机和发电机驱动器之间的电能的连续交换是可能的。在第一个和完成项目期间，建立了路径规划方法，减少了各种机械解耦多轴系统定位任务的能源需求。因此，应用基于模型的优化算法。一方面，在模型中考虑了驱动部件的依赖于工作点的能量损失，并因此尽可能地减少。另一方面，使用DC总线的电能交换的可能性被系统地放大。此外，利用DC总线电容器的能量存储容量以及机械轴的动能和势能存储。因此，显著更大量的可回收机械能可用于供应其他电驱动或启动后续运动。在项目的第二阶段，正如在最初的建议中所概述的那样，开发的方法被传输到机械耦合的多轴运动学（例如串联机器人）。因此，开发的模型方程的第一个项目期间必须扩展和额外的模型参数必须被识别。为了提高其他机器人系统和运动学的方法的可移植性，建模和参数识别的努力必须减少。因此，将使用模型参数的敏感性分析来确定有效的模型降阶。同时，在路径规划过程中必须考虑碰撞的风险，使用适当的算法。通常，现有系统部件的能量存储容量是有限的，并且通常不足以用于给定的应用。因此，通过电气和机械能量存储设备以及适当的控制策略来扩展多轴系统。在复杂的生产线中，通常同时使用许多不同的单轴和多轴系统。为了进一步降低电网能源消耗，所有系统都通过扩展的DC总线连接。此外，用于有效过程协调的新操作技术对于放大不同（例如多个机器人）系统之间的电能交换至关重要。最后，该方法被分配到一个实时控制程序的发展，一个新的在线轨迹优化方法。由此，电能的交换减少了例如示例性相机控制的拾取和放置应用的需求。

In German production plants about 2/3 of electrical energy are consumed by electrical drives. Here, energy losses mainly result from inefficient operating points and braking energy dissipation by conversion to thermal energy. The internal DC buses of modern servo inverters can be electrically coupled (e.g. in multi-axis systems). Hence, a continuous exchange of electrical energy between motor and generator drives is possible. During the first and completed project period path planning methods were established that reduce the energy demand of positioning tasks of miscellaneous, mechanically decoupled multi-axis systems. Therefore, model based optimization algorithms were applied. On the one hand, operating point-dependent energy losses of the drive components are considered in the model and consequently reduced where possible. On the other hand, the possibility of electrical energy exchange using the DC bus is systematically amplified. Also the energy storage capacity of the DC bus capacitors as well as kinetic and potential energy storage of the mechanical axes are utilized. In consequence, a significantly bigger amount of the recuperable mechanical energy can be used for the supply of other electrical drives or the initiation of subsequent movements. Finally, the total energy demand is decreased.During the second period of the project, as already outlined in the initial proposal, the developed methods are transmitted to mechanically coupled multi-axis kinematics (e.g. serial robots). Therefore, the developed model equations of the first project period must be extended and the additional model parameters must be identified. To improve the transferability of the approaches to other robotic systems and kinematics, the efforts for modeling and parameter identification must be reduced. Therefore, valid model reductions will be determined using a sensitivity analysis of the model parameters. Simultaneously, the risk of collisions must be regarded during the path planning procedure using appropriate algorithms. Generally, the energy storage capacities of the existing system components are limited and usually not sufficient for a given application. Hence, the multi-axis system is extended by electrical and mechanical energy storage equipment and appropriate control strategies. In complex production lines, usually numerous different single- and multi-axis systems are utilized simultaneously. To further reduce the consumption of electrical grid energy, all systems are connected via an extended DC bus. Furthermore, new operation techniques for efficient process coordination are essential to amplify the exchange of electrical energy between different (e.g. multiple robotic) systems. Finally, the approaches are assigned to a real-time control procedure for the development of a new online trajectory optimization method. Hereby, the exchange of electrical energy reduces the demand of e.g. an exemplary camera controlled Pick&Place applications.