Efficient load sharing in multi-motor systems using energy based methods

多电机和耦合能源在实践中很常见，例如在机器人、网络处理设备和电力系统中，随着电动汽车和混合动力汽车以及分布式发电的普及，这种能源变得越来越重要。处理模块化和紧耦合系统中的多个目标和扰动，以获得实用的控制结构，对于执业工程师和涉及关键责任的应用来说是一个挑战。该计划的主要目标是促进基于机电系统能量特性的控制方法和战略的发展，以提高其整体性能。具体地说，我们将研究具有电压扰动和内部稳定性准则的刚性和柔性耦合多电机系统的负荷分担问题，特别是在能效优化的背景下。基于能量宏观表示(EMR)的反推和逆混合控制将设计出具有保证稳定性的实用控制结构，并将在多电机试验台上进行实验验证。一种常见的EMR-BackStep方法将提供一种系统的方法来处理能量管理、负载分担和耦合动态，从而通过设计方法的可访问性和所提供的保证的稳定性来产生对工业实施具有吸引力的控制律。通过优化多电机系统中的负载分担，可以显著节省能源。然而，这种方法并不局限于这些系统，它也可以应用于其他系统，如分布式发电和混合能源系统。应用于牵引系统以及电动和混合动力汽车的不同子系统将是本研究计划的成果之一。

Multi-motor and coupled energy sources are common in practice, e.g. in robots, web handling equipment and power systems, and are increasingly important with the proliferation of electrical and hybrid vehicles and of distributed generation. Handling of multiple objectives and disturbances in modular and tightly coupled systems to obtain practical control structures is a challenge for practicing engineers and for applications that involve critical liability. The main objective of the program is to contribute to the development of control methods and strategies based on energetic characterization of electromechanical systems to improve their overall performance. Specifically, the problem of load sharing in rigidly and flexibly coupled multi-motor systems subject to voltage disturbance and internal stability criteria will be studied, in particular in the context of energy efficiency optimization. Practical control structures with guaranteed stability will be developed using a mixed backstepping and inversion based control from Energetic Macroscopic Representation (EMR), and the results will be validated experimentally on a multi-motor test-bed. A common EMR-backstepping approach will provide a systematic approach to deal with energy management, load sharing and coupled dynamics leading to control laws that are attractive for industrial implementation by the accessibility of the design approach and the guaranteed stability it offers. Significant energy savings are possible by optimizing load sharing in multi-motor systems. However, the approach is not limited to these systems and it can also be applied to other systems such as in distributed generation and in hybrid energy sources systems. Application to traction systems and to different subsystems in electric and hybrid vehicles will constitute one of the outputs of this research program.