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A stacked polyphase bridge converter consists of multiple standard, three‐phase two‐level voltage source inverters connected in series to the same dc voltage source. The authors present a decentralised and dynamic dc‐bus reconfiguration strategy for this type of converter. The innovation of the proposed strategy lies in its ability to isolate or reactivate one of the inverters in the series connection online, even in motoring mode, enabling increased fault tolerance and an extended speed range. Both the required hardware alterations and the multi‐agent control strategy are addressed. Its major benefits compared to the state‐of‐the‐art are that only two additional active, unidirectional semiconductor switches are required per inverter, and that the control is based on local computations, local measurements and neighbour‐to‐neighbour communication only. Hence, the scalability and reliability of the hardware are extended towards the control. Simulations and experimental results on a 4 kW modular axial‐flux PMSM prove the feasibility of the concept, and validate that the dc‐bus can be reconfigured in 100 ms, without torque interruption. [ABSTRACT FROM AUTHOR]

A modular motor drive (MMD) can be considered as a multi‐agent system, in which the agents work together to reach a common goal. One agent in such an MMD comprises only a subset of the concentrated windings and power electronic converter modules and is equipped with an independent controller. The goal of this research is to let the agents cooperate to distribute a torque demand among them in a completely decentralised way, in order to comply with the flexibility and reliability of modular motor drives. However, the current condition of each agent must still be taken into account during this torque allocation. To limit the communication load, only communication between neighbouring agents is allowed. The combination of a gossip consensus algorithm and multiple decentralised PI current controllers is used for this purpose. Simulations and experimental results on a modular axial‐flux permanent magnet synchronous machine consisting of five agents confirm that the total torque demand is delivered under the proposed control strategy, even during agent malfunctions, under random communication link failures and with non‐identical agents. [ABSTRACT FROM AUTHOR]

Squirrel‐cage induction machines (IMs) with indirect field‐oriented control are widely used in industry and are frequently chosen for their accurate and dynamic torque control. During operation, however, temperature rises leading to changes in machine parameters. The rotor resistance, in particular, alters, affecting the accuracy of the torque control. The authors investigated the effect of a rotor resistance parameter mismatch in the control algorithm on the angular rotor flux misalignment and the subsequent deviation of stator currents and motor torque from their setpoints. Hence, an online, data‐driven torque compensation to eliminate the temperature effect is proposed to enable robust torque‐controlled IMs. A model‐based analysis and experimental mapping of the temperature effect on motor torque is presented. A temperature‐torque lookup‐table is subsequently implemented within the control algorithm demonstrating the ability to reduce the detrimental effect of temperature on torque control. Experimental results on a 5.5 kW squirrel‐cage induction motor show that the proposed data‐driven online temperature compensation method is able to reduce torque mismatch when compared to having no temperature compensation. Up to 17% torque mismatch is reduced at nominal torque and even up to 23% at torque setpoints that are lower than 20% of the nominal torque. A limited torque error of <1% remains in a broad operating range. [ABSTRACT FROM AUTHOR]