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Modular converters or reconfigurable battery energy storage systems are a promising approach to eliminate the dependence on the weakest element in previously hard-wired battery packs and to combine heterogeneous batteries (so-called mixed-battery systems). But their need for expensive sensors and complex monitoring as well as control subsystems hinders their progress. Estimating the parameters of each module can substantially reduce the number of required sensors and/or communication components. However, the existing estimation methods for cascaded modular circuits neglect important parameters such as the internal resistance of the battery, resulting in large systematic errors and bias. This article proposes an online estimator based on a dual Kalman filter (DKF) that exploits the slow dynamics of the battery compared to the load. The DKF algorithm estimates the open-circuit voltage (OCV) and internal resistance of each module by measuring only the output voltage and current of the system. Compared with the state-of-the-art, the proposed method is simpler and cheaper with only two sensors compared to $ \geq N + 2$ ($N$ is the number of modules). Furthermore, the proposed algorithm achieves a fast convergence through an optimal learning rate. Simulations and experimental results confirm the ability of the proposed approach, achieving <1.5% and <5% estimation error for OCV and the internal resistance, respectively. [ABSTRACT FROM AUTHOR]

Various advantages are directing the attention to modular multilevel converters (MMCs). Simple ways to balance the voltage difference of MMC modules are strongly desired but an open problem. The modular multilevel series/parallel converter (MMSPC) can be an efficient solution for this problem. However, implementing an effective control method is essential for close-to-optimum operation of MMSPCs. Generally, on the higher level of control, various modulation techniques can control the output, while a scheduler balances the module voltages on a lower control level. This article proposes a simple yet powerful module scheduling method for MMSPCs. This scheduling method can be combined with many modulation techniques, such as nearest-level modulation (NLM). It reduces the control complexity using the sensorless balancing capability, improves efficiency by minimizing the conduction loss, and achieves a compromise between balancing the module voltages and switching loss, alhough applicable to other modulation methods, simulation, and experiments combine the proposed method with NLM for a comparison with the prior art of scheduling. Based on the presented results and analysis, the algorithm is suited particularly for MMSPCs with a low to medium number of modules. The proposed technique achieves 18%–55% reduction in power loss and 7.5% improvement in averaged capacitor currents compared to other algorithms. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMCs) feature an established topology for the highest voltage and power levels. For lower levels, MMCs find a wide range of applications in generation, energy storage, and electric motor drive. However, the large quantity of expensive voltage sensors as well as high data-processing requirements for the module voltage balancing remains an obstacle. Additionally, the stark cost reductions of power electronic semiconductors have reduced their share in the total cost and rendered initially uneconomical module topologies appealing in low and medium voltages. In this article, we proposed an MMC topology with an active clamping path that balances the voltage of the modules in an arm. The proposed structure can achieve sensorless voltage balancing with a minimum control effort. The sensorless operation has the added benefit of reducing the communication as well as computation demand between the modules and the central controller. As compared with the state-of-the-art voltage balancing schemes, the proposed solution achieves a balanced system operation with less power loss, fewer components, and without any measurement. The presented analysis as well as the simulation and experimental results verify the benefits of the proposed topology. The results demonstrate that even in the face of a severe imbalance, all the module voltages are maintained within tight boundaries. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMCs) enjoy the benefits of modularity and scalability. In particular, MMCs with symmetrical half-bridge submodules enable bipolar operation yet with a simple structure and low conduction losses. However, bulky dc capacitors in MMC submodules act as one major obstacle that retards the further improvement of system size, weight, and cost performance. Additionally, tight regulation and balance of dc capacitor voltages necessitate expensive voltage sensors paired with dedicated voltage controllers. This article proposes an effective hardware-based strategy that achieves MMC capacitance reduction through parallelization of symmetrical half-bridge submodules. On top of capacitance saving, the proposed strategy balances capacitor voltages in a sensorless fashion, which translates into the removal of voltage sensors and great simplification of control efforts. In addition, the proposed strategy allows fault-tolerant operation of MMCs. Finally, simulation and experimental results validate the effectiveness of the proposed strategy in capacitance reduction and capacitor voltage balancing of MMCs as static compensators. [ABSTRACT FROM AUTHOR]