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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]

Since the introduction of modular multilevel converters (MMC), various additional features have been introduced for MMCs, among them parallel inter-module connectivity. However, such a parallel mode requires appropriate modulation and switching strategies to exploit its full potential. Low-frequency switching modulation is widely used with half-bridge modules and a large body of research focusses on the optimum control and scheduling of these methods. However, so far, a suitable adaptation for MMCs with parallel mode is missing, and existing methods perform suboptimum. This article proposes a generic scheduling algorithm for simple and low-cost integration with low-frequency switching modulation. The proposed method reduces control complexity, minimizes power loss, and can be combined with most modulation techniques, including nearest-level modulation (NLM) and selective harmonic elimination. The text in this article provides a general algorithm for integrating this method with other control levels and analyzes its effect on MMCs with parallel functionality. Moreover, it examines the performance of the system with NLM combined with the proposed scheduler and compares it to other alternatives. Results show up to a 50% reduction in power loss with a similar modulation technique as well as significantly lower THD and power loss compared to optimized phase-shifted carrier modulation as another sensorless alternative method. [ABSTRACT FROM AUTHOR]

High-voltage battery pack and charger structure are the main concerns of the electric vehicle (EV) developments. To achieve required voltage and power in propulsion systems, cascading battery stacks is essential. However, due to small discrepancies between different cells, charge imbalance occurs. Charge imbalance reduces battery cells life cycle, accessible energy, and system performance. Hence, charge equalization among battery stacks is necessary. Furthermore, EVs should have some essential requirements to provide desired contributions in future networks. Therefore, bidirectional power flow and reactive power control are other important capabilities of the battery charger system. In this paper, a bidirectional structure with two operation modes for a modular battery stack is developed. The developed structure has active and reactive control capabilities during grid to vehicle and vehicle to grid operations. To improve the battery system performance, a modular charge equalizer circuit (CEC) for both operation modes is developed. The modular configuration of the battery stack improves the system reliability and flexibility. Moreover, the overall system performance for the CEC and converter is improved by utilizing the integrated control strategy. Performance of the proposed structure is evaluated using simulations and laboratory experiments. The results confirm the capability of the proposed structure. [ABSTRACT FROM PUBLISHER]