Search Results (12)

Reconfigurable battery modules can dynamically adjust the connection topology among battery cells, significantly improving the energy utilization efficiency of battery energy storage systems. However, existing state estimation methods focus primarily on individual battery cells. Frequent topology changes cause traditional State of Charge (SOC) estimation algorithms to accumulate large errors due to mismatches in equivalent capacity and internal resistance, making them ineffective for reconfigurable battery modules. To address this limitation, this paper proposes a Gated Recurrent Unit–Transformer architecture for precise SOC estimation in reconfigurable battery modules. The model uses a Gated Recurrent Unit to capture the temporal continuity of electrochemical evolution and employs the Transformer’s self-attention mechanism to analyze discrete topology changes. Experimental results show excellent estimation accuracy across different initial SOC levels, with a mean absolute error as low as 0.085% at full charge and 0.035% at 50% SOC. The architecture demonstrates strong topology self-identification capability and maintains high robustness even under abrupt voltage steps caused by reconfiguration. This method provides accurate and reliable state estimation for large-scale two-layer reconfigurable battery systems while reducing control complexity and improving operational efficiency. Full article

One of the most important functions of a battery management system (BMS) is cell balancing. The limitations of active balancing systems arise from reactive control strategies that rely exclusively on instantaneous measurements of cell voltage or state of charge (SOC). Such strategies do not account for short-term voltage dynamics, which can lead to unnecessary energy transfers. This paper proposes a predictive cell balancing strategy based on cell voltage estimation, intended for active balancing systems, particularly those employing flyback converters. The proposed predictive model uses historical voltage and current measurements, as well as operating temperature information, to estimate the short-term evolution of the cell voltage. The model is trained using experimental datasets obtained from NCR18650B lithium-ion cells (Panasonic, Osaka, Japan) subjected to multiple current profiles and temperature conditions. The proposed strategy is implemented on the DC2100B-C module (Linear Technology, Milpitas, CA, USA), which employs the LTC3300-1 integrated circuit (Linear Technology, Milpitas, CA, USA), and is experimentally validated on a battery pack consisting of 12 NCR18650B cells connected in series. The experimental results demonstrate that the use of short-term voltage prediction improves the balancing process by reducing the voltage equalization time and the number of balancing command reconfigurations. Full article

The increasing adoption of Light Electric Vehicles (LEVs) in urban areas, driven by the micromobility wave, raises significant safety concerns, particularly regarding battery fire incidents. This research investigates the electromechanical performance of aged 18650 lithium-ion batteries (LIBs) from LEVs under mechanical impact conditions. For this study, a battery module from a used e-scooter was disassembled, and its constituent cells were reconfigured into compact modules for testing. To characterize their initial condition, the cells underwent cycling tests to evaluate their state of health (SOH). Although a slight majority of the cells retained an SOH greater than 80%, a notable increase in their internal resistance (IR) was also observed, indicating degradation due to aging. The mechanical impact tests were conducted in adherence to the UL 2271:2018 standard, employing a semi-sinusoidal acceleration pulse. During these tests, linear kinematics were analyzed using videogrammetry, while key electrical and thermal parameters were monitored. Additionally, strain gauges were installed on the central cells to measure stress and deformation. The results from the mechanical shock tests revealed characteristic acceleration and velocity patterns. These findings clarify the electromechanical behavior of aged LIBs under impact, providing critical data to enhance the safety and reliability of these vehicles. Full article

This paper presents a charging architecture for the Reconfigurable Cascaded Multilevel converter, which was specifically designed for electric vehicle (EV) powertrain applications. The RCMC topology is capable of executing power conversion and actively managing battery systems concurrently. The active battery management is achieved using the Reconfigurable Battery Module, which regulates the serial connection of cells via a switch pattern. In this paper, the RCMC is directly interfaced with an AC three-phase power system, facilitating the dynamic control over battery cells charging. Its inherent design allows for the implementation of various charging algorithms, customizable to specific requirements, without necessitating additional intermediary power stages. Firstly, an overview of the RCMC topology is given, and an analysis to define the optimal filter inductance is carried out. Subsequently, after the AC system characteristics are explained, two charging algorithms are presented and described: one prioritizes State of Charge (SOC) balancing among battery cells, while the other focuses on minimizing power losses. Moreover, a time estimation computation for the RCMC is carried out considering a two-level AC charging station. The result is compared with the time required for a conventional battery pack. The results show a reduction of 10 s in charging time for a mere 20% increase in SOC. Finally, the experimental setup is presented and used to validate the efficacy of the proposed algorithms. Full article

In order to address the issue of battery cell disparity in lithium-ion battery systems, battery balancing techniques are required. This paper proposes an improved battery balancing strategy within a reconfigurable converter system. The strategy is based on the state of charge (SOC) of batteries, and utilizes the reconfigurable converter system to transfer energy from battery modules with high SOC to those with lower SOC. Additionally, it allows for battery module balancing while supplying power to loads. A MATLAB/Simulink simulation model with five batteries was built to validate the effectiveness of the proposed balancing strategy under unloaded and loaded conditions. The simulation results demonstrate that the proposed strategy achieves more efficient and accurate battery module balancing compared to the previous balancing modes. Full article

The battery system is one of the most-important, but also -critical components in the electric power-train. The battery’s system states and parameters are commonly tracked by the battery monitoring system. However, in reality, the accuracy of the state and parameter estimation may suffer from insufficient excitation of the system. Since the current states and parameters serve as the basis for many battery management system functions, this might lead to incorrect operation and severe damage. Reconfigurable battery systems allow enhancing the system’s excitation by applying a switching operation. In this contribution, the state and parameter estimation of a reconfigurable battery module were simulated and tested experimentally. Thereby, a low-exciting and a high-exciting drive cycle were compared. Furthermore, the switching patterns were applied to enhance the excitation and, hence, improve the estimation of an extended Kalman filter. The cells were switched via a pulse-width modulation signal, and the influence of frequency and duty cycle variation on the estimation accuracy were investigated. Compared to the low-excitation input, a significant improvement in the estimation of up to $46\%$ for the state of charge and $78\%$ for the internal resistance were achieved. Hereby, low frequencies and duty cycles proved to be particularly advantageous. Switching, however, has only a limited influence on an already highly excited system and may lead to additional aging due to higher heat generation. Full article

The capacity and voltage rating of battery packs for electric vehicles or stationary energy storages are increasing, which challenge battery management and monitoring. Breaking the larger pack into smaller modules and using power electronics to achieve dynamic reconfiguration can be a solution. Reconfigurable batteries come with their own set of problems, including many sensors and complex monitoring systems, high-bandwidth communication interfaces, and additional costs. Online parameter estimation methods can simplify or omit many of these problems and reduce the cost and footprint of the system. However, most methods require many sensors or can only estimate a subset of the elements in the module’s equivalent circuit model (ECM). This paper proposes a simple decoupling technique to derive individual modules’ voltage and current profiles from the output measurements without direct measurement at the modules. The determined profiles can achieve a high sampling rate with minimum communication between the battery management system (BMS) and the modules. With accurate profiles, an estimation technique can easily determine the parameters of the modules. Provided simulations and experiments confirm this claim by estimating the parameters of a first-order ECM with a parallel capacitor. The proposed technique reduces the number of sensors from 2N + 2 to only two at the pack’s output terminals. Full article

This paper reports the development of a model for continuous simulation of the power flow into AC–DC hybrid microgrids operating for different generation–consumption scenarios. The proposed application was assembled using a multiple-input multiple-output model which was built using blocks containing simplified models of photovoltaic (PV) modules, wind turbines (WT), battery arrays (energy storage units, ESU), and power loads. The average power was used as the input/output variable of the blocks, allowing flexibility for easy reconfiguration of the microgrid and its control. By defining a generation profile, PV and WT were modeled considering environmental conditions and efficiency profiles of the maximum power point tracking (MPPT) algorithms. ESUs were modeled from intrinsic characteristics of the batteries, considering a constant power charge regime and using the State of Energy (SoE) approach to compute autonomy. To define a consumption profile, DC and AC loads were modeled as a constant real power. As an innovative characteristic, unidirectional and bidirectional power conversion stages were modeled using efficiency profiles, which can be obtained from experiments applied to the real converters. The outputs of the models of generation, consumption, and storage units were integrated as inputs of the mathematical expressions computing the power balance of the buses of the microgrid. The proposed model is suitable to analyze efficiency for different configurations of the same microgrid architecture, and can be extended by integrating additional elements. The model was implemented in LabVIEW software and three examples were developed to test its correct operation. Full article

48 V is emerging as a safe-to-touch alternative voltage level for electric vehicles (EVs). Using a low- instead of a high-voltage drive train reduces isolation efforts, eliminates the risk of electric shock, and thus increases the system safety. In contrast, fast charging of a 48 V battery would require very high currents and is incompatible with the widely established high-voltage electric vehicle charging infrastructure. Instead of employing additional on board power converters for fast charging, the concept of a reconfigurable battery is presented. A small-scale prototype system is designed consisting of eight 48 V lithium iron phosphate battery modules. In series configuration, they can be charged at 460 V with up to 25 A. In 48 V parallel configuration, the peak discharge current is up to 800 A. The MOSFET-based reconfiguration system also operates as a module charge balancer during high-voltage charging. The cost overhead for the reconfiguration system is estimated to 3% for a scaled-up full size EV. Due to the additional reconfiguration switch resistances, the simulation of a 48 V 75 kW electric vehicle in the World harmonized Light-duty vehicles Test Procedure showed a performance reduction of 0.24%. Full article

Voltages of electric double-layer capacitor (EDLC) modules vary rather wider than traditional secondary batteries. Although EDLCs should desirably be cycled in a voltage range as wide as possible to achieve a high energy utilization ratio, the wide voltage variation of EDLC modules impairs the performance of DC–DC converters. To address such issues, previous works reported series-parallel reconfiguration techniques, which are roughly divided into balance- and unbalance-shift circuits. However, conventional balance-shift circuits are not applicable to modules comprising odd number cells, impairing modularity. Unbalance-shift circuits, on the other hand, unavoidably cause cell voltage imbalance that reduces energy utilization ratio. This paper proposes a novel series-parallel reconfigurable EDLC module with cell voltage equalization capability. The proposed reconfigurable EDLC module is applicable to any number of cells, realizing good modularity. Furthermore, all cells in the proposed module can be charged and discharged uniformly without generating cell voltage imbalance, achieving an improved energy utilization ratio compared with conventional techniques. A five-cell module prototype was built for experimental verification. While the module voltage varied between 1.04 and 2.83 V, all cells discharged from 2.5 to 0.3 V. The result is equivalent to a 98.6% energy utilization ratio. Full article

Voltage variations of electric double-layer capacitors (EDLCs) are rather wider than those of traditional rechargeable batteries, and an energy utilization ratio of EDLCs is dependent on cells’ voltage variation ranges. To satisfactorily utilize EDLCs’ energies, voltages of EDLC modules should be within a certain range, while cells need to be charged and discharged over the wide voltage range. To this end, various kinds of series-parallel reconfiguration techniques based on balance- and unbalance-shift circuits have been proposed, but conventional techniques can only be applied to modules consisting of even number cells, impairing the design flexibility and scalability. With the unbalance-shift circuits, cell voltages are unavoidably mismatched due to unequal currents, resulting in reduced energy utilization ratios. This article proposes a novel series-parallel reconfiguration technique with voltage equalization capability for EDLC modules. The proposed technique can be applied to any number of cells, improving design flexibility and scalability. Furthermore, since the proposed circuit behaves as a switched capacitor converter, in which all cells are virtually connected in parallel, cells are equally charged and discharged without causing voltage imbalance, realizing the improved energy utilization ratio. A prototype for an EDLC module comprising four cells, each with a rated charging voltage of 2.5 V, was built and experimentally tested. The module voltage varied in the range of 3.2–5.0 V, while all cells were uniformly discharged down to as low as 0.8 V, achieving the energy utilization ratio of 90%. Full article

This study investigates the benefit of an optimal and energy-efficient reconfiguration technique for the design of channel-aware receiver aiming Internet of Things (IoT) applications. First, it demonstrates the interest for adaptive receivers based on an estimation of the received power and compares the proposed channel-aware receiver with the State Of the Art. It is shown that the lifetime of the Wireless Sensor (WS) battery can be extended by a factor of five with the optimization of operating points of the tunable receiver while maintaining similar performances than industrial modules. The design of an Ultra-Low Power (ULP) inductorless Low Noise Amplifier (LNA), which fits the low power mode of the tunable receiver, is then optimized and described. The back-gate biasing of Fully Depleted Silicon-On-Insulator (FD-SOI) technology to lower the power consumption by more than 25% still maintaining performances is evaluated. The proposed LNA has been implemented in ST-Microelectronics 28 nm FD-SOI Technology, its active area is only 0.0015 mm². The measured performances at 2.4 GHz exhibit more than 16 dB of voltage Gain (Gv), 7.3 dB of Noise Figure (NF), and a −16 dBm Input referred third-order Intercept Point (IIP3). The LNA consumes 300 µW from a 0.6 V supply. Full article