Search Results (1,096)

Over the last decade, the proliferation of electric vehicles (EVs) has highlighted the importance of robust battery management systems (BMSs) to mitigate cell imbalance driven by manufacturing tolerances, thermal gradients, and non-uniform aging. To address these limitations, this study presents a MATLAB R2023b/Simulink-based comparative performance analysis of passive and active cell balancing topologies for lithium-ion battery packs. Using an equivalent circuit model based on the ORION 18650/26 cell, twelve distinct configurations encompassing passive switched-resistor alongside active inductor, capacitor, transformer, and converter topologies were evaluated. To isolate intrinsic charge-transfer dynamics from multi-cell network latency, all topologies were benchmarked in a standardized adjacent two-cell baseline under a strict convergence threshold (ΔOCV ≤ 1 mV). The simulation results demonstrate that parallel two-inductor and buck–boost topologies achieve the fastest equalization speed (≈1.47–2.53 s), whereas switched-capacitor configurations yield the lowest total energy dissipation (≈0.0011 Wh–0.0013 Wh). Furthermore, to evaluate string-level scalability and multi-hop energy transfer dynamics, the high-performing buck–boost topology was extended and benchmarked in a four-cell series (4S) configuration. The simulation results demonstrate that while the adjacent two-cell baseline achieves fast equalization (≈1.47–2.53 s), the 4S string reaches multi-cell convergence within 12.47–13.94 s, providing quantitative insights into multi-hop routing latency. Overall, this work provides an unconfounded quantitative baseline to support BMS engineers in selecting optimal balancing topologies tailored to specific EV performance, space, and economic constraints. Full article

This paper proposes a bidirectional LC resonance DC–DC converter for wide-range applications. By introducing an auxiliary Boost bridge arm on the HVS of the conventional structure and multiplexing the resonant inductor, the proposed converter extends the voltage gain range. Utilizing a combined PWM and PFM control strategy, the converter operates in multiple modes: two gain modes (medium and high) during battery discharge, and three gain modes (low, medium, and high) during battery charging. This multi-mode mechanism effectively extends the voltage gain range, narrows the switching frequency variation, and simplifies magnetic component design. Furthermore, ZCS operation is confirmed under the tested representative operating conditions, significantly reducing switching losses. Finally, an experimental prototype with a rated power of 750 W was developed to verify the performance for 40–120 V battery charging and discharging requirements. The experimental results demonstrate the effectiveness and validity of the proposed topology and control strategy for high-efficiency, wide-range power conversion applications. Full article

In SRAM-based compute-in-memory (CIM), read-bitline (RBL) charging and discharging depend on the physical bit pattern stored in the memory array, so the energy-relevant code statistic should be defined with respect to the actual read-port polarity. This paper presents a read-polarity-aware row-wise offset-encoding method for W4A8 INT4 weights. In the evaluated Q-sensed 8T topology, the stored logical one is the discharge-active state; hence, the topology-specific read-active density equals the stored-one fraction. Under the exact whole-row INT4-feasibility protocol, a nonzero row offset is accepted only when every translated valid signed-INT4 code remains within [−8, 7]; no clipping, saturation, wraparound, or remapping is permitted, and zero offset remains the fallback. The complete software evaluation covers 286 quantized modules, 579,464 physical 16 × 16 tile positions, and 147,156,296 quantized weights across ResNet-18, MobileNetV3-Small, and SmolLM2-135M. Circuit re-validation uses 300 independent tile-policy samples, 1200 matched baseline-selected bitplane pairs, and 2400 successfully completed transistor-level Spectre simulations. The balanced circuit population yields an aggregate local SRAM readout-energy reduction of 5.03%, with a sample-cluster bootstrap 95% confidence interval of 4.12–6.02%. After four-bitplane aggregation, relative read-active-density reduction and local SRAM readout-energy reduction exhibit Pearson r = 0.81 and Spearman $\rho$ = 0.75, indicating a substantial but imperfect relationship. The directly validated no-offset, positive-offset, and signed-offset policies preserve the corresponding model-level Top-1 accuracy or perplexity. Proposal-specific digital overheads and metadata-storage capacity are quantified separately, whereas representative physical SRAM/ROM metadata-access energy remains uncharacterized. Accordingly, the measured energy benefit is limited to local SRAM readout; a net energy reduction at the complete CIM-macro or system level, robustness across all evaluated PVT conditions, and robustness to process mismatch are not established by the present evidence. Full article

This paper presents the design, simulation, and experimental validation of an Active Compensation System (ACS) intended for bidirectional energy exchange between the utility grid and a battery energy storage system. The proposed architecture combines a bridgeless totem-pole power factor correction converter BLTP-PFC and a bidirectional CLLLC resonant DC/DC converter. A comparative evaluation of different converter topologies is performed considering efficiency, bidirectional operation capability, implementation complexity, and suitability for active compensation applications. Simulation and laboratory measurements verify operation in both charging and discharging modes. Experimental results demonstrate a maximum output power of 2.18 kW, power factor close to unity, current THD of 1.43%, and system efficiency exceeding 96%. The results confirm the suitability of the proposed topology for future smart-grid, renewable-energy, and battery-energy-storage applications. Full article

The precise detection and pose estimation of electric vehicle (EV) charging ports in unstructured outdoor environments remain challenging due to small sizes, variable illumination, and stringent tolerance requirements for robotic plug-in operations. To address these issues, this paper presents a hybrid perception framework that integrates an attention-embedded detection network with geometrically constrained pose optimization. For robust detection, CBAM-YOLOv11 is proposed, which incorporates a sequential channel-spatial attention module into the backbone network to enhance feature representation of texture-less small targets while suppressing background clutter and glare. Then, a topological geometric constraint-based method is developed for accurate pose estimation. Specifically, the 2D-3D correspondences are purified before being fed into an Efficient Perspective-n-Point (EPnP) solver, while a nonlinear refinement with rigid distance priors is applied as regularization. Extensive experiments on the dataset and a physical robotic platform demonstrate that the proposed detector achieves 99.2% mAP@0.5 and a 24.6 percentage point improvement in mAP@0.5:0.95 over the baseline YOLOv11. The pose estimation module reduces positioning standard deviations along the X, Y, and Z axes to 4.72 mm, 5.65 mm, and 5.60 mm, respectively, surpassing conventional EPnP by about 60%. In 30 repeated robotic insertion trials, the system attains a 93.3% success rate with approximately 78 ms, fully satisfying real-time and precision requirements for autonomous EV charging. Full article

Vehicle-side weight is a key constraint in wireless power transfer (WPT) systems for electric vehicles, as it directly affects cost, installation, and vehicle integration. This paper presents a lightweight Vehicle Assembly (VA) based on a conventional Series–Series (SS) compensation topology and a phase-shift-controlled active rectifier, designed within the SAE J2954 framework. The architecture reduces vehicle-side passive components while enabling load adaptation through the rectifier conduction angle. A fixed-output-power time-domain methodology is used to compare two operating strategies. In the exact 2-ZVS mode, only two rectifier commutations satisfy the charge-based ZVS condition, whereas in the robust 4-ZVS mode all four commutations are constrained to achieve ZVS through joint optimization of the rectifier control parameters and switching frequency. In both cases, the primary DC voltage is adjusted to maintain a constant output power of 7.7 kW. Measured coupler parameters are used in the circuit model. Across the aligned position and two measured misalignment conditions, exact 2-ZVS achieves an estimated AC–AC resonant-link efficiency of 98.01–98.41% and a modeled DC–DC efficiency of 96.16–96.90%. Robust 4-ZVS remains feasible, but its higher circulating-current requirement reduces the corresponding efficiencies to 93.26–94.96%, respectively. Therefore, for the investigated system, exact 2-ZVS provides the best efficiency–soft-switching trade-off. The AC–AC metric includes only winding and capacitor-ESR losses. The DC–DC metric additionally includes the modeled conduction and output-capacitance transition losses of the primary inverter and active rectifier; gate-drive, control, and auxiliary losses are excluded. Full article

High-precision two-dimensional intermolecular potential energy surfaces (PESs) for Rg–CuF (Rg = Ar, Kr, Xe) were constructed at the coupled-cluster singles and doubles with non-iterative triples [CCSD(T)] level by employing aug-cc-pVXZ (X = D, T, Q) basis sets, and the energies were extrapolated to the complete basis set (CBS) limit. All three complexes exhibit a consistent topological pattern: the global minimum corresponds to a collinear Rg–Cu–F configuration, and the local minimum corresponds to an anti-linear Rg–F–Cu configuration. As the atomic number of noble gas increases, the Rg–Cu equilibrium distance lengthens while the binding strength remarkably enhances. Bound state calculations were performed based on these PESs to yield rotational levels, which can be used to derive the intermolecular vibrational frequencies, molecular structures and spectroscopic parameters for all primary isotopologues. The predicted rotational constants B are in excellent agreement with the experimental observations, attaining a sub-MHz accuracy at the AVTZ level for Kr–CuF and at the CBS limit for Ar–CuF and Xe–CuF. Vibrational wavefunction analysis reveals that the intermolecular vibrational modes of Kr–CuF and Xe–CuF are highly localized, consistent with the pronounced molecular rigidity observed experimentally. Isotopic effect analysis reveals a well-defined linear relationship between the changes in the rotational constant B and the intermolecular vibrational frequency in relation to the reduced mass of the complex, which provides a reliable basis for predicting spectroscopic parameters of unobserved isotopologues. Symmetry-adapted perturbation theory (SAPT) energy decomposition further demonstrates that the Rg–Cu interaction is dominated by induction forces, with significant contributions from dispersion and electrostatics, and exhibits notable charge transfer character. This polarization and orbital overlap transcend the conventional van der Waals picture and reveal a partially covalent nature in noble gas transition metal interactions. Full article

Accurate prediction of electric vehicle charging demand is imperative for ensuring grid stability and optimizing urban mobility resources. While the emergence of large language models has introduced translation-based forecasting paradigms, existing methods typically suffer from numerical precision loss due to textual tokenization and fail to capture complex, non-Euclidean spatial dependencies. To address these limitations, this study introduces STAR, a spatio-temporal agentic reasoning framework that fundamentally redefines the forecasting task as a generative reasoning process. STAR integrates three core innovations, beginning with a temporal patching alignment mechanism that projects historical time-series segments into dense semantic vectors to preserve numerical fidelity. This is seamlessly combined with a graph-conditioned spatial context fusion module that empowers the agent to retrieve dynamic spatial dependencies via cross-attention-based topological fusion over an urban knowledge graph, thereby linking temporal dynamics with spatial causality. Finally, the framework employs an agentic chain-of-thought inference engine that mandates the generation of explicit reasoning traces by analyzing trends and synthesizing external factors prior to outputting the final forecast. Extensive experiments on ST-EVCDP, an open benchmark dataset collected from Shenzhen for urban EV charging demand prediction, demonstrate that STAR significantly outperforms state-of-the-art baselines, achieving a 27.3% to 41.9% prediction improvement for 60 min horizons compared to existing methods. Furthermore, the framework exhibits exceptional zero-shot cross-zone transferability across unseen traffic districts, providing interpretable decision support for critical infrastructure management. Full article

Current distribution in serial–parallel battery packs is commonly assumed to be uniform in the absence of cell-to-cell variations. However, in practical systems, the electrical topology and finite resistance of current-collecting busbars can introduce significant inhomogeneities even when all cells are identical. In this work, a matrix-based modeling framework is developed to analyze the current and voltage distribution in large battery packs with arbitrary serial–parallel configurations. The results reveal that the resistance of current-supplying busbars plays a dominant role in shaping current distribution, leading to pronounced current imbalance that increases with both resistance and operating C-rate. To quantify this effect, a current non-uniformity factor is introduced and used to define an illustrative criterion for acceptable operation. Based on this metric, together with a maximum-cell-voltage constraint, design maps are constructed to identify operating regions that are acceptable or critical with respect to current overload and localized overvoltage as a function of busbar resistance and charging rate. The analysis further demonstrates that topology-induced current inhomogeneity can lead to cell-level voltage divergence and localized overcharge under high-current operation. Such local effects may remain hidden when only the pack voltage or the voltage of a series-connected cell group is monitored, because conventional battery management systems (BMSs) typically do not resolve individual cell currents or local voltage drops within parallel-connected cell groups. The proposed approach enables the derivation of design-oriented constraints linking electrical performance to physical parameters such as busbar resistance and cell spacing. The resulting design maps provide a practical tool for battery pack engineering, enabling the determination of the maximum allowable busbar resistance or operating current to ensure safe, homogeneous pack operation. Full article

With the wide-scale deployment of battery packs in a variety of applications, some life cycle challenges are coming to light. These challenges include extending their operational life as a pack given their increasing cell-level imbalances and repurposing their cells into new battery packs to give them a second life, e.g., in grid storage. This paper presents a new circuit topology addressing both issues using active (controlled and nondissipative) cell-to-cell balancing for online operation, i.e., while the battery energy storage system is in use. The proposed circuit design is fast and safe for balancing, relying on current control to target each individual cell’s maximum charging and discharging current, while taking into account the pack current. The design has the lowest number of switches and circuit components compared to the state-of-the-art techniques, and is also flexible, allowing for the addition or replacement of cells in series. Its practical hierarchical control system enables speed, reliability, and reconfigurable limits in real-time operation on the individual cells. Experimental validation is carried out on homogeneous and heterogeneous packs in online operation, and the results demonstrate the speed and efficacy of the proposed technique. Full article

Electrochemical impedance spectroscopy (EIS) resolves the internal physicochemical processes of lithium-ion batteries across timescales—from ohmic conduction through charge-transfer kinetics to solid-state diffusion. Despite this analytical power, EIS deployment remains largely confined to laboratory electrochemical workstations that are bulky, expensive, and incapable of online multi-cell operation under dynamic DC bias conditions. This study presents a multi-channel EIS measurement device that simultaneously addresses three requirements for practical battery diagnostics: workstation-grade measurement accuracy, multi-cell synchronous acquisition, and tolerance to the DC bias voltage present across battery terminals during operation. The device employs a master–slave distributed architecture: each slave unit is built around the DNB1101 battery-dedicated impedance measurement chip with a Kelvin four-wire sensing configuration, while the STM32F407-based master controller coordinates measurement scheduling and data communication under FreeRTOS. A four-channel slave board with a differential daisy-chain communication topology and hardware broadcast trigger mechanism supports multi-cell synchronous acquisition. The device operates over a frequency range of 0.01 Hz to 5620 Hz with logarithmic spacing, and a C#-based host application provides real-time Nyquist and Bode visualization along with MATLAB R2024a-based post-processing for outlier rejection and data smoothing. Validation was conducted using Panasonic NCR18650 ternary (NCA) and LiFePO₄ (LFP) 18650 cells, benchmarked against a CorrTest CS350 electrochemical workstation at SOC = 40% and 25 °C. The device achieves a maximum impedance magnitude error of 1.55% and a maximum phase error of 1.22%. Equivalent circuit model fitting via ZSimpWin yields parameter differences below 1% between the device and the reference workstation. Under online conditions with a 3.6 V DC bias, the impedance measurement deviation of a 20 mΩ precision resistor remains below 0.69% across the full frequency range. Multi-channel synchronous measurements across four cells demonstrate inter-channel amplitude variance below 2.13%. Cross-chemistry validation with LiFePO₄ cells yields magnitude and phase errors below 0.92%. These results demonstrate that the proposed device provides laboratory-grade EIS accuracy with multi-channel, online, and cross-chemistry capabilities, offering a practical platform for integrating EIS-based diagnostics into next-generation battery management systems. Full article

Extreme weather couples spatially correlated component damage with photovoltaic (PV) derating, changing electric-vehicle (EV) demand, repair delay, and time-varying network topology. This paper develops a coordinated restoration architecture for multi-area feeders containing PV, battery energy storage, and charging stations. Its weather-facing layer constructs joint outage-risk, renewable-error, charging-demand, and voltage-vulnerability descriptors. Those descriptors parameterize a two-stage mixed-integer second-order-cone program with a finite-support optimal-transport ambiguity set that remains well defined for discontinuous mixed-integer recourse. Regional actor–critic agents propose five-minute corrections around the hourly robust schedule; constrained projection, non-linear AC power-flow screening, emergency fallback, and margin-tightened re-optimization retain the authority to accept or reject each proposal. The evaluation uses public 33-node and 123-node feeders together with synthetic 240-node and 850-node stress networks. A pre-fit manifest allocates 240 records to training, 80 to validation, and 320 to final testing, while aggregate operational outcomes cover 50 random streams. Within this controlled benchmark, accepted schedules restore 93.6% of critical-load energy (SD 2.1 percentage points), serve 96.7% of total demand (SD 1.8 percentage points), retain 82–86% of EV service across hazard classes, and reduce the modeled 24 h objective by 25.8% relative to deterministic dispatch. The full pipeline records two to four candidate-stage voltage-limit events by hazard, and 4.9% of candidates undergo tightened re-optimization before accepted schedules reach zero reported AC voltage-limit violations. Between-method comparisons are descriptive and unpaired; the larger synthetic cases are structural stress tests rather than feeder-transfer tests. Full article

There is a growing trend toward employing two-coil and three-coil systems in magnetically coupled resonance wireless power-transfer (MCR-WPT) technology. However, these configurations have limitations at longer transmission distances and are sensitive to load variations. This paper provides a comprehensive review of four-coil WPT systems, focusing on their design, optimization, and applications. The reviewed literature indicates that four-coil configurations generally maintain higher power-transfer efficiency (PTE) over longer transmission distances, exhibit greater tolerance to misalignment, and show reduced sensitivity to load variations. The literature review indicates that while symmetric designs are easier to analyze, asymmetric configurations may provide higher efficiency and extended transmission range. The review also discusses how four-coil technology can be used in medical implants, sensors, and consumer electronics. It also addresses the current challenges of power and compliance in the electric vehicle (EV) industry. Finally, this paper identifies important areas of research that need to be addressed. Future research should aim to optimize power and efficiency together, explore multi-receiver systems for public charging, and investigate the potential of four-coil technology for Electric Micromobility Vehicles (EMVs). Full article

With the ever-evolving and constantly growing need for electric vehicles (EVs) in the automotive industry, the importance of reliable, efficient, and dynamic EV chargers is increasing. Power electronics is the enabler and forms the execution layer of any charging station. EV charging must now integrate fast control, wide adaptability, bidirectionality, and reliability. The existing literature provides overview studies on the EV charging system, its infrastructure, and necessary power electronics. However, the integration of 5G-enabled EV charging (i.e., data transmission/communication via the 5G network) has introduced new performance expectations that go beyond the capabilities of conventional power converters. This paper presents an in-depth overview of power electronics applications in a 5G-enabled EV charging system. Several key aspects such as advanced converter topologies, a resonant converter for 5G charging, the integration of power electronics with 5G communication, and anomaly and intrusion detection models for a 5G-enabled Blink-2-level EV charger are discussed. Moreover, the challenges and risks of integrating 5G into EV charging infrastructure are discussed. Some recommendations on future research opportunities are provided. This study provides a basic guideline on power electronics applications in a 5G-enabled EV charging system and is therefore valuable to the researchers, scientists, and engineers working in this interesting field. Full article

This paper explores methods to eliminate high-voltage spikes during dead time ($t_{dt}$) in high-frequency inverters for Wireless Power Transfer (WPT) systems, focusing on the transition from traditional Silicon IGBTs to enhancement-mode Gallium Nitride (GaN) HEMTs. At elevated switching frequencies, dead-time parameters strongly govern system efficiency and signal integrity. While IGBTs suffer from reverse-recovery charge ($Q_{rr}$) in antiparallel freewheeling diodes that generates severe voltage spikes, hard-switching GaN systems require precise dead-time minimization to prevent shoot-through while limiting third-quadrant conduction losses. Unlike prior WPT studies bounded by specific hardware setups, this paper presents a baseline technology benchmark that explicitly decouples intrinsic semiconductor commutation physics, specifically $Q_{rr}=0$ versus third-quadrant conduction, from macro-system parameters ($f_{sw}$, power level, and resonant topology). Experimental evaluation of a 130 kHz L-S-tuned GaN full-bridge inverter confirms that primary current commutates via third-quadrant conduction during dead time, completely eliminating reverse-recovery voltage spikes ($I_{rr}=0$). Ultimately, this work demonstrates that GaN’s spike-free operation is an intrinsic device-level property, reframing the dead-time optimization objective from transient overvoltage suppression to third-quadrant conduction loss minimization in next-generation WPT systems. Full article