Amount Of Electricity Research Articles

Signal Detection by Sensors and Determination of Friction Coefficient During Brake Lining Movement

This article presents a laboratory device by which the course of two signals can be detected using two types of sensors—strain gauges and the DEWESoft DS-NET measuring apparatus. The values of the coefficient of friction of the brake lining when moving against the rotating shell of the brake drum were determined from the physical quantities sensed by tensometric sensors and transformed into electrical quantities. The friction coefficient of the brake lining on the circumference of the rotating brake disc shell can be calculated from the known values measured by the sensors, the design dimensions of the brake, and the revolutions of the rotating parts system. The values of the friction coefficient were measured during brake lining movement. A woven asbestos-free material, Beral 1126, which contained brass fibers and resin additives, showed slightly higher values when rotating at previously tested speeds compared to the friction coefficient values obtained when the brake drum rotation was uniformly delayed. The methodology for determining the friction coefficient of the brake lining allowed the laboratory device to verify its magnitude for different friction materials under various operating conditions.

A STUDY OF SPATIAL VARIABILITY IN A CHESTNUT ORCHARD (Castanea sativa) FOR PRECISION AGRICULTURE PURPOSES

The aim of this study is to study the variability of apparent electrical conductivity, quantity, and quality characteristics in a chestnut farm. The experiment took place in a chestnut orchard located in Agia, Larissa, Greece during the 2022 – 2023 growing season (April 2023 – October 2023), and specifically from the stage of tree dormancy to the stage of harvesting. All cultivation treatments were performed uniformly according to the farmer’s protocols. Soil data and chestnut samples were taken and evaluated to measure the above-mentioned variables (apparent electrical conductivity, quantity, and quality characteristics). The results showed that there was no significant correlation between apparent electrical conductivity and chestnut quality or quantity. They also showed obvious correlation between quantity and quality of chestnuts (high mass means plenty of chestnuts and vice versa).

A Method for Fault Localization in Distribution Networks with High Proportions of Distributed Generation Based on Graph Convolutional Networks

To address the issues arising from the integration of a high proportion of distributed generation (DG) into the distribution network, which has led to the transition from traditional single-source to multi-source distribution systems, resulting in increased complexity of the distribution network topology and difficulties in fault localization, this paper proposes a fault localization method based on graph convolutional networks (GCNs) for distribution networks with a high proportion of distributed generation. By abstracting busbars and lines into graph structure nodes and edges, GCN captures spatial coupling relationships between nodes, using key electrical quantities such as node voltage magnitude, current magnitude, power, and phase angle as input features to construct a fault localization model. A multi-type fault dataset is generated using the Matpower toolbox, and model training is evaluated using K-fold cross-validation. The training process is optimized through early stopping mechanisms and learning rate scheduling. Simulations are conducted based on the IEEE 33-node distribution network benchmark, with photovoltaic generation, wind generation, and energy storage systems connected at specific nodes, validating the model’s fault localization capability under various fault types (single-phase ground fault, phase-to-phase short circuit, and line open circuit). Experimental results demonstrate that the proposed model can effectively locate fault nodes in complex distribution networks with high DG integration, achieving an accuracy of 98.5% and an AUC value of 0.9997. It still shows strong robustness in noisy environments and is significantly higher than convolutional neural networks and other methods in terms of model localization accuracy, training time, F1 score, AUC value, and single fault detection inference time, which has good potential for practical application.

Research on the Carrier Characteristics of Power Cables Considering the Aging Status of Insulation and Semiconducting Layers

The 10 kV XPLE cable is widely used in highly cabled transmission and distribution networks. It is necessary to closely monitor the transient current, harmonic content, and electric field distribution of each layer of the insulation and semiconductive layers of the cable when they age and deteriorate, so as to promptly carry out circuit breaking treatment and prevent safety accidents. Considering the frequency sensitivity and dielectric sensitivity of the distributed Runit, Lunit, Gunit, and Cunit parameters of long cables, this paper quantitatively analyzes the frequency variation of 10 kV cable parameters under different aging states. Reconstructing the frequency variation process of typical electrical quantities through MATLAB PSCAD joint simulation, constructing fault circuits for cable insulation and semiconducting layers, obtaining transient currents in each layer of the cable under aging conditions, and conducting total harmonic distortion (THD) analysis to provide theoretical guidance for the subsequent monitoring and fault diagnosis of distribution cable status.

A flow battery cell testing facility for versatile active material characterization: Features and operations

Technological development plays a fundamental role in view of the successful realization of large Flow Battery (FB) systems. This work firstly presents the design, construction and commissioning of FB-Cell Testing Facility (FB-CTF), a bench for testing electrolytes, electrodes, membrane and cell configurations under controlled conditions. Several construction aspects related to the hydraulic system, power conditioning system, and flow battery management system are described in detail. FB-CTF has been conceived and built to accurately measure the main thermal, hydraulic, electric, and energy quantities which define the performance of FBs. A comprehensive experimental campaign has been carried out on FB-CTF to characterize some widely used electrodes and membranes for Vanadium FBs (VFBs), produced by some major manufacturers. The paper presents the developed testing protocols and the test results, specifically focusing on electrical and hydraulic characterization. In addition, a methodology using FB-CTF data in the prediction of the electric and hydraulic performance of large stacks is proposed. More generally, FB-CTF measurements can be used to address the design of industrial-scale FBs. FB-CTF can provide insights for the design of large flow battery systems, to help bridge the gap between academic research and industry.

An improved k-means cluster method based on partial correlation coefficient for line-transformer connectivity identification in distribution network

Abstract The accurate identification of line-transformer connectivity of the distribution network is very important for load balancing and line loss management. The electric quantity data can be used to identify the relationship, but the recognition accuracy is limited. The essence of relation recognition is unsupervised classification, but as there is no direct center of mass and distance, the traditional mainstream clustering method cannot be applied. Therefore, this paper proposes an improved K-means clustering algorithm based on a partial correlation coefficient. Firstly, spectrum analysis is carried out for the collected power data of the distribution transformer and the 10 kV line, and the high-frequency component of the data is obtained by the high-pass filter. Then, the K-means clustering algorithm improved by the partial correlation coefficient is used to set the electric energy data of each line as the initial centroid. The correlation between the station area and the line is calculated by using the concept of the partial correlation coefficient, and the station area represented by the minimum line distance is assigned to the corresponding line. The results show that this method can improve the accuracy of linear relation identification based on electric quantity data.

Study on electric towing tractor quantity based on cellular automata

Abstract Aircraft ground taxiing contributes significantly to carbon emissions and engine wear. The electric towing tractor (ETT) addresses these issues by towing the aircraft to the runway end, thereby minimising ground taxiing. As the complexity of ETT towing operations increases, both the towing distance and time increase significantly, and the original method for estimating the number of ETTs is no longer applicable. Due to the substantial acquisition cost of ETT and the need to reduce waste while ensuring operational efficiency, this paper introduces for the first time an ETT quantity estimation model that combines simulation and vehicle scheduling models. The simulation model simulates the impact of ETT on apron operations, taxiing on taxiways and takeoffs and landings on runways. Key timing points for ETT usage by each aircraft are identified through simulation, forming the basis for determining the minimum number of vehicles required for airport operations using a hard-time window vehicle scheduling model. To ensure the validity of the model, simulation model verification is conducted. Furthermore, the study explores the influence of vehicle speed and airport scale on the required number of ETTs. The results demonstrate the effective representation of real-airport operations by the simulation model. ETT speed, airport runway and taxiway configurations, takeoff and landing frequencies and imbalances during peak periods all impact the required quantity of ETTs. A comprehensive approach considering these factors is necessary to determine the optimal number of ETTs.

Measurement and Modeling of Self-Directed Channel (SDC) Memristors: An Extensive Study

This study systematically addresses the challenge of accurately modeling memristors, focusing on four distinct types doped with tungsten, tin, chromium, and carbon, fabricated by Knowm Inc. A comprehensive characterization is performed by subjecting the devices to sinusoidal excitations with varying frequencies and amplitudes, followed by data averaging and high-frequency filtering. The resulting measurements are fitted using three prominent memristor models: VTEAM, MMS, and Yakopcic. Additional bespoke modifications are assessed. These models, typically formulated as coupled algebraic differential equations integrating electrical quantities (voltage and current) with internal state variables governing device dynamics, are optimized using two robust approaches: (1) interior-point optimization with gradient-based search, and (2) Nelder–Mead gradient-free optimization, both with box constraints applied. A thorough comparison and discussion of the optimized model parameters ensue, accompanied by an examination of the sensitivity to diverse frequency and amplitude ranges. The findings inform conclusions and provide a foundation for future refinements, underscoring the importance of multi-model evaluation and advanced optimization strategies in precise memristor modeling. The presented methodology offers a valuable framework for elucidating optimal modeling paradigms tailored to specific memristor architectures and operating regimes, ultimately enhancing their integration in emerging neuromorphic and computational applications.

Enhanced Transformer Overcurrent Protection via Oil Temperature Acceleration

When a transformer is in a long-term heavy load operation state, the oil temperature reaches the alarm temperature; if a slight fault occurs inside the transformer, traditional inverse time current protection and other protections that react to phase current may not operate due to insufficient sensitivity or they may operate for too long. Based on this, this article proposes a new principle of accelerating inverse time overcurrent protection based on transformer oil temperature. The proposed method uses transformer oil temperature to accelerate the action time of traditional inverse-time overcurrent protection, then introduces the transformer oil temperature factor and acceleration index to optimize the inverse time characteristic curve, and establishes a mathematical model to optimize the adjustment for the complexity of adjustment of the protection action equation and the risk of mismatch of the protection after the acceleration of oil temperature. The existing theoretical analysis and simulation verification results show that the proposed new overcurrent protection scheme based on the transformer oil temperature acceleration inverse time can effectively improve the protection of the rapidity and sensitivity, providing a new research idea for the combination of non-electrical and electrical quantity protection.

Investigation of ELectrochemical Behavior of Ferri/Ferrocyanide Redox on Carbon Paste Based Electrodes for Mercury (II) Electrochemical Sensor

The electrochemical characterisation of the materials used to make sensors is mostly based on the cyclic voltametry method. Cyclic voltametry is an electrical method for the dynamic study of electrochemical systems. Through a reversible potential sweep, the material is studied in contact with the ferri/ferrocyanide. Ferri/Ferrocyanide is one of the most studied chemical compounds in electrochemistry and photo-electrochemistry because of its singular known and controlled reactivity. The appearance of voltamorams and mathematical expressions make it possible to collect the information necessary for understanding the reaction. An electrode material is considered active if it shows a reversible peak in contact with the redox marker in cyclic voltametry. The mechanism of the reaction is also assessed using the peak potential difference ΔEp. The nature of the mass transport is determined by the anodic and cathodic peak current ratio Ipa/Ipc. The aim of this work is to compare the electrochemical activity of the Feri/Ferrocyanide couple achieved with carbon paste-based electrodes for application to the electrochemical sensor. The study of the peak potential difference ΔEp showed that the composition of the electrode material influences the reaction mechanism at the interface. Material transport and electronic charge transfer are impacted by complex phenomena. By studying the electrical quantities potential difference ΔEp, formal standard potential E° and current ratio Ipa/Ipc, the electrochemical sensors developed can be optimised.

Green electricity product menu design for retailers without knowing consumer environmental awareness

Adverse selection problem due to asymmetry of consumer environmental awareness (CEA) could reduce electricity retailer's profit and obstructs renewable energy (RE) consumption. This study analyzes mechanism design problem of retailer constricted by RE consumption quota to incentive consumers display true CEA in competitive retail market. Based on principal-agent theory, we develop an extended principal-agent model with the addition of an RE consumption quota constraint to design a green electricity product menu which includes the green level, the price and electric quantity. Influence of information symmetry and quota setting on product attributes, retailer's profit, consumer utility, RE consumption is analyzed, and results show that: (1) Compare to symmetric information, under asymmetric information, green level of product provided to consumers with CEA (denoted as C1) distorts upward, information rent is greater than zero when quota is large, while green level of product provided to consumers without CEA (denoted as C2) distorts downward, with no information rent. (2) Under asymmetric information, unit environmental premium (UEP) of green electricity positively relates to proportion of C1, CEA level, and incremental WTP, and reaches the maximum value at a certain quota. (3) Under asymmetric information, retailer's profit and RE consumption positively relates to proportion of C1, and CEA level. (4) Under asymmetric information, quota difference could contribute to improve retail service quality under competitive retail market, and RE consumption elevation.

Time and Metrology

The recourse to Quantum Mechanics for the definition of the International System of Units has been the trigger of significant progress. In the first part of the paper, we briefly recall the definitions of units now in use for the basic quantities. We summarize the levels of precision available today within the framework of these definitions. Time, whether we are aware of it or not, is a very special physical quantity. We therefore expose the extended use that could be made of the expression of physical quantities by means of time, like what is already practiced for the masses, expressed by means of energies. We detail a little more the case of the electrical quantities voltage and resistance which, without being basic quantities, benefit from new approaches thanks to two quantum phenomena: the Josephson effect, and the Quantum Hall Effect. But time is not an absolute. The next part of the paper exposes the corresponding teachings brought by Special Relativity on the one hand, and General Relativity on the other hand. Finally, the perspectives of the field are approached under the aspect of the metrological repercussions. Indeed, the technologies applicable to the measurement of time lead to performances that can be considered extraordinary in absolute terms, and in any case superior in relative to anything that can be achieved for other physical quantities. In conclusion, we examine the challenge that may represent the achievement of ever-increasing metrological performance for all physical quantities, and for time in particular, and the perspectives opened up for research in the domain by fields of knowledge not yet covered.

Electricity Conservation among Rural Households in Bunkpurugu-Nakpanduri District in the Northeast Region of Ghana

Residential energy use contributes significantly to the world's energy demand. It makes up 20% of all energy use. It is expected to rise by 40% by 2040 in developing nations due to urbanization. The adoption of energy conservation measures presents the possibility of reducing electricity consumption by reducing the price and quantity of electricity required by households. This paper examines the nature of electricity conservation among rural households in Ghana. The study was conducted through the administration of questionnaires to 156 households in six rural communities. The findings revealed that the average household size in the study area is above the national average, which affects electricity conservation practices. Level of education was found to have an influence on conservation practices; those who have attained some form of formal education adopted conservation practices. Many of the households did not know that a change in electricity saving behaviour reduces electricity consumption. Therefore, there is a need for the Ghanaian government and the electricity service providers to conduct periodic awareness campaigns in rural areas to educate them about electricity conservation and save energy waste.

Improvement of metrology infrastructure in the area of extreme impedance calibrations

The paper describes how the Laboratory for Electrical Measurements at the Ss. Cyril and Methodius University in Skopje, an accredited calibration laboratory, enhanced its calibration and measurement capabilities for extreme values of electrical impedance. This was conducted through development of new calibration methods for instruments that measure extreme electrical resistance and inductance. The paper also explains how these methods were validated to ensure traceability and how the measurement uncertainty in impedance instruments calibration was innovatively estimated, by deploying the data fusion concept to increase the metrology infrastructure capacity. As the testing facilities for electrical quantities in Southeast Europe are not sufficiently developed, and some calibration areas of electrical instruments are not well provided by the existing laboratories, despite the economic and scientific demands, the relevance of this metrology infrastructure upgrade is evident.

Neural Network-Based Aggregated Equivalent Modeling of Distributed Photovoltaic External Characteristics of Faults

Distributed power networks have a large number of photovoltaic power sources. The bidirection of power flow, different transient control strategies, and installation locations make the transient characteristics highly complex and unpredictable. The vast network of the distribution system makes it almost impossible to predict the electrical quantities of each branch. Reasonable aggregation modeling of the distribution network can greatly simplify the network topology, facilitating transient control and the setting of relay protection settings. An aggregated equivalent modeling method based on the LSTM neural network for distributed PV fault external characteristics is proposed. This method equates the complex distribution network to a highly nonlinear but controllable current source. The method can output the I–V curves of equivalent PV system parallel points under any output power and is able to predict the fault characteristics of the equivalent system after a voltage drop at the parallel point. Compared to traditional mechanistic modeling, this method does not require specific modeling of complex physical systems and is able to accurately map the strong nonlinear inputs and outputs of distribution networks. The established LSTM model first uses a one-dimensional convolutional layer for feature extraction of the PV power coefficients (input), and then two hidden layers are utilized to process the sequence data; the vectors are mapped into a sequence of external characteristic curves (output) in a fully connected layer. A typical distribution network is built based on the traditional PV power model, and a large number of different output combinations are selected for simulation to provide an effective training set and validation set data for LSTM model training. By using the training set data, the weights and offset coefficients of each layer of the LSTM are continuously optimized until the model with the smallest overall error is obtained, which is the optimal model. Finally, the optimal model is utilized to establish an equivalent distribution network system, different degrees of voltage drops are set up at the grid-connected points, the fault characteristics are compared with those of the complete model, and the simulation results can prove the reliability and practicality of the proposed method.

Dosimetry for repetitive transcranial magnetic stimulation: a translational study from Alzheimer's disease patients to controlledin vitroinvestigations.

Objective.Recent studies have indicated that repetitive transcranial magnetic stimulation (rTMS) could enhance cognition in Alzheimer's Disease (AD) patients, but to now the molecular-level interaction mechanisms driving this effect remain poorly understood. While cognitive scores have been the primary measure of rTMS effectiveness, employing molecular-based approaches could offer more precise treatment predictions and prognoses. To reach this goal, it is fundamental to assess the electric field (E-field) and the induced current densities (J) within the stimulated brain areas and to translate these values toin vitrosystems specifically devoted in investigating molecular-based interactions of this stimulation.Approach.This paper offers a methodological procedure to guide dosimetric assessment to translate the E-field induced in humans (in a specific pilot study) intoin vitrosettings. Electromagnetic simulations on patients' head models and cellular holders were conducted to characterize exposure conditions and determine necessary adjustments forin vitroreplication of the same dose delivered in humans using the same stimulating coil.Main results.Our study highlighted the levels of E-field andJinduced in the target brain region and showed that the computed E-field andJwere different among patients that underwent the treatment, so to replicate the exposure to thein vitrosystem, we have to consider a range of electric quantities as reference. To match the E-field to the levels calculated in patients' brains, an increase of at least the 25% in the coil feeding current is necessary whenin vitrostimulations are performed. Conversely, to equalize current densities, modifications in the cells culture medium conductivity have to be implemented reducing it to one fifth of its value.Significance.This dosimetric assessment and subsequent experimental adjustments are essential to achieve controlledin vitroexperiments to better understand rTMS effects on AD cognition. Dosimetry is a fundamental step for comparing the cognitive effects with those obtained by stimulating a cellular model at an equal dose rigorously evaluated.

(Digital Presentation) The Effects of Heat Treatment on Electroreduction of Tungsten (VI) Oxide

According to the classic scheme of the FFC Cambridge process, oxides of refractory metals are reduced in the solid state. Before electrolysis, oxides are shaped into cylindrical preforms and annealed at high-temperatures (~1000 °С). Therefore, the purpose of this study is to establish the effect of heat treatment of the initial sample of tungsten trioxide on its electrochemical reduction on a solid cathode in a CaCl2–NaCl melt.There are two types of tablets (preforms) were used for research: non-sintered (only compressed) WO3 and annealed at a temperature of 1000 °C. The surface of a pelletized tungsten trioxide sample without sintering is characterized by a uniform distribution of particles, shown in the SEM image (Fig. a). The particles agglomeration is characteristic for the sample WO3 after heat treatment (1000 °С) (Fig. b), which leads to a decrease in the area and an increase in the size of the voids. The unsintered sample has a larger surface area between the particles due to their dispersed state, which facilitates the penetration of the melt compared to the annealed sample.Electrochemical reduction of pressed WO3 samples (d=0.8 cm, h=0.15±0.20 cm, m=0.45–0.50 g) was carried out under galvanostatic conditions (800 °С) with using steel as the cathode and graphite as the anode. It was established that preliminary heat treatment of WO3 does not contribute to its electrochemical reduction. After applying 1.20 A·h of electricity, the porous granules of unsintered WO3 were completely transformed into metallic tungsten (W), which is shown in Fig. c, line 1. However, sintered samples after electrolysis (quantity of electricity is 1.42 A·h) reduced only partially: W – 74.1%; CaWO4 – 25.9% (Fig. c, line. 2).The results show that the reduction occurs more intensively in samples with more micropores, through which mass transfer occurs at the phase interface: tungsten compound to be reduced molten electrolyte mixture. That is why in the unsintered WO3 sample, the electrochemical reduction is faster. It can be assumed that the degree of reduction of WO3 on a solid electrode in CaCl2–NaCl also depends on its crystal structure. The annealed sample (tetragonal structure) is less susceptible to electrochemical reduction compared to the unannealed sample of tungsten trioxide (monoclinic structure). This is due to the fact that tetragonal WO3 (above 740 °C) is resistant to chemical attack, a poor conductor of electricity and has a low surface area. Monoclinic WO3 (from 17 to 330 °C) is more reactive, a better conductor of electricity and has a higher surface area. Figure 1

Diagnosis of Polymer Electrolyte Fuel Cell: Should We Rely Only on Electrical Quantities?

Polymer electrolyte fuel cells (PEMFC) will play a central role in the establishment of a de-carbonized society. They are seen as a key technology to empower electric heavy-duty vehicles. However, the lifespan is still below the fixed standards for their commercialization. A way to increase their durability is to complement them during operation with a mitigation strategy enabling to avoid the arise of faulty states accelerating degradation processes. Nowadays, most of the proposed fault identification and isolation architectures rely on monitoring of the performance through electrochemical impedance spectroscopy (EIS). Nevertheless, the analysis of impedance data is often complicated, since the contribution of many processes in the EIS spectra are coupled with each other and, for this reason, difficult to identify. This constitutes a limiting factor for its employment as diagnostic tool. In the last years, in order to overcome such issues, the use of nonelectrical periodic inputs and/or outputs has been advanced. The idea motivating this research direction is the possibility to detect the contribution of selected processes on the performance of PEMFCs separating them from the others. Novel frequency response techniques involving back pressure, temperature and partial pressure have been developed [1].In this contribution, the so-called concentration frequency response analysis (CFRA) is considered [2, 3]. It consists on perturbing the cathode side of the cell with a feed characterized by a periodic partial pressure of oxygen and water, and the detection of the electric response, voltage or current. A test station has been designed and constructed in order to apply this technique and investigate its capabilities. A model based analysis of the measured CFRA spectra indicates the possibility to decouple the contributions of the water transport into Nafion and oxygen mass transport on the performance of the cell depending on the chosen concentration input and electrical output. In this way, the analysis and identification of the related power losses is simplified with respect to classic EIS.Moreover, the performance of a fault identification and isolation architecture employing CFRA as monitoring technique have been evaluated and compared to EIS. For such purpose, an identifiability analysis of parameters related to faulty states and obtained by model fitting to spectra of each technique has been performed. The results clearly show that the employment of CFRA based on water pressure input offers the most reliable parameter estimation and, consequently, constitutes the most preferable diagnosis method among the others analyzed.

Development of a prototype to evaluate and monitor energy efficiency aiming at power quality 4.0

In research and development projects, the need to implement prototypes to speed up the development and delivery process is paramount, offering tools to validate scenarios and anticipate challenges. The aim of this research is to experimentally develop a prototype for monitoring electrical power systems using a gateway that converts MODBUS-RTU communication protocols to TCP, providing useful information for technicians and managers of a company in the Manaus Industrial Estate (PIM) in the field of reflective tapes. To achieve this goal, it was necessary to specify the technical requirements for panel assembly and communication via MODBUS, acquire and research materials in accordance with the technical specifications and technological requirements, implement the monitoring system with an IMS Controller for reactive power compensation, and configure and parameterise the MODBUS protocol via the RTU to TCP converter. The prototype is expected to be able to take accurate measurements and, in the data acquisition process, obtain readings of electrical quantities such as: voltage per phase; current per phase; power factor per phase; active power per phase; reactive power per phase; apparent power per phase; frequency; voltage THD and voltage harmonics. The prototype must act intelligently to drive the capacitor bank to control and monitor reactive power. The development of the prototype included crucial stages such as the specification of technical requirements, the acquisition of suitable materials, and the implementation and configuration of the system. The specification ensured that the components were aligned with the project objectives, while the procurement of materials ensured the quality and efficiency of the system. The implementation of the Automatic Reactive Power Compensation Controller was vital for reactive power compensation and the configuration of the MODBUS protocol ensured precise communication between the components. To summarise, this project demonstrates the importance of prototypes in technological advancement, offering practical and efficient solutions for industry. The prototype developed to monitor electrical power systems through a MODBUS-RTU to TCP protocol converter gateway represents a significant advance, providing essential data and contributing to informed decision-making, improving the performance and management of the company's energy resources.

Mechanisms for the evolution of cell-to-cell variations and their impacts on fast-charging performance within a lithium-ion battery pack

Cell-to-cell variations (CtCV) compromise the electrochemical performance of battery packs, yet the evolutional mechanism and quantitative impacts of CtCV on the pack’s fast-charging performance remain unexplored. This knowledge gap is vital for the proliferation of electric vehicles. This study underlies the relationship between CtCV and charging performance by assessing the pack’s charge speed, final electric quantity, and temperature consistency. Cell variations and pack status are depicted using 2D parameter diagrams, and an mPnS configured pack model is built upon a decomposed electrode cell model. Variations in three single electric parameters, i.e., capacity (Q), electric quantity (E), and internal resistance (R), and their dual interactions, i.e., E-Q and R-Q, are analyzed carefully. The results indicate that Q variations predominantly affect the final electric quantity of the pack, while R variations impact the charge speed most. With incremental variances in cell parameters, the pack’s fast-charging capability first declines linearly and then deteriorates sharply as variations intensify. This research elucidates the correlations between pack charging capabilities and cell variations, providing essential insights for optimizing cell sorting and assembly, battery management design, and charging protocol development for battery packs.