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Equivalent circuit

An equivalent circuit is an electrical model that represents the behavior of a complex circuit, device, or system at specific terminals using a simpler network of idealized components, such as voltage sources, current sources, resistors, inductors, and capacitors, while preserving the same voltage-current characteristics externally.^[1] This concept allows engineers to analyze and design systems by reducing intricate topologies to manageable forms without altering their observable performance from the perspective of connected loads or sources.^[2] The origins of equivalent circuits trace back to foundational work in electromagnetism and circuit theory in the 19th century, building on principles like Ohm's law and Kirchhoff's laws. Hermann von Helmholtz first formalized the voltage-source equivalent in 1853, demonstrating that any linear network could be modeled as a single electromotive force in series with a resistance.^[2] This idea was independently rediscovered and popularized by Léon Charles Thévenin in 1883, who proposed that the behavior of any linear circuit at a pair of terminals could be replaced by an equivalent voltage source V_{TH} in series with an equivalent resistance R_{TH}. Complementing this, Edward Lawry Norton and Hans Ferdinand Mayer independently developed the current-source equivalent in 1926, with Norton at Bell Labs representing the same circuit as a current source I_N in parallel with R_{TH}, where I_N = V_{TH}/R_{TH}.^[3] Equivalent circuits are fundamental to electrical engineering, enabling efficient analysis of power systems, electronic devices, and signal processing networks by applying theorems like superposition and maximum power transfer.^[2] They are widely used in modeling transistors (e.g., hybrid-pi models for amplifiers),^[1] transformers (e.g., T-equivalent circuits for leakage and magnetizing effects), and even magnetic systems via duality principles that translate flux and magnetomotive force into voltage and current analogs.^[4] In modern applications, such as integrated circuit design and power distribution simulations, these models integrate with computational tools like SPICE for both linear small-signal and nonlinear large-signal behaviors.^[2]

Fundamentals

Definition and Principles

An equivalent circuit is a simplified electrical model that replicates the terminal behavior of a more complex circuit or device, producing identical voltage, current, or power relationships at its ports under specified operating conditions, while disregarding internal details. This approach focuses on external characteristics, such as the current-voltage (I-V) relationship observed across the terminals, allowing engineers to analyze and predict system performance without modeling every component.^[5] Key principles underlying equivalent circuits include the preservation of terminal characteristics, where the simplified model must match the original's response to external stimuli, often assuming linearity for superposition to apply.^[2] Many equivalent circuits rely on lumped-parameter approximations, treating components as discrete elements with negligible physical size relative to signal wavelengths, in contrast to distributed models that account for wave propagation effects along continuous media like transmission lines.^[6] This linearity assumption enables the use of theorems like Thévenin's to derive equivalents for linear networks.^[7] The concept of equivalent circuits emerged in the late 19th century alongside the development of circuit theory, building on foundational work by Gustav Kirchhoff, who formulated his circuit laws in 1845 to analyze currents and voltages in networks.^[2] It was further rooted in Ohm's law from 1827 and the principle of superposition, but the term and formal methods, such as voltage-source equivalents, were solidified in the late 19th century through contributions like those of Léon Thévenin in 1883.^[8] A basic example is a network of resistors connected in series and parallel, which can be simplified to a single equivalent resistor whose resistance value yields the same total current for a given applied voltage in DC analysis.^[7]

Purpose and Limitations

Equivalent circuits serve as simplified representations of complex electrical networks, primarily to facilitate analysis, design, and simulation by reducing intricate topologies to basic components that replicate the original system's terminal characteristics. This approach minimizes computational complexity, allowing engineers to apply standard techniques like Kirchhoff's laws and Ohm's law more efficiently to predict behaviors such as voltage drops and current flows. For instance, in optimization scenarios, equivalent circuits enable impedance matching to achieve maximum power transfer without exhaustive full-circuit evaluations.^[9]^[10] The benefits extend to practical engineering workflows, where these models support quick performance forecasting and modular electronics design by isolating subsystems for independent assessment before assembly. They are particularly valuable in troubleshooting, as they allow identification of bottlenecks through simplified voltage and current predictions, and in simulation tools where reduced models accelerate iterative testing.^[10]^[11] Despite these advantages, equivalent circuits are constrained by their validity within defined frequency ranges and operating conditions; beyond these, parameters like reactances in AC models shift, rendering predictions inaccurate. They typically overlook parasitic elements, such as stray capacitance in high-frequency setups, which can alter real-world responses. Furthermore, the assumption of linearity limits applicability to devices exhibiting nonlinear behavior, like saturated amplifiers.^[10] Equivalent circuits prove inadequate for scenarios demanding distributed models, such as high-frequency RF systems where transmission line effects prevail over lumped approximations, or nanoscale devices influenced by quantum phenomena that defy classical circuit paradigms.^[11]^[10]

Derivation Techniques

Thévenin's Theorem

Thévenin's theorem, named after the French telegraph engineer Léon Charles Thévenin who proposed it in 1883, provides a fundamental method for simplifying linear electrical networks.^[12] The theorem states that any linear electrical network containing voltage sources, current sources, and impedances, when viewed from two terminals, can be replaced by an equivalent circuit consisting of a single voltage source V_{th} in series with an equivalent impedance Z_{th}.^[13] This equivalence holds for both direct current (DC) circuits with resistances and alternating current (AC) circuits with complex impedances, as the linear relationship between voltage and current at the terminals remains unchanged.^[14] To derive the Thévenin equivalent, first determine the open-circuit voltage V_{oc} across the two terminals with no load connected, which directly gives V_{th} = V_{oc}.^[15] Next, deactivate all independent sources in the network—replacing voltage sources with short circuits and current sources with open circuits—while leaving dependent sources active if present. The equivalent impedance Z_{th} is then calculated as the impedance looking into the terminals under these conditions, often by applying a test voltage or current and measuring the ratio.^[13] Alternatively, Z_{th} can be found using the ratio of the open-circuit voltage to the short-circuit current: Z_{th} = V_{oc} / I_{sc}, where I_{sc} is the current through the terminals when shorted.^[16] These formulas enable the reduction of complex networks to a simple series form, facilitating analysis of load effects without resolving the entire original circuit each time. For instance, consider a voltage divider circuit with a 10 V source in series with a 2 kΩ resistor, paralleled by a 3 kΩ resistor across the output terminals. The open-circuit voltage V_{oc} is calculated as V_{th} = 10 \times (3 / (2 + 3)) = 6 V, and with sources deactivated, the equivalent resistance Z_{th} (here, purely resistive) is the parallel combination of 2 kΩ and 3 kΩ, yielding $1.2 kΩ. This Thévenin equivalent—a 6 V source in series with 1.2 kΩ—accurately models the voltage across any load attached to the terminals.^[15]

Norton's Theorem

Norton's theorem states that any linear electrical network containing voltage and current sources and impedances can be replaced, at a pair of terminals, by an equivalent circuit consisting of a single current source I_N in parallel with an equivalent impedance Z_N.^[17] This representation is particularly useful for analyzing networks where the load is connected in parallel, as it directly models the current division across the terminals.^[18] The theorem represents the duality of Thévenin's theorem, which uses a voltage source in series with an impedance; the Norton form interchanges voltage and current while preserving the network's terminal behavior.^[3] It was independently derived in 1926 by Hans Ferdinand Mayer, a researcher at Siemens & Halske, and Edward Lawry Norton, an engineer at Bell Laboratories, building on late 19th-century developments in linear circuit analysis such as Thévenin's 1883 work.^[3] Mayer's derivation appeared in a publication in Telegraf- und Telefonie, while Norton's was detailed in an internal Bell Labs memorandum.^[3] To obtain the Norton equivalent, first calculate the Norton current I_N, which equals the short-circuit current I_{sc} flowing through the terminals when they are directly connected.^[18] This is found using methods like Kirchhoff's current law or superposition with the load removed and terminals shorted.^[17] Next, determine the equivalent impedance Z_N by deactivating all independent sources—replacing voltage sources with short circuits and current sources with open circuits—then computing the impedance seen across the terminals; this Z_N matches the Thévenin impedance Z_{th}.^[17] Equivalently, Z_N = \frac{V_{oc}}{I_{sc}}, where V_{oc} is the open-circuit voltage across the terminals.^[18] The relationship between the Norton and Thévenin equivalents follows from their duality: V_{th} = I_N Z_N and I_N = \frac{V_{th}}{Z_{th}}, with Z_{th} = Z_N.^[17] This allows straightforward conversion between the two forms without recalculating impedances. As an illustrative example, consider a network with a 12 V voltage source in series with a 4 Ω resistor, connected in parallel to another branch with a 6 V voltage source in series with a 6 Ω resistor; the terminals are across the parallel combination.^[18] Shorting the terminals yields I_N = I_{sc} = 2 A, calculated via superposition: the 12 V branch contributes \frac{12}{4} = 3 A toward the short, while the 6 V branch contributes \frac{6}{6} = 1 A away, netting 2 A.^[18] With sources deactivated, Z_N = 4 \, \Omega \parallel 6 \, \Omega = 2.4 \, \Omega.^[18] For a 3 Ω load in parallel, the load current is I_L = I_N \frac{Z_N}{Z_N + 3} = 2 \times \frac{2.4}{2.4 + 3} \approx 0.89 A, simplifying what would otherwise require full network analysis.^[18]

Delta-Wye Transformations

The delta-wye transformation, also known as the Y-Δ or star-delta conversion, provides a method to convert a three-terminal delta (Δ) configuration of resistors into an equivalent wye (Y) configuration, or vice versa, enabling the simplification of resistor networks that resist direct series-parallel reduction. This technique preserves the equivalent resistance between any pair of terminals, making it invaluable for analyzing complex passive circuits without voltage or current sources.^[19] The transformation was originally developed and published by electrical engineer Arthur E. Kennelly in 1899, addressing the equivalence of triangular and three-pointed star arrangements in conducting networks, which were prevalent in early electrical systems such as telephony wiring.^[20]^[21] To derive the delta-to-wye formulas, the equivalent resistance between each pair of terminals is equated between the two configurations, leading to a system of three equations solved for the wye resistances. For a delta network with branch resistances R_a, R_b, and R_c, the corresponding wye resistances are:

R_{Y1} = \frac{R_a R_b}{R_a + R_b + R_c}, \quad R_{Y2} = \frac{R_b R_c}{R_a + R_b + R_c}, \quad R_{Y3} = \frac{R_c R_a}{R_a + R_b + R_c}

A useful property is that the sum of the wye resistances equals the sum of the delta resistances: R_{Y1} + R_{Y2} + R_{Y3} = R_a + R_b + R_c.^[19]/06%3A_Analysis_Theorems_and_Techniques/6.7%3A_Delta-Y_Conversions) Conversely, for the wye-to-delta transformation, starting from wye resistances R_{Y1}, R_{Y2}, and R_{Y3}, the delta resistances are obtained by:

R_a = \frac{R_{Y1} R_{Y2} + R_{Y2} R_{Y3} + R_{Y3} R_{Y1}}{R_{Y3}}, \quad R_b = \frac{R_{Y1} R_{Y2} + R_{Y2} R_{Y3} + R_{Y3} R_{Y1}}{R_{Y1}}, \quad R_c = \frac{R_{Y1} R_{Y2} + R_{Y2} R_{Y3} + R_{Y3} R_{Y1}}{R_{Y2}}

This derivation similarly relies on matching terminal resistances, ensuring electrical equivalence.^[19]/06%3A_Analysis_Theorems_and_Techniques/6.7%3A_Delta-Y_Conversions) As an illustrative example, consider a balanced delta network where each resistor is 6 Ω. Applying the delta-to-wye formulas yields wye resistances of 2 Ω each, since R_{Y1} = \frac{6 \times 6}{6 + 6 + 6} = 2 Ω (and similarly for the others). This conversion simplifies the integration of the network into a larger circuit, such as resolving an unbalanced Wheatstone bridge for balance condition analysis.^[19]/06%3A_Analysis_Theorems_and_Techniques/6.7%3A_Delta-Y_Conversions) This method briefly aids in simplifying parameters for two-port network representations by transforming interconnected resistors.^[19]

Specialized Forms

DC Equivalent Circuits

DC equivalent circuits model the steady-state behavior of electrical networks under direct current conditions, employing resistors to represent dissipative elements and ideal DC voltage or current sources to represent energy inputs. These models exclude the dynamic effects of capacitors and inductors, treating capacitors as open circuits (infinite resistance) and inductors as short circuits (zero resistance) once steady state is achieved, as their voltage and current become constant over time.^[22]^[23] Simplification of these circuits begins with combining resistors: those in series sum directly to form an equivalent resistance, while those in parallel combine via the reciprocal sum formula. For networks with multiple independent sources, the superposition principle is applied, calculating the response due to each source individually (with others deactivated—voltage sources shorted and current sources opened)—and then summing the results to obtain the total steady-state voltages and currents. Techniques such as Thévenin's and Norton's theorems further aid in deriving a simplified equivalent by replacing complex portions with a single voltage source in series with a resistance or a current source in parallel with a resistance, respectively.^[23]^[24] A representative example is a DC power supply network consisting of a 12 V voltage source in series with a 100 Ω resistor, with a 200 Ω resistor connected across the output terminals; this can be reduced to an equivalent 8 V source in series with \frac{200}{3} Ω (approximately 66.7 Ω), enabling prediction of load current as I = \frac{8}{\frac{200}{3} + R_L} for any load R_L. The equivalent resistance R_{eq} serves as a central metric in such analyses and is determined through systematic methods like node-voltage analysis, which solves Kirchhoff's current law equations at network nodes to find voltages relative to a reference, or mesh-current analysis, which applies Kirchhoff's voltage law to loop currents for efficient computation in planar circuits.^[23]^[22] These models are limited to steady-state operation, assuming no time-varying transients; they become accurate only after capacitors have fully charged (reaching their time constant \tau = [RC](/page/RC)) or inductors have stabilized to constant current, ignoring initial switching behaviors that could otherwise dominate short-term responses.^[23]

AC Equivalent Circuits

AC equivalent circuits extend the principles of equivalent circuit modeling to alternating current systems, where frequency-dependent reactive components such as capacitors and inductors play a central role, unlike the time-invariant resistances in DC analysis. These circuits represent the behavior of linear networks under sinusoidal steady-state conditions using complex impedances, defined as Z = R + jX, where R is the resistance, X is the reactance (positive for inductors and negative for capacitors), and j is the imaginary unit. This formulation allows the application of phasor analysis, which transforms time-domain sinusoidal signals into complex numbers for algebraic manipulation, simplifying the solution of Kirchhoff's laws in the frequency domain.^[25]^[26] The Thévenin and Norton theorems, originally developed for DC circuits, are directly applicable to AC equivalents by replacing resistances with impedances. In the Thévenin form, any linear AC network across two terminals can be simplified to a single voltage source V_{th} (a phasor representing the open-circuit voltage) in series with an equivalent impedance Z_{th} (found by deactivating sources and computing the impedance seen from the terminals), capturing both magnitude and phase. Similarly, the Norton equivalent consists of a current source I_n (short-circuit current phasor) in parallel with Z_n = Z_{th}. These representations preserve the network's input-output characteristics at a given frequency, enabling efficient analysis of voltage and current responses.^[10]^[27] A practical example is the reduction of a series RLC filter circuit to its equivalent impedance for frequency response analysis. In such a circuit, the total impedance is Z = R + j(\omega L - 1/(\omega [C](/page/Capacitance))), where \omega is the angular frequency, L is inductance, and [C](/page/Capacitance) is capacitance; this single complex value determines the filter's attenuation and phase shift across frequencies, allowing designers to predict bandpass or low-pass behavior without solving the full differential equations.^[28] Impedance transformation techniques, such as those in ladder or bridged-T networks, further simplify AC equivalents by converting complex configurations into canonical forms while maintaining the overall Z. At resonance, where X_L = |X_C| (i.e., \omega = 1/\sqrt{[LC](/page/LC)}), the reactive components cancel, reducing the equivalent impedance to the purely resistive R, which maximizes current or voltage and minimizes power losses in tuned circuits.^[29]^[30] The development of AC equivalent circuit theory emerged in the early 1900s alongside the rise of AC power systems, pioneered by Charles Proteus Steinmetz, who introduced the use of complex numbers and phasors for circuit analysis in his 1893 work on alternating currents. This approach revolutionized the field by providing a unified framework for handling hysteresis, steady-state, and transient behaviors in polyphase systems. As the zero-frequency limit, DC equivalents align with AC models when reactances vanish (\omega \to 0).^[31]^[32]

Two-Port Networks

A two-port network is an electrical circuit or device characterized by two pairs of terminals, known as ports, where each port consists of a pair of nodes for connecting input and output signals. This model facilitates the analysis of linear networks by relating the voltages and currents at the input port (port 1) to those at the output port (port 2), assuming no direct connection between the ports except through the network itself. Two-port networks are commonly described using parameter sets such as impedance (Z), admittance (Y), hybrid (H), or transmission (ABCD) parameters, each suited to specific circuit configurations and analysis requirements.^[33] Equivalent forms of these parameters enable flexible modeling by converting between sets to match the problem at hand. For instance, Z-parameters express the input and output voltages in terms of input and output currents:

\begin{align} V_1 &= Z_{11} I_1 + Z_{12} I_2, \\ V_2 &= Z_{21} I_1 + Z_{22} I_2, \end{align}

where Z_{11} and Z_{22} are the input and output impedances with the other port open-circuited, and Z_{12} and Z_{21} represent the reverse and forward transfer impedances, respectively.^[33] Similar matrix representations apply to Y-parameters (relating currents to voltages), H-parameters (mixing voltage and current), and ABCD-parameters (relating input to output quantities), with conversion formulas allowing seamless transitions, such as deriving H-parameters from Z-parameters via matrix inversion and substitution.^[34] Simplification of interconnected two-port networks is achieved through parameter manipulation, particularly for cascade (series) connections using ABCD-parameters, where the overall transfer matrix is the product of individual matrices:

\begin{pmatrix} A & B \\ C & D \end{pmatrix}_{\text{total}} = \begin{pmatrix} A_1 & B_1 \\ C_1 & D_1 \end{pmatrix} \begin{pmatrix} A_2 & B_2 \\ C_2 & D_2 \end{pmatrix}.

This multiplicative property simplifies the analysis of multi-stage systems like filters or transmission lines. For parallel connections, Y-parameters are additive, providing another avenue for equivalent circuit reduction. A representative example is modeling a transistor amplifier stage as a two-port network using hybrid parameters, which are ideal for common-emitter configurations. Here, the forward current gain h_{21} (also known as \beta) quantifies the amplification from input current to output current, enabling straightforward calculation of voltage gain as A_v = -h_{21} \frac{R_L}{h_{11}}, where R_L is the load resistance and h_{11} is the input impedance.^[34] In applications involving chains of two-ports, such as multi-stage amplifiers or cascaded filters, the overall equivalent circuit is derived by successively applying the chain rule for ABCD-parameters, yielding a single composite matrix that captures the end-to-end behavior without detailed internal analysis. This approach is essential for designing complex systems where individual stages are treated as modular black boxes. The formalization of two-port network theory emerged in the 1920s, driven by the need to analyze vacuum tube circuits in early radio and telephony equipment, marking a key advancement in linear network synthesis.^[35]

Applications

In Power Systems and Devices

In power systems, equivalent circuits simplify the analysis of complex transmission networks by representing lines with lumped parameters. The nominal π-model, commonly used for medium-length transmission lines (typically 80–250 km), divides the total shunt admittance Y = j \omega C equally between the sending and receiving ends, while the series impedance Z = R + j \omega L connects the midpoints.^[36] This configuration accurately captures voltage regulation and reactive power flow under varying load conditions, enabling efficient power flow studies without solving distributed-parameter equations.^[37] For batteries, particularly lithium-ion (Li-ion) cells used in electric vehicles and portable devices, equivalent circuit models (ECMs) approximate electrochemical behavior through electrical components. A basic ECM consists of an open-circuit voltage (OCV) source in series with an internal resistance R_0, representing ohmic losses, followed by one or more parallel RC branches to model polarization and diffusion effects.^[38] The RC branches capture the transient voltage drop due to charge transfer and solid-phase diffusion, with the terminal voltage given by v_t = OCV - i_t R_0 - V_p, where V_p is the polarization voltage across the RC network.^[38] The simplest variant, known as the Rint model, uses only the series resistance R_{int} alongside OCV, providing a straightforward approach for state-of-charge (SOC) estimation via SOC = \frac{\int i \, dt}{Q_n}, where Q_n is the nominal capacity, though it overlooks dynamic transients.^[39]^[40] In semiconductor devices like bipolar junction transistors (BJTs), small-signal equivalent circuits facilitate amplifier design by linearizing operation around a bias point. The hybrid-π model represents the BJT with a transconductance g_m = I_{C, \text{BIAS}} / V_T (where V_T \approx 25 mV), a base-emitter resistance r_\pi, and controlled current sources, enabling analysis of voltage gain and frequency response in circuits such as common-emitter amplifiers.^[41] This model ignores large-signal nonlinearities, focusing on incremental signals typically below 1% of bias levels for accuracy.^[41] A practical example is the modeling of Li-ion battery discharge curves using a first-order Thevenin equivalent, which includes a series resistance and a single RC branch to represent polarization voltage. During discharge, the terminal voltage v_t initially drops due to R_0 (instantaneous ohmic effect), then gradually due to the RC time constant capturing diffusion-induced polarization, closely matching experimental curves under constant current loads.^[42] This approach validates SOC tracking with errors below 5% in real-time battery management systems.^[42] Recent advancements in ECMs for EV batteries, as of 2023, integrate temperature dependencies to enhance predictive accuracy. Second-order models with hysteresis now incorporate Arrhenius-based variations in polarization resistances R_1 and R_2, where R_1 at 10°C can exceed values at 50°C by over 100 times, reflecting slowed ion diffusion at low temperatures.^[43] These models, validated via electrochemical impedance spectroscopy (EIS) and hybrid pulse power characterization (HPPC), also account for elevated heat generation rates—up to 1.5 times higher at -10°C versus 25°C during 3C discharge—improving thermal management in high-power applications.^[43] As of 2025, further progress includes hybrid neuro-fuzzy approaches combining ECMs with machine learning for adaptive parameter estimation, improving SOC accuracy and reliability in dynamic EV conditions.^[44]

In Biological Systems

Equivalent circuit models in biological systems provide a framework for understanding electrical phenomena in cells and tissues by analogizing ion flows and membrane properties to electrical components such as resistors, capacitors, and batteries. In neuroscience, these models are particularly prominent for describing neuronal excitability and signal propagation. The Hodgkin-Huxley model, developed in the early 1950s, represents the neuronal membrane as an equivalent circuit where variable resistors symbolize the conductances of ion channels for sodium, potassium, and leak currents, while capacitors account for the lipid bilayer's charge storage capacity.^[45] This circuit integrates batteries representing the Nernst equilibrium potentials for each ion species, enabling the simulation of action potential dynamics through voltage-dependent gating variables.^[45] A foundational example is the resting state of the neuron membrane, modeled as a parallel RC circuit in series with a battery that establishes the resting potential, typically around -70 mV, due to unequal ion permeabilities maintained by active pumps. In cell biology, equivalent circuits extend to action potentials across excitable cells like muscle fibers, incorporating voltage-gated conductances that dynamically alter membrane resistance during depolarization and repolarization phases.^[45] Alan Hodgkin and Andrew Huxley formulated this approach based on voltage-clamp experiments on squid giant axons, earning them the 1963 Nobel Prize in Physiology or Medicine for elucidating ion channel mechanisms. Modern extensions incorporate stochastic elements to capture channel noise from finite ion channel numbers, transforming the deterministic equations into probabilistic models that better reflect variability in small neuronal compartments.^[46] Despite their utility, these equivalent circuit models approximate continuous ion fluxes as ohmic conductances, overlooking discrete molecular events like single-channel flickering or spatial heterogeneities in channel distribution.^[47] Thévenin equivalents can simplify analyses of membrane potentials under steady-state conditions by collapsing complex channel interactions into a single voltage source and series resistance.^[48]

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The equivalent circuit model of a Lithium-ion battery is a performance model that uses one or more parallel combinations of resistance, capacitance, and other ...
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How does the Rint model relate to EV battery simulation?
Dec 11, 2024 · The Rint model is the simplest of the common integral order equivalent circuits used to model battery performance.
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On SOC estimation of lithium-ion battery packs based EKF
With Rint equivalent circuit model, this paper employs EKF algorithm to estimate SOC, which takes into consideration both precision requirement of the ...
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BJTs after Biasing: Analyzing BJTs with a Small-Signal Model
Apr 10, 2018 · This article presents two circuits that can be used to analyze the small-signal behavior of a bipolar junction transistor.
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A novel hybrid equivalent circuit model for lithium-ion battery ...
Apr 15, 2021 · The proposed equivalent circuit model of lithium-ion battery is based on Thevenin equivalent circuit model, and a state-of-charge (SOC) part is added into the ...
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Research on electrochemical characteristics and heat generating ...
Feb 15, 2023 · It has been reported that low temperature causes the chemical reaction inside the battery to slow down, which affects the kinetics of charge ...
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AC-Equivalent Circuit Modelling - Technical Articles
Jun 1, 2015 · The basic converters complete equivalent circuits can be studied here which include the basic AC modeling approach and the results for several converters.
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A quantitative description of membrane current and its application to ...
A quantitative description of membrane current and its application to conduction and excitation in nerve - Hodgkin - 1952 - The Journal of Physiology - Wiley ...
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Stochastic versions of the Hodgkin-Huxley equations - PMC - NIH
A Hodgkin-Huxley model algorithm for the numerical simulation of noise in neurons is contracted from a master equation description (cellular automoton) into ...Missing: modern | Show results with:modern
[46]
Limitations of the Hodgkin-Huxley Formalism: Effects of Single ...
Abstract. A standard membrane model, based on the continuous deterministic Hodgkin-Huxley equations, is compared to an alternative membrane model, based.
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Nonlinear equivalent circuits for membranes - PubMed
For each, necessary and sufficient conditions are derived for the existence and uniqueness of either the Thévenin equivalent or the Norton equivalent or both.