Spatial Equivalent Circuit Model for Simulation of On-Chip Thermoelectric Harvesters

Lineykin, Simon; Sitbon, Moshe; Kuperman, Alon

doi:10.3390/mi11060574

Cited by 8 publications

(3 citation statements)

References 30 publications

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“…On the other hand, Figure 7b, shows the thermal circuit of one volume element where C T is the thermal capacitance representing the storage energy rate in a small volume of solid [32]. The conduction heat transfer resistance is modelled with the six thermal resistances oriented from the center of the volume element [33,34]. The other two resistors are used to model the convective heat flow between the metal surface and the environment.…”

Section: Thermal Distributed Element Circuitmentioning

confidence: 99%

Digital Twin-Enabled Modelling of a Multivariable Temperature Uniformity Control System

Araque,

Angel,

Viola

et al. 2024

Electronics

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The use of a digital twin as an enabling technology for industry 4.0 provides control systems engineers with novel tools for modelling, designing, and controlling complex systems, providing a deep understanding of the physical asset based not only on its physics but also the real system’s response. It is particularly critical for uniformity temperature control applications, where providing a reasonable model of the system’s diffusion is always affected by the physical behavior of the system’s components required for heating, cooling, or power distribution. In this paper, a digital twin is used to represent a multivariable thermoelectric system employed for temperature uniformity distribution control with potential applications in semiconductor manufacturing. The modelling employs a five-step methodological framework consisting of the stages: target system definition, system description, multiphysics and data-driven simulation, behavioral matching, and implementation to represent the system’s temperature distribution accurately. The temperature distribution is measured using an infrared thermal camera to perform model behavioral matching on heating and cooling temperature uniformity applications. The obtained results indicated that using digital twins not only increases the accuracy of the system’s representation but can also provide the system with novel information that can be leveraged for the design and implementation of smart control systems.

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Section: Thermal Distributed Element Circuitmentioning

confidence: 99%

Digital Twin-Enabled Modelling of a Multivariable Temperature Uniformity Control System

Araque,

Angel,

Viola

et al. 2024

Electronics

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“…In heat transfer, equations and variables that describe thermal behavior have similar concepts in circuits, temperature analogy with voltage, thermal power analogy with current, thermal resistance analogy with resistance, and heat capacity analogy with capacitance. The equation ( 2) can be further transformed into the following form, both sides of this equation are functions of thermal power, similar to the KCL equation in the thermal domain [18,19]:…”

Section: Two-dimension Equivalent Circuit Modelmentioning

confidence: 99%

Efficient system-level simulations of thermal wind sensors considering environmental factors

Wang¹,

Zhou²,

Yi³

et al. 2022

J. Micromech. Microeng.

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For the development of MEMS technology during the past several years, MEMS design has requirements of high precision, high efficiency, iterative design, joint design of structure and circuit and so on. With the improvement of thermal wind sensor performance requirements and the complexity of the application environment, it is becoming increasingly difficult to ignore the impact of environmental factors. However, there is no system-level model considering the influence of environmental factors adequately in macro model. To solve these problems, a 2-D thermal wind sensor macro model considering environmental factors is proposed. In order to build a macro model which can reflect the output of sensors in different environments, this paper, starting from the basic law of heat transfer, proposes an accurate macro model of the thermal wind sensor. The model proposed in this study accurately considers the influence of thermal and transport properties in different environments, and can be simulated together with the interface circuits in Cadence software. The results indicate that the variation of temperature and atmospheric pressure in the natural range can affect the sensor output by more than 15%, and the influence of relative humidity should not be ignored when the temperature is higher than 70 ℃. Furthermore, the flow direction over the sensor can be further studied according to the 2-D equivalent circuit model. The simulation results agree well with the experimental results, and the results can provide a valuable reference for the research and practical application of thermal wind sensors.

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“…The use of electrical analogies for modeling non-electrical processes is a widespread practice. An example would be thermal processes in thermoelectric systems [ 18 ], dynamic mechanical processes [ 19 ], gas-discharge bulbs behavior [ 20 ], subsea observation networks [ 21 , 22 ], and even macro-processes, such as photovoltaic cells and panels [ 23 ], urban train traffic [ 24 ], and more. This technique is especially effective in cases where the model under study is part of a complex system and must be analyzed and simulated together with the system’s electronic (or electrical) components.…”

Section: Introductionmentioning

confidence: 99%

Static, Dynamic, and Signal-to-Noise Analysis of a Solid-State Magnetoelectric (Me) Sensor with a Spice-Based Circuit Simulator

Sindler

Lineykin

2022

Sensors

Self Cite

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Modeling the non-electrical processes by equivalent electrical circuits is a widely known and successfully used technique in research and development. Although finite element methods software development has supplanted electrical analogy techniques due to greater accuracy and intuitiveness in recent decades, the modeling of physical processes based on analogies has several advantages in some cases. Representation of physical processes in the form of lumped circuits and graphs allows researchers to estimate the system with an alternative view, use standardized methods for solving electrical circuits for non-electrical systems, and, most importantly, allows us to use electrical circuit simulators with their unique capabilities. Of particular interest for using the analogy technique are systems that include electronic components along with components belonging to other physical domains, such as mechanical, thermal, magnetic, and others. A solid-state magnetoelectric (МЕ) sensor equipped with a charge amplifier is proposed in this study as an example of analysis using the equivalent electrical circuit and simulating these circuits using SPICE-based circuit simulators. Sensor analysis is conducted with an emphasis on noise budgeting and optimizing the sensor’s signal-to-noise ratio and resolution. In addition, the steady state, the phasor, and transient types of analyses were employed to study the static and dynamic behavior of the system. Validation of the model using analytical calculations and comparison with experimental data demonstrated superior results.

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Spatial Equivalent Circuit Model for Simulation of On-Chip Thermoelectric Harvesters

Cited by 8 publications

References 30 publications

Digital Twin-Enabled Modelling of a Multivariable Temperature Uniformity Control System

Digital Twin-Enabled Modelling of a Multivariable Temperature Uniformity Control System

Efficient system-level simulations of thermal wind sensors considering environmental factors

Static, Dynamic, and Signal-to-Noise Analysis of a Solid-State Magnetoelectric (Me) Sensor with a Spice-Based Circuit Simulator

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